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Confidential Information Ensurance Through Physical Layer Security in Device-to-Device Communication
Abstract
This paper inquires the achievement of secret key generation (SKG) in device-to-device (D2D) communications with the aid of relay. The confidential information between D2D users is taken under the consideration of physical layer secret key generation scheme with the help of colluding or non-colluding relay node. The selected relay conforms to help in the generation of secret keys to keep the information confidential from eavesdropping. In order to ensure the information confidential between D2D users, we explicate a mechanism for selecting relay node based on two basic social phenomena for the selection of relay node. The non-colluding relay selection is considered under the scenario of social trust, while colluding relay selection is based on social reciprocity. Furthermore, we utilize coalition game theory for the selection of optimal relay node in order to improve secret key generation rate (SKGR). Particularly, to attain more eminent SKGR within channel coherence time, the coalition game approach is determined to select an optimal node for relaying by D2D users. On the basis of relay selection, social phenomena, and coalition game theory, we propose an algorithm for achieving higher SKGR. The generated keys are not only protected from eavesdropper but also from the selected (colluding or non-colluding) relay. The performance of our proposed scheme validates and guarantees information confidentiality in D2D communications.
... Although research on physical layer security has been conducted for several years, there are still few applications because most schemes cannot meet the requirement of lowcost implementation. As proved in [16,17], ST have strict requirements for the number of antennas to inject artificial interference while transmitting confidential information, which inevitably increases energy consumption. As for SKG, interactively sending reconciliation signal is necessary for both legal parties to reduce the negative impact of imperfect CSI and correct error key bits, which also results in large overhead [18]. ...
... en, Alice sends them to Bob through the public channel. Since the generator matrix is well known, it divulges (n s − k s ) bits secret keys [17], so the length of available secret keys L key 1 after information reconciliation is L key 1 � k s − n s − k s , for η ∈ (0.5, 1), ...
... As can be observed from the figures, the simulation and numerical results match very well. Figures 6 and 7 show the channel capacity of equivalent interference channel of Alice-Bob and Alice-Eve, where C AB and C AE are calculated according to (17) and (18). According to Figure 6, one can see that the increase in c p significantly improves C AB , and, for different c p , q is different when C AB is the maximum. ...
Due to the channel estimation error, most of the physical layer secret key generation schemes need information reconciliation to correct error key bits, resulting in reduced efficiency. To solve the problem, this work proposes a novel secure communication scheme based on a equivalent interference channel. Different keys generated from imperfect channel state information are directly applied to signal scrambling and descrambling, which is equivalent to the process of a signal passing through an interference channel. Legitimate communication parties can reduce interference with the help of similar keys and channel coding without sending additional signals, while the eavesdropper channel is deteriorated due to the spatial decorrelation. For this kind of schemes, we first establish a discrete memoryless broadcast channel model to derive the expressions of bit error rate (BER), channel capacity, and security capacity for performance analysis. Simulation results verify the derivations that the proposed scheme achieves secure communication with a correlated eavesdropping channel and has a higher upper bound of transmission rate. Furthermore, we design a new metric to evaluate the efficiency and the result shows that the proposed scheme has superior performance on error reconciliation efficiency, despite its slight increase in BER.
... Classical encryption techniques are typically used for securing information between communicating parties based on secret key sharing. Nevertheless, this technique is less attractive for distributed systems because, unlike centralised systems, mobile devices have limited computational capability and are deployed in large areas [10]. Moreover, the secret keys depend on every user possessing a public key certificate. ...
... As eavesdroppers do not know the channel variations between the two communicating authorised users, it becomes hard for them to read the transmitted messages between two users. As a result, the PLS scheme comes into play by exploiting the dynamicity of the wireless channel to counter the eavesdropping attack [10]. ...
... The low rate of SKG is due to the small variations in the wireless channel that lead to weak randomness in the channel. Therefore, the legitimate users generate shorter length of secret keys due to the limited time period, known as the channel coherence time [10] as there are two principle metrics in the SKG rate (SKGR) equation, i.e. coherence time and power. We demonstrate the effect of optimising power allocations for SKGR in WCN due to overcoming the limitation of coherence time. ...
The intrinsic broadcast nature of wireless communication let the attackers to initiate several passive attacks such as eavesdropping. In this attack, the attackers do not disturb/stop or interrupt the communication channel, but it will silently steal the information between authentic users. For this purpose, physical layer security (PLS) is one of the promising methodologies to secure wireless transmissions from eavesdroppers. However, PLS is further divided into keyless security and secret key‐based security. The keyless security is not practically implemented because it requires full/part of instantaneous/statistical channel state information (CSI) of the eavesdroppers. Alternatively, key‐based security is exploiting the randomness and reciprocity of wireless channels that do not require any CSI from an eavesdropper. The secret key‐based security is due to the unpredictability of wireless channels between two users. However, the secret key‐based security mainly on two basic parameters, i.e. coherence time and transmission power. Nevertheless, the wireless channel between users has a short coherence time, and it will provide shorter keys' length due to which eavesdropper can easily extract keys between communicating parties. To overcome this limitation, we proposed the power allocation scheme to improve the secret key generation rate (SKGR) to strengthen the security between authentic users.
... In IoT edge computing, since the task generation process is highly dynamic, statistics are difficult to obtain or accurately predict [10,11]. Chen et al. [12] proposed a dynamic computation offloading algorithm based on stochastic optimization. ...
... The service range of each wireless AP is 50×50m, and the speed of each wireless mobile IoT device is randomly 0-40m/s. Initially, there are IoT devices within the service range of each AP, and the probability of each IoT device generating unloading requests in batches at each time satisfies the Poisson distribution [51,11]. ...
Currently, the deep integration of the Internet of Things (IoT) and edge computing has improved the computing capability of the IoT perception layer. Existing offloading techniques for edge computing suffer from the single problem of solidifying offloading policies. Based on this, combined with the characteristics of deep reinforcement learning, this paper investigates a computation offloading optimization scheme for the perception layer. The algorithm can adaptively adjust the computational task offloading policy of IoT terminals according to the network changes in the perception layer. Experiments show that the algorithm effectively improves the operational efficiency of the IoT perceptual layer and reduces the average task delay compared with other offloading algorithms.
... The downside is the difficulty of achieving perfect secrecy due to the limited key length, sensitivity to channel estimation and reciprocity mismatch errors. Moreover, processing on both sides incurring power, latency, and overhead costs (Waqas et al., 2018b;Sharma et al., May, 2022;Pogaku et al., Feb, 2022). ...
Unmanned aerial vehicles (UAVs) have attracted much attention for civil and military uses because of their high mobility and adaptable deployment capabilities in open spaces. They facilitate agile communications and ubiquitous connectivity. UAVs benefit from dominant line-of-sight communication links but are more susceptible to adversary eavesdropping attacks. Since upper-layer cryptography methods may be insufficient, physical-layer security (PLS) is an attractive alternative. PLS capitalizes on the inherent randomness of wireless channels to improve information confidentiality, particularly in UAV systems.
This article provides a comprehensive overview of PLS in the context of UAV systems, examining various communication channels, including ground-to-air (G2A), ground-to-ground (G2G), air-to-ground (A2G), and air-to-air (A2A). First, we give a general review of UAV communications, emphasizing its functions as user equipment, base station (BS), and mobile relay. Following that, we provide an overview of PLS and its forms. The survey organizes the most advanced PLS techniques against passive wireless eavesdropping regarding the channels they are designed to protect. These schemes are further categorized into optimization and secrecy performance analysis. We examine technical aspects within each sub-category and classify core contributions based on approaches and objectives to improve secrecy performance. Moreover, we added summary tables of the identified schemes considering optimization and secrecy performance analysis domains for each category, providing an in-depth understanding of their technical aspects. In addition, we discuss open research issues and identify future research directions to address evolving threats and requirements in UAV communications to improve information confidentiality.
... Each vehicle consists of public/private secret keys, which are generated by the R at registration process. The vehicles can use the public key in their zones for data communication [18,19]. The private key can be used during the migration from one zone to another zone, and communications with other vehicles in different zones. ...
With the development of communication network and technology, Internet of Vehicles (IoV) is gradually widely used in the transportation network, and subsequent problems are also increasing. Nowadays, most of the Internet of Vehicles systems use centralized trusted units for information storage, processing and transmission, which will lead to many security risks, such as message leakage, high cost and high latency of the central unit. Therefore, ensuring the communication security in the network is the key in the field of IoV. By introducing the concept of blockchain in the scene, the decentralized system based on the IoV becomes possible. Blockchain technology is considered as the key technology for efficiently and securely storing, processing and sharing data. To overcome the limitations of existing works, we propose a vehicle-based blockchain security consensus authentication algorithm. Compared with the existing technologies, our method is better in authentication processing delay, and key analysis time. CCS CONCEPTS • Security and privacy; • Systems security; • Distributed systems security; KEYWORDS Blockchain, internet of vehicles (IoV), security, authentication, key processing ACM Reference Format:
... Therefore, the security challenges associated with the IoT system cannot be resolved successfully by either the cloud or the isolated attack detection system [3]. On the other hand, a distributed security system allows for interoperability, flexibility, and scalability while securing and managing heterogeneous devices in a unified manner [4]. ...
With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.
... These techniques implement authentication without additional overhead. Some of the physical layer authentication methods proposed include channel-based authentication using channel state information [5][6][7][8], radio frequency (RF) fingerprint-based schemes [9][10][11], received signal strength indicator (RSSI) [12][13][14][15], multi-attribute multi-observation (MAMO) techniques [16], fingerprint/watermark embedding [17,18] and so on. All these authentication methods were threshold-based, in which the channel state information (CSI) is compared with a reference CSI. ...
Cyber-physical wireless systems have surfaced as an important data communication and networking research area. It is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking technologies. Due to their high reliability, sensitivity and connectivity, their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping, spoofing, botnets, man-in-the-middle attack, denial of service (DoS) and distributed denial of service (DDoS) and impersonation. Existing methods use physical layer authentication (PLA), the most promising solution to detect cyber-attacks. Still, the cyber-physical systems (CPS) have relatively large computational requirements and require more communication resources, thus making it impossible to achieve a low latency target. These methods perform well but only in stationary scenarios. We have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile scenarios. The features are fed to ensemble learning algorithms, such as AdaBoost, LogitBoost and Gentle Boost, to classify data. The authentication of the received signal is considered a binary classification problem. The transmitted data is labeled as legitimate information, and spoofing data is illegitimate information. Therefore, this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing attacks. It detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are mobile. The proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time. 4490 CMC, 2022, vol.73, no.3
... Sawtooth Lake [22] proposed a consensus algorithm based on PoET (time disappearance proof) of special hardware "proof". This method ensures security and randomness by providing trusted guaranteed waiting time by TEE [23]. Town crier [24] uses Intel SGX to ensure the security of external data used by smart contracts. ...
Blockchain has the characteristics of openness and
decentralization and faces many security threats in application
scenarios. Apply trusted computing technology to establish
trusted blockchain boundaries and build a systematic security
protection framework to meet the security requirements in
blockchain application scenarios. Therefore, this paper combines
trusted computing technology with blockchain security protection
requirements, proposes blockchain trusted boundary, focuses
on blockchain boundary trusted measurement technology, and
ensures the security and credibility of blockchain boundary from
systematization.
... A large number of trusted reports form blocks and are written into the audio chain. The blockchain audit platform analyzes the credibility reports reported by the blockchain nodes to determine the credibility, credibility and risk value of the blockchain nodes and then provides a reference for the formulation of credible policies [15]. In terms of reasonable report storage, the blockchain audit platform builds a separate audit chain to record credible node reports [16]. ...
As a new generation of information technology,
blockchain plays an increasingly prominent role in social operation,
bringing significant changes to the economic process, social
organization and governance. Blockchain application scenarios
are complex and diverse, with many computing nodes, scattered
locations and dynamic topology changes. Security threats
have become an essential factor restricting blockchain development,
and various security problems have become increasingly
prominent. The blockchain network lacks an effective security
management mechanism, resulting in the frequent flow of illegal
data on the chain and malicious attacks, which seriously affects
the operation order and healthy development of the blockchain
network. Based on trusted computing technology, this paper
carries out the research on the blockchain-oriented management
platform, constructs a distributed blockchain management center,
carries out system management, security management and audit
management of the blockchain, and provides a safe and reliable
guarantee for the stable operation of the blockchain network.
... 1. Communication security Communication security requires that physical as well as digital data must be secured or protected from any non-legitimate users, access, revelation, disturbance, alteration, inspection, recording, or demolition (Liu et al. 2020a;Waqas et al. 2018d). Communication security is different from other security in the sense that it keeps the data secure. ...
Security is one of the biggest challenges concerning networks and communications. The problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence (AI) has emerged as a promising solution and a volume of literature exists on the methodological studies of AI to resolve the security challenge. In this survey, we present a taxonomy of security threats and review distinct aspects and the potential of AI to resolve the challenge. To the best of our knowledge, this is the first comprehensive survey to review the AI solutions for all possible security types and threats. We also present the lessons learned from the existing AI techniques and contributions of up-to-date literature, future directions of AI in security, open issues that need to be investigated further through AI, and discuss how AI can be more effectively used to overcome the upcoming advanced security threats.
... Because of these features, side channel attacks are powerful noninvasive attacks that exploit the leakage of physical information when cryptographic algorithms run in a system. And side channel attacks are powerful attacks that leave no trace or destroy encryption devices because they exploit accessible data, clocks, and voltage interfaces on the target device [22,23]. Thus, side channel attacks have become a major threat to current cryptographic devices Fault injection attacks are one of the most effective sub-channel attacks, which use voltage glitches, clock glitches, and laser pulses to inject faults that interfere with the operational state of a cryptographic device or chip and generate controllable faults [24]. ...
As a large amount of data needs to be processed and speed needs to be improved, edge computing with ultra-low latency and ultra-connectivity is emerging as a new paradigm. These changes can lead to new cyber risks, and should therefore be considered for a security threat model. To this end, we constructed an edge system to study security in two directions, hardware and software. First, on the hardware side, we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array (FPGA) which is suitable for edge computing and identifying communication status to control the communication method according to priority. In addition, on the software side, data collected on the server performs end-to-end encryption via symmetric encryption keys. Also, we modeled autonomous defense systems on the server by using machine learning which targets to incoming and outgoing logs. Server log utilizes existing intrusion detection datasets that should be used in real-world environments. Server log was used to detect intrusion early by modeling an intrusion prevention system to identify behaviors that violate security policy, and to utilize the existing intrusion detection data set that should be used in a real environment. Through this, we designed an efficient autonomous defense system that can provide a stable system by detecting abnormal signals from the device and converting them to an effective method to control edge computing, and to detect and control abnormal intrusions on the server side.
... CSI can be used in many fields, such as passive perception and device-to-device communication [37,38]. Thanks to the emergence of new tools, it is easy to obtain CSI on commercial Wi-Fi network cards. ...
Material identification is a technology that can help to identify the type of target material. Existing approaches depend on expensive instruments, complicated pre-treatments and professional users. It is difficult to find a substantial yet effective material identification method to meet the daily use demands. In this paper, we introduce a Wi-Fi-signal based material identification approach by measuring the amplitude ratio and phase difference as the key features in the material classifier, which can significantly reduce the cost and guarantee a high level accuracy. In practical measurement of WiFi based material identification, these two features are commonly interrupted by the software/hardware noise of the channel state information (CSI). To eliminate the inherent noise of CSI, we design a denoising method based on the antenna array of the commercial off-the-shelf (COTS) Wi-Fi device. After that, the amplitude ratios and phase differences can be more stably utilized to classify the materials. We implement our system and evaluate its ability to identify materials in indoor environment. The result shows that our system can identify 10 commonly seen liquids with an average accuracy of 98.8%. It can also identify similar liquids with an overall accuracy higher than 95%, such as various concentrations of salt water.
... The decryptions are satisfied if the user's attributes meet the defined access structure by achieving fine-grained access control. However, the traditional attribute-based encryption (ABE) technology in cloud computing is challenging to apply in fog computing [6,7]. The reason is that the conventional ABE technology mainly adopts the single authorization center method, which has an efficient bottleneck and single point attack. ...
Fog computing is a revolutionary technology for the next generation to bridge the gap between cloud data centers and end-users. Fog computing is not a counterfeit for cloud computing but a persuasive counterpart. It also accredits by utilizing the network edge while still rendering the possibility to interact with the cloud. Nevertheless, the features of fog computing are encountering several security challenges. The security of end-users and/or fog servers brings a significant dilemma in implementing fog computing. Moreover, in conventional cloud computing, the attribute-based encryption (ABE) technology is not appropriate for end-users due to restricted computing resources, i.e., limited resources, high end-to-end delay, and transmission capability. Hence, the revocation and outsourcing mechanisms become inappropriate between end-users and cloud servers. In this regard, this paper recommends a multi-authority attribute-based encryption (MA-ABE) technique to support revocation and outsource the attributes to fog computation. We present an attribute revocation scheme based on cipher-text attribute-based encryption by introducing the attribute group keys. In this process, the secret keys are dynamically altered and realized the requirement of immediate attribute revocations. Hence, we provide the complete encryption and decryption process for end-users and fog servers based on multi-authority, attribute revocation, and outsourcing computation, while most of the existing scheme lack to incorporate all these parameters. Our scheme also outsources the complicated encryption and decryption tasks to the fog server that significantly improves the overall computation efficiency compared to the state-of-the-art.
... We use P s = 0 for R s as a benchmark. On the other hand, we keep P s between 0.1 to 0.4 for social reciprocity and between 0.6 to 1 for social trust, respectively [62]. In our experiments, we consider the secret key generation rate, R s , and security sum rate, respectively. ...
Fog computing is an emerging technology that aims at reducing the load on cloud data centers by migrating some computation and storage towards end-users. It leverages the intermediate servers for local processing and storage while making it possible to offload part of the computation and storage to the cloud. Inspired by the benefits of fog computing, we present a novel paradigm that considers the context of social phenomena. Online and offline human interactions and the mobile social network's relentless growth allowed real-world data and created users' traces. We categorize social phenomena into two main groups to integrate with fog computing from social interactions' continuous development. In this regard, the first contribution addresses the social relationship between the end-users and fog nodes based on personal benefits. The social relationship considers trust, reciprocity, incentives, and selfishness mechanisms. The second contribution describes the group-based social behavior, i.e., centrality, community, and co-location in fog computing networks (FCNs). We also discuss the impact of social phenomena on fog computing networks in network performance, resource allocations, security, and privacy. We present open challenges and highlight future directions on social perception to encourage follow-up work.
... This interaction becomes complex in cases when users do not know the query requirements. For example, if users want to travel by themselves, there may be unclear search needs, leading to users not knowing what information [7] to search for better. Such interaction could involve attention requirements same as the simple or complex texting, also bi-directional interactions. ...
Distracted driving due to smartphone use is one of the key reasons for road accidents. However, the 6G super-heterogeneous network systems and highly differentiated application scenarios require highly elastic and endogenous information services involving the use of smart apps, and related information retrieval by drivers in modern Vehicle-to-People (V2P) Networks. The tension raised due to the conflicting attention requirements of driving and information retrieval can be resolved by designing information retrieval solutions that demand minimal user interaction. In this paper, we construct a Personalized Search Query Generator (PSQG) to reduce driver-mobile interaction during information retrieval in the 6G era. This system has a query generator and a query recommendation component that update two sets of relationships dynamically: one is the query and the title, another is search and recommendation. The proposed system learns a user's intent based on historical query records and recommends personalized queries, thus reducing the driver-mobile interaction time. We deploy the system into a real search engine and conduct several online experiments. These experiments are conducted using a custom constructed dataset comprising ten million samples. We use the BLEU-score metric and perform A/B testing. The results demonstrate that our system can assist users in making precise queries efficiently. The proposed system can improve drivers' safety if used in smartphones and other information retrieval systems in vehicles.
... It offers the opportunity to imitate or require the characteristics of channels [14]. For example, the channel randomness of authentic users is unknown to unauthorized users [15]. In addition, PHY-SKG may not require any computational complexity due to channel randomness. ...
Secret key generation (SKG) is an emerging technology to secure wireless communication from attackers. Therefore, the SKG at the physical layer is an alternate solution over traditional cryptographic methods due to wireless channels' uncertainty. However, the physical layer secret key generation (PHY-SKG) depends on two fundamental parameters, i.e., coherence time and power allocation. The coherence time for PHY-SKG is not applicable to secure wireless channels. This is because coherence time is for a certain period of time. Thus, legitimate users generate the secret keys (SKs) with a shorter key length in size. Hence, an attacker can quickly get information about the SKs. Consequently, the attacker can easily get valuable information from authentic users. Therefore, we considered the scheme of power allocation to enhance the secret key generation rate (SKGR) between legitimate users. Hence, we propose an alternative method, i.e., a power allocation, to improve the SKGR. Our results show 72% higher SKGR in bits/sec by increasing power transmission. In addition, the power transmission is based on two important parameters, i.e., epsilon and power loss factor, as given in power transmission equations. We found out that a higher value of epsilon impacts power transmission and subsequently impacts the SKGR. The SKGR is approximately 40.7% greater at 250 from 50 mW at epsilon = 1. The value of SKGR is reduced to 18.5% at 250 mW when epsilonis 0.5. Furthermore, the transmission power is also measured against the different power loss factor values, i.e., 3.5, 3, and 2.5, respectively, at epsilon = 0.5. Hence, it is concluded that the value of epsilon This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2180 CMC, 2021, vol.68, no.2 and power loss factor impacts power transmission and, consequently, impacts the SKGR.
... In addition, PLS takes advantage of channel randomness and reciprocity, and is the basic concept for the secret key generation (SKG) method [2]. In contrast, S a common approach [6] for SKG is to observe the time period, i.e., the coherence time of the channel. Within the coherence time, the system is considered to be static, and the rate at which the secret keys are generated is low [3], [4]. ...
In device-to-device (D2D) communications, the channel gain between a transmitter and a receiver is difficult to predict due to channel variations. Hence, an attacker can easily perform an impersonation attack between two authentic D2D users. As a countermeasure, we propose a reinforcement learning-based technique that guarantees identification of the impersonator based on channel gains. To show the merit of our technique, we report its performance in terms of false alarm rate, miss-detection rate, and average error rate. The secret key generation rate is also determined under the impersonation attack based on physical layer security.
Physical layer key generation is a lightweight technique to generate secret keys from wireless channels for resource-constrained Internet of things (IoT) applications. The security of the key generation relies on spatial decorrelation, which assumes that eavesdroppers observe uncorrelated channel measurements when they are located over a half-wavelength away from legitimate users. Unfortunately, no experimental validation exists for communications environments with both large-scale and small-scale fading effects. Furthermore, while the current key generation work mainly focuses on short-range communications techniques such as WiFi and ZigBee, the exploration with long-range communications, e.g., LoRa, is somewhat limited. This paper presents a long-range key generation testbed and reveals a new attack scenario that perceives and utilizes large-scale fading effects in key generation channels, by using multiple eavesdroppers circularly around a legitimate user. We formalized such an attack and validated it through extensive experiments conducted in indoor and outdoor environments. It is corroborated that the attack reduces secret key capacity when large-scale fading is predominant. We further investigated potential defenses by proposing a conditional entropy and high-pass filter-based countermeasure to estimate and eliminate large-scale fading components. The experimental results demonstrated that the countermeasure significantly improved the key generation’s security when both large-scale and small-scale fading existed. The keys generated by legitimate users have a desirable low key disagreement rate (KDR) and are validated by the NIST randomness tests. In contrast, eavesdroppers’ average KDR is increased from 0.25 to 0.49.
Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) offers a promising technique to fulfil the high data demand and connectivity of the Internet-of-Things (IoT) and 5G communications because it owns valuable and unknown spectrum resources. Using massive antennas with recently introduced drone-enabled aerial computing platforms, named unmanned aerial vehicles (UAVs), can cast high energy consumption if fully-digital precoding is employed at the UAVs. Using hybrid precoding at a UAV can reduce hardware complexity and energy consumption but is challenging with a need for joint optimization of three precoding matrices at the UAV (sixth-order polynomial objective function). In this paper, we propose to decompose the original UAV hybrid precoding challenge into three subproblems and develop a coordinated descent optimization (CDO) algorithm to solve the three problems recursively. In addition, the convergence and complexity of this new technique are analyzed. Numerical studies indicate the improved effectiveness of the proposed solution over existing solutions.
With the development of the Internet of Things technology and the advent of the 5G era, cloud computing is difficult to meet the requirements of low latency, high reliability, and data security for various application services. The fog computing model newly proposed by researchers in recent years can increase the task processing and data analysis capabilities of network edge devices, so it can reduce the computing load of cloud computing devices and improve the efficiency of data operations. Although fog computing can largely solve existing cloud computing problems, secure access and privacy protection are still a very important and urgent problem to be solved. Aiming at the problem of selecting a relay node to generate a security key under the fog computing model under the fog computing model, this paper proposes a secure relay node selection method based on game theory. In this paper, a fog computing model based on social relationships is constructed. Under this model, a secure relay node selection method based on game theory is designed to realize the selection of relay nodes when a communication link generates a security key. Finally, this paper analyzes the selection efficiency from the two dimensions of total equipment and dynamic changes of terminal equipment. Simulation results show that the method proposed in this paper can quickly select secure relay nodes in the social connection-based fog computing model.
Device‐to‐device (D2D) communication has emerged as a promising technology for the next‐generation mobile communication networks and wireless systems (5G). As an underlay network of conventional cellular networks, e.g. LTE and 5G network, D2D communications have shown great potential in improving communication capability, erasing communication delay, reducing power dissipation, and fostering multifarious new applications and services. In spite of the significant benefits, new application scenarios and system architecture expose D2D services into specific security and privacy threats and issues. These issues hinder the success of various D2D services. In this article, we explore a security architecture for D2D communications under 5G framework. Under this architecture, we investigate potential security and privacy threats and specify security and privacy requirements for designing a security and privacy, preserving D2D system. The state‐of‐the‐art solutions on security and privacy in D2D communications are reviewed comprehensively and intensively and evaluated under the security architecture. The analysis results show the features and drawbacks of existing works when coping with these security and privacy threats and requirements. Finally, we point out open research issues from the existing works and inspire future research efforts.
Key generation from the randomness of wireless channels is a promising alternative to public key cryptography for the establishment of cryptographic keys between any two users. This paper reviews the current techniques for wireless key generation. The principles, performance metrics and key generation procedure are comprehensively surveyed. Methods for optimizing the performance of key generation are also discussed. Key generation applications in various environments are then introduced along with the challenges of applying the approach in each scenario. The paper concludes with some suggestions for future studies.
In this article we propose to facilitate local peer-to-peer communication by a Device-to-Device (D2D) radio that operates as an underlay network to an IMT-Advanced cellular network. It is expected that local services may utilize mobile peer-to-peer communication instead of central server based communication for rich multimedia services. The main challenge of the underlay radio in a multi-cell environment is to limit the interference to the cellular network while achieving a reasonable link budget for the D2D radio. We propose a novel power control mechanism for D2D connections that share cellular uplink resources. The mechanism limits the maximum D2D transmit power utilizing cellular power control information of the devices in D2D communication. Thereby it enables underlaying D2D communication even in interference-limited networks with full load and without degrading the performance of the cellular network. Secondly, we study a single cell scenario consisting of a device communicating with the base station and two devices that communicate with each other. The results demonstrate that the D2D radio, sharing the same resources as the cellular network, can provide higher capacity (sum rate) compared to pure cellular communication where all the data is transmitted through the base station.
Device-to-device (D2D) communication is seen as a major technology to overcome the imminent wireless capacity crunch and to enable new application services. In this paper, a novel social-aware approach for optimizing D2D communication by exploiting two layers, namely the social network layer and the physical wireless network layer, is proposed. In particular, the physical layer D2D network is captured via the users' encounter histories. Subsequently, an approach, based on the so-called Indian Buffet Process, is proposed to model the distribution of contents in the users' online social networks. Given the social relations collected by the base station, a new algorithm for optimizing the traffic offloading process in D2D communications is developed. In addition, the Chernoff bound and approximated cumulative distribution function (cdf) of the offloaded traffic are derived and the validity of the bound and cdf is proven. Simulation results based on real traces demonstrate the effectiveness of our model and show that the proposed approach can offload the network's traffic successfully.
In this paper, we propose SoCast - a cooperative video multicast framework to stimulate effective cooperation among mobile users (clients), by leveraging two types of important social ties, i.e., social trust and social reciprocity. By using SoCast, clients can form groups to restore incomplete video frames by obtaining missing packets from other clients, according to the unique video encoding structure. In return, the user perception video quality of mobile video multicast can be improved. Specifically, we first cast the problem of social ties based group formation among clients as a coalitional game, and then devise a distributed algorithm to obtain the core solution (group formation) for the formulated coalitional game. Further, a resource allocation mechanism is proposed for the base station to handle radio resource requests from client groups. Extensive numerical studies with real video traces corroborate the significant performance gain by using the SoCast.
Dynamic spectrum sharing is a promising technology for improving the spectrum
utilization. In this paper, we study how secondary users can share the spectrum
in a distributed fashion based on social imitations. The imitation-based
mechanism leverages the social intelligence of the secondary user crowd and
only requires a low computational power for each individual user. We introduce
the information sharing graph to model the social information sharing
relationship among the secondary users. We propose an imitative spectrum access
mechanism on a general information sharing graph such that each secondary user
first estimates its expected throughput based on local observations, and then
imitates the channel selection of another neighboring user who achieves a
higher throughput. We show that the imitative spectrum access mechanism
converges to an imitation equilibrium, where no beneficial imitation can be
further carried out on the time average. Numerical results show that the
imitative spectrum access mechanism can achieve efficient spectrum utilization
and meanwhile provide good fairness across secondary users.
In this tutorial, we provided a comprehensive overview of coalitional game theory, and its usage in wireless and communication networks. For this purpose, we introduced a novel classification of coalitional games by grouping the sparse literature into three distinct classes of games: canonical coalitional games, coalition formation games, and coalitional graph games. For each class, we explained in details the fundamental properties, discussed the main solution concepts, and provided an in-depth analysis of the methodologies and approaches for using these games in both game theory and communication applications. The presented applications have been carefully selected from a broad range of areas spanning a diverse number of research problems. The tutorial also sheds light on future opportunities for using the strong analytical tool of coalitional games in a number of applications. In a nutshell, this article fills a void in existing communications literature, by providing a novel tutorial on applying coalitional game theory in communication networks through comprehensive theory and technical details as well as through practical examples drawn from both game theory and communication application.
Human groups maintain a high level of sociality despite a low level of relatedness among group members. This paper reviews the evidence for an empirically identifiable form of prosocial behavior in humans, which we call "strong reciprocity", that may in part explain human sociality. A strong reciprocator is predisposed to cooperate with others and punish non-cooperators, even when this behavior cannot be justified in terms of extended kinship or reciprocal altruism. We present a simple model, stylized but plausible, of the evolutionary emergence of strong reciprocity.
As the first part of a study of problems involving common
randomness at distance locations, information-theoretic models of secret
sharing (generating a common random key at two terminals, without
letting an eavesdropper obtain information about this key) are
considered. The concept of key-capacity is defined. Single-letter
formulas of key-capacity are obtained for several models, and bounds to
key-capacity are derived for other models
With the popularity of proximity-based services, device-to-device (D2D) communication underlaying cellular networks is a promising technology to cope with the growing demands by improving network resource utilization. However, wireless communication’s broadcast nature is vulnerable to eavesdropping, thus, ensuring secrecy communication for both cellular user equipments (CUEs) and D2D pairs in an underlay network is a challenging issue. We investigate the problem of physical-layer secure transmission jointly with resource allocation in D2D communications. Different from existing works, we framed overlapping (partial) coalitional game where each D2D pair can access multiple CUEs’ spectral resources. Moreover, multiple D2D pairs can share single CUE subchannel in multiple eavesdroppers scenario to ensure information security for both CUEs and D2D pairs, and to maximize system sum-rate in socially-aware D2D network. We incorporate mutual interference and propose different transmission modes for secrecy ensured resource allocation based overlapping coalition formation scheme with transferable utility to obtain a final stable partition. We further prove the proposed algorithm stability, convergence and computational complexity. Both analytical and numerical results demonstrate the effectiveness of our proposed scheme, which ensures system-wide security and at the same time improves the performance by maximizing the system sum-rate. IEEE
Physical layer security (PLS) is a promising technology
in device-to-device (D2D) communications by exploiting
reciprocity and randomness of wireless channels, which attracts
considerable research attention in the D2D communications
community. In this paper, we investigated PLS for secure key
generation rate (SKGR) in D2D communications based on cooperative
trusted and non-trusted relays. By leveraging social ties,
we exploit three social phenomena for secure communications,
i.e., trusted scenario (social trust), non-trusted scenario (social
reciprocity) and partially trusted scenario (mixed social trust
and social reciprocity). The coalition game theory is further
utilized to select the optimal relay pairs for improving SKGR.
On the basis of social ties, we develop an algorithm for SKGR
that protects the keys secret from both eavesdropper and nontrusted
selected relays. We incorporate secure relays selection
and system wide security for D2D communications. The stability
and convergence of the proposed algorithm are also proved
in our work. Both numerically and analytically results verify
effectiveness and consistency of our proposed scheme, which
ensures better SKGR performance in D2D communications.
With the explosion growth of mobile data demands for proximal services, device-to-device (D2D) communication is proposed as a vital technology for the next generation cellular network. With the extensive increase in personal mobile devices, content transmission of proximal devices underlaying cellular networks is gaining considerable attention. However, due to the mobility constraint of mobile devices, content transmission under- laying cellular networks greatly affects the overall transmission capacity of these proximal devices. In this paper, we investi- gate the problem of mobility assisted content transmission and resource allocation by exploiting the contact patterns regulated by these proximal devices' mobility. We formulate the content transmission and resource allocation with the help of the statistic property of contact rates, and then utilize convex optimization to determine the successful content transmission and resource allocation scheme. We present the optimal resource allocated content transmission (RACT) algorithm based on the pseudo- polynomial time algorithm using dynamic programming to solve the optimization problem. Real data traces are utilized in our proposed algorithm to find out the natural strategies of mobile homophily. Extensive simulations under the realistic human mobility factors are evaluated to demonstrate the efficiency of our proposed scheme.
Device-to-device communications are promising
technology to enhance 5G cellular network. However, mobility
greatly affects the transmission capacity of proximal devices.
In this paper, we investigate the problem of mobility-assisted
content transmission and resource allocation by leveraging the
contact patterns determined by proximal users. We formulate
the problem with the help of statistical properties of contact
rate, and utilize convex optimization to solve the problem of
content transmission and resource allocation for mobile users.We
propose the optimal Resource Allocated Content Transmission
(RACT) algorithm based on pseudo-polynomial time algorithm
using dynamic programming. Extensive simulations are evaluated
under realistic mobility factors, which indicates the efficiency of
our proposed RACT algorithm.
Abstract:
Device-to-Device (D2D) communication presents a new paradigm in mobile networking to facilitate data exchange between physically proximate devices. The development of D2D is driven by mobile operators to harvest short range communications for improving network performance and supporting proximity-based services. In this article, we investigate two fundamental and interrelated aspects of D2D communication, security and privacy, which are essential for the adoption and deployment of D2D. We present an extensive review of the stateof- the-art solutions for enhancing security and privacy in D2D communication. By summarizing the challenges, requirements, and features of different proposals, we identify lessons to be learned from existing studies and derive a set of “best practices”. The primary goal of our work is to equip researchers and developers with a better understanding of the underlying problems and the potential solutions for D2D security and privacy. To inspire follow-up research, we identify open problems and highlight future directions with regard to system and communication design. To the best of our knowledge, this is the first comprehensive review to address the fundamental security and privacy issues in D2D communication.
In this paper, we propose a physical-layer secret key generation scheme for multi-antenna legitimate nodes with the help from multiple untrusted relays with single antenna. The relays' actions conform to the rules but they passively eavesdrop the information. Different from most previous key generation schemes, where a key is generated based on a channel coefficient, in the proposed scheme, we use the linear combination of channel coefficients to generate a key. Simulation results show that the rate leaked to the untrusted relays is low and the secret key rate is therefore high. We also point out that the relay communication can achieve higher secret key rate than the direct communication in several distance ranges.
Long-term evolution-advanced (LTE-A) networks exploit low-power relay nodes, picocells and femtocells to boost throughput, enhance coverage, decrease latency, and reduce cost. End users in a relay-based LTE-A network can recruit relay nodes to cooperate as virtual antenna arrays, thereby reaping the benefits offered by multiple input single output (MIMO) techniques. Although the relay-based cooperative MIMO (coop MIMO) implementation in LTE-A networks improves performance, security issues are often overlooked. This paper introduces a physical layer security scheme for point-to-point networks, and extends this scheme to MIMO networks. Two practical relay-based coop MIMO architectures and corresponding secret key generation (SKG) schemes are presented. For both the MIMO and coop MIMO networks, the impact of proposed power allocation on SKG rate (SKGR) is quantified via the theoretical and numerical analysis. Results indicate that the proposed power allocation scheme can offer 15%–30% increase in SKGR relative to MIMO/coop MIMO networks with equal power allocation at low-power region, thereby improving network security.
To satisfy the ever increasing wireless service demand, it is effective to form a converged network by utilizing interworking mechanisms, such that the resources of heterogeneous wireless networks can be allocated in a coordinated and efficient manner. Despite the potential advantages of a converged network, its performance needs further improvement, especially at cell edges and rural areas where only one network is available. In this article, we investigate how to leverage device-to-device, D2D, communication to further improve the performance of a converged network which consists of an LTE-A cellular network and IEEE 802.11n WLANs. Three main technical challenges that complicate resource allocation are identified: allocation of resources capturing diverse radio access technologies of the networks, selection of users' communication modes for multiple networks to maximize hop and reuse gains, and interference management. To address these challenges, we propose a resource allocation scheme that performs mode selection, allocation of WLAN resources, and allocation of LTE-A network resources in three different timescales. The resource allocation scheme is semi-distributedly implemented in the underlying converged D2D communication network, and the achievable performance improvements are demonstrated via simulation results.
This paper studies the cooperative transmission for securing a decode-and-forward (DF) two-hop network where multiple cooperative nodes coexist with a potential eavesdropper. Under the more practical assumption that only the channel distribution information (CDI) of the eavesdropper is known, we propose an opportunistic relaying with artificial jamming secrecy scheme, where a “best” cooperative node is chosen among a collection of N possible candidates to forward the confidential signal and the others send jamming signals to confuse the eavesdroppers. We first investigate the ergodic secrecy rate (ESR) maximization problem by optimizing the power allocation between the confidential signal and jamming signals. In particular, we exploit the limiting distribution technique of extreme order statistics to build an asymptotic closed-form expression of the achievable ESR and the power allocation is optimized to maximize the ESR lower bound. Although the optimization problems are non-convex, we propose a sequential parametric convex approximation (SPCA) algorithm to locate the Karush-Kuhn-Tucker (KKT) solutions. Furthermore, taking the time variance of the legitimate links' CSIs into consideration, we address the impacts of the outdated CSIs to the proposed secrecy scheme, and derive an asymptotic ESR. Finally, we generalize the analysis to the scenario with multiple eavesdroppers, and give the asymptotic analytical results of the achievable ESR. Simulation results confirm our analytical results.
With the fast development of mobile terminals and wireless communication networks, mobile social networks (MSNs) play an important role in everyday lives to access social activities. However, most research on MSNs typically focuses on the relations of the users' physical location, but not make sufficient use of social ties. Consequently, in this paper, we consider a scenario of MSNs with online social networks and offline Device-to-Device (D2D) communication underlaying cellular networks, and study the problem of data dissemination to the mobile users under the constraint of limited spectrum resources. We first present a novel approach to formulate the social relationships for the offline mobiles by comparing the similarity of mobile users' social activities with the Bayesian model. And then we realize efficient data propagation using coalitional graph game. Finally, we provide simulation results to verify effectiveness of our studies.
This paper studies secret key establishment between two adjacent mobile nodes, which is crucial for securing emerging device-to-device (D2D) communication. As a promising method, cooperative key generation allows two mobile nodes to select some common neighbors as relays and directly extract a secret key from the wireless channels among them. A challenging issue that has been overlooked is that mobile nodes are often self-interested and reluctant to act as relays without adequate reward in return. We propose SYNERGY, a game-theoretical approach for stimulating cooperative key generation. The underlying idea of SYNERGY is to partition a group of mobile nodes into disjoint coalitions such that the nodes in each coalition fully collaborate on cooperative key generation. We formulate the group partitioning as a coalitional game and design centralized and also distributed protocols for obtaining the core solution to the game. The performance of SYNERGY is evaluated by extensive simulations.
With emerging demands for local area services, device-to-device communication is conceived as a vital component for the next-generation cellular networks to improve spectral reuse, bring hop gains, and enhance system capacity. Ripening these benefits depends on efficiently solving several main technical problems, including mode selection, resource allocation, and interference management. Aiming to establish a new paradigm for solving these challenging problems in D2D communication, in this article we propose a social-aware enhanced D2D communication architecture that exploits social networking characteristics for system design. By developing a profound understanding of the interplay between social networks' properties and mobile communication problems, we qualitatively analyze how D2D communications can benefit from social features, and quantitatively assess the achievable gains in a social-aware D2D communication system.
Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of the interplay between social structure and mobile communications, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device communications. Specifically, as hand-held devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game theoretic framework to devise social-tie based cooperation strategies for device-to-device communications. We also develop a network assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, and truthful. We evaluate the performance of the mechanism by using real social data traces. Numerical results show that the proposed mechanism can achieve up-to 122% performance gain over the case without D2D cooperation.
Social networks overlaid on technological networks account for a significant fraction of Internet use. Through graph theoretic and functionality models, this paper examines social network analysis and potential implications for the design of technological networks, and vice versa. Such interplay between social networks and technological networks suggests new directions for future research in networking.
Most of the existing work on key generation from wireless fading channels requires a direct wireless link between legitimate users so that they can obtain correlated observations from the common wireless link. This paper studies the key generation problem in the two-way relay channel, in which there is no direct channel between the key generating terminals. We propose an effective key generation scheme that achieves a substantially larger key rate than that of a direct channel mimic approach. Unlike existing schemes, there is no need for the key generating terminals to obtain correlated observations in our scheme. We also investigate the effects of an active attacker on the proposed key generation protocol. We characterize the optimal attacker's strategy that minimizes the key rate of the proposed scheme. Furthermore, we establish the maximal attacker's power under which our scheme can still achieve a nonzero key rate.
In this paper, we propose a hybrid cooperative beamforming and jamming scheme to enhance the physical-layer security of a single-antenna-equipped two-way relay network in the presence of an eavesdropper. The basic idea is that in both cooperative transmission phases, some intermediate nodes help to relay signals to the legitimate destination adopting distributed beamforming, while the remaining nodes jam the eavesdropper, simultaneously, which takes the data transmissions in both phases under protection. Two different schemes are proposed, with and without the instantaneous channel state information of the eavesdropper, respectively, and both are subjected to the more practical individual power constraint of each cooperative node. Under the general channel model, it is shown that both problems can be transformed into a semi-definite programming (SDP) problem with an additional rank-1 constraint. A current state of the art technique for handling such a problem is the semi-definite relaxation (SDR) and randomization techniques. In this paper, however, we propose a penalty function method incorporating the rank-1 constraint into the objective function. Although the so-obtained problem is not convex, we develop an efficient iterative algorithm to solve it. Each iteration is a convex SDP problem, thus it can be efficiently solved using the interior point method. When the channels are reciprocal such as in TDD mode, we show that the problems become second-order convex cone programming ones. Numerical evaluation results are provided and analyzed to show the properties and efficiency of the proposed hybrid security scheme, and also demonstrate that our optimization algorithms outperform the SDR technique.
Due to the broadcast nature of wireless channels, wireless communication is vulnerable to eavesdropping, message modification, and node impersonation. Securing the wireless communication requires the shared secret keys between the communicating entities. Traditional security schemes rely on public key infrastructures and cryptographic algorithms to manage secret keys. Recently, many physical-layer-based methods have been proposed as alternative solutions for key generation in wireless networks. These methods exploit the inherent randomness of the wireless fading channel to generate secret keys while providing information-theoretical security without intensive cryptographic computations. This article provides an overview of the existing PHY-based key generation schemes exploiting the randomness of the wireless channels. Specifically, we first introduce the fundamental and general framework of the PHY-based key generation schemes and then categorize them into two classes: received-signal-strength-based and channel- phase-based protocols. Finally, we present a performance comparison of them in terms of key disagreement probability, key generation rate, key bit randomness, scalability, and implementation issues.
The impact of relay nodes on the secret key gener-ation via the physical layer resources is investigated. A novel relay-assisted strategy is proposed to improve the generated secret key rate. The main idea is to exploit the random channels associated with relay nodes in the network as additional random sources for the key generation. This approach is particularly useful when the channels between legitimate nodes change slowly. Four increasingly sophisticated yet more practical scenarios are studied, for which relay-assisted key generation protocols are proposed and are shown to be optimal or order-optimal in terms of the key rate. It is also shown that the multiplexing gain in the key rate scales linearly with the number of relays, which demonstrates that relay-assisted schemes substantially increase the key rate. This is in sharp contrast to scenarios with relays helping information transmission, in which the multiplexing gain does not scale with the number of relays. Furthermore, a cooperative scheme is also proposed in which relays help key generation but the generated keys are kept secure from these relays.
Device-to-Device communication underlaying a cellular network enables local services with limited interference to the cellular network. In this paper we study the optimal selection of possible resource sharing modes with the cellular network in a single cell. Based on the learning from the single cell studies we propose a mode selection procedure for a multi-cell environment. Our evaluation results of the proposed procedure show that it enables a much more reliable device-to-device communication with limited interference to the cellular network compared to simpler mode selection procedures. A well performing and practical mode selection is critical to enable the adoption of underlay device-to-device communication in cellular networks.
We describe some new exactly solvable models of the structure of social networks, based on random graphs with arbitrary degree distributions. We give models both for simple unipartite networks, such as acquaintance networks, and bipartite networks, such as affiliation networks. We compare the predictions of our models to data for a number of real-world social networks and find that in some cases, the models are in remarkable agreement with the data, whereas in others the agreement is poorer, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph.