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Internet of vehicles security situation awareness based on intrusion detection protection systems
Abstract
With the rise of technologies such as mobile Internet, 5G networks and artificial intelligence, the development of Internet of Vehicle Information Security (ICVS) has become the mainstream and direction for the future development of the automotive industry. ICVS, people, roads, clouds, and APP constitute a complex network of vehicles. As part of the Internet, vehicle networking will inevitably face various complex information security threats and risks. This paper aims to design a kind of security situation awareness of Internet of vehicles based on intrusion detection protection systems (IDPS). By collecting the security data of car, app and private cloud for big data analysis, the whole smart car security situation awareness system is constructed. The system can be used to analyze potential threats, send out warnings, and carry out emergency responses.
... For example, "Stuxnet virus" attacking Bushehr nuclear power plant in Iran, "Aurora attack" against Google mail server, "BlackEnergy" attack against Ukrainian power grid, etc. Although the information security personnel of the enterprise have deployed a large number of security devices in the network, some attacks will still bypass all protective measures and go straight to the enterprise, resulting in the leakage, damage or tampering of important data assets [1]. Therefore, it is necessary to find the threats hidden in the network in time through technical means, quickly find the malicious behaviors in the threats as soon as possible, accurately locate the target and the source of the attack, and judge and trace the intrusion path and attacker background, so as to solve the security threats in the enterprise network from the source and reduce the losses caused by the security threats to the enterprise as much as possible [2]. ...
... In addition to the above analysis, it is also necessary to consider the node protection degree en and the alarm return sn. The security index of the independent node can be obtained by (1). ...
... Data such as GPS location, speed, and road conditions can contribute to better traffic management, route planning, and accident prevention. However, this data is also sensitive [5]. BCFL enables aggregation of data from multiple vehicles to train models without sharing the raw data [11,15,16,50,87,94]. ...
While centralized servers pose a risk of being a single point of failure, decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Merging distributed computing with cryptographic techniques, decentralized technologies introduce a novel computing paradigm. Blockchain ensures secure, transparent, and tamper-proof data management by validating and recording transactions via consensus across network nodes. Federated Learning (FL), as a distributed machine learning framework, enables participants to collaboratively train models while safeguarding data privacy by avoiding direct raw data exchange. Despite the growing interest in decentralized methods, their application in FL remains underexplored. This paper presents a thorough investigation into blockchain-based FL (BCFL), spotlighting the synergy between blockchain’s security features and FL’s privacy-preserving model training capabilities. First, we present the taxonomy of BCFL from three aspects, including decentralized, separate networks, and reputation-based architectures. Then, we summarize the general architecture of BCFL systems, providing a comprehensive perspective on FL architectures informed by blockchain. Afterward, we analyze the application of BCFL in healthcare, IoT, and other privacy-sensitive areas. Finally, we identify future research directions of BCFL.
... Yajun Guo yj.guo@ccnu.edu.cn Yimin Guo yiminguo@zuel.edu.cn 1 data trust, security, and sustainability [11]. Although multiple network infrastructures can be used to store data, the data is scattered and is vulnerable to security threats such as data tampering and information theft. ...
Blockchain technology can provide excellent support for identity authentication and access control mechanisms. In particular, blockchain technology can ensure that large amounts of confidential data generated by the Internet of Vehicles devices are stored and transmitted in a safe and reliable environment, which is the key to making system services optimal. In addition, mobile edge computing is the best solution for IoV applications to deal with low latency and limited computing and storage capacity of vehicle-mounted devices. Mobile edge computing can help IoV systems achieve a variety of functions and features, the most important of which is the ability to process terminal data in real-time. Even though the amount of data generated by IoV devices is growing rapidly, the system is still characterized by low latency and high efficiency. Because the communication between IoV devices is carried out in an untrusted environment, it is particularly important to design a secure and effective identity authentication scheme. Therefore, this paper proposes an efficient, safe, and time-sensitive authentication mechanism for devices on the Internet of Vehicles, which applies to a large number of scenarios. The mechanism is based on the blockchain concept and mobile edge computing technology. Security analysis shows that the proposed scheme meets the security requirements of the Internet of Vehicles and is resistant to many known attacks. By comparing with existing advanced IoT authentication schemes, the performance evaluation of the mechanism shows that the scheme enhances security features while reducing computation and communication overhead.
Network situational awareness has become a new hotspot in the research of network security. Based on the analysis of existing network situational awareness models, this paper establishes a network situational awareness model based on the SimHash algorithm in a big data environment, which provides reference value for the next step of the network situational awareness system.
This article aims to provide a comprehensive overview on PHY layer security assisted ICV networks. Beginning with a discussion from a general perspective of the ICV network architecture, this work summarizes the major security threats faced by ICV networks. To achieve confidential data transmission with a low latency and a high data rate, several physical layer security schemes are surveyed in this article, which include RRM, cooperative jamming, multi-antenna technologies, and PHY-layer key generation. In addition, the performances of the aforementioned schemes are compared in terms of different aspects, followed by a discussion on some major challenges that need to be tackled in the implementation of ICV networks.
In recent years, the problem of data leakage in Internet of Things applications has become a major social issue, causing strong concern in all aspects. Especially for today’s popular car networking technology, if the driving data and other information is stolen, it will not only expose personal privacy and personal information, but also can even harm life safety. At the same time, some manufacturers tamper with the collected vehicle data, in order to forge false vehicle performance and deceive consumers. In the light of the data security risks faced by current Internet of Vehicles applications, based on the TrustZone architecture, this paper builds a trusted execution environment, uses timestamp authentication technology, and introduces Rabin, Huffman coding and random components, respectively, from the perspective of improving encryption speed and reducing the size of ciphertext files, to optimize the traditional asymmetric RSA algorithm, thus to construct a secure data acquisition method of Internet of Vehicles based on TrustZone and optimized RSA, which realizes the information security of the data collection of the vehicle network data. The experimental environment was built based on raspberry PI 3B experimental board, and the test and comparative experiment were conducted. The experimental results show that the method can encrypt the vehicle driving data efficiently and safely, prevent the attacker from stealing and tampering with the data, and ensure the data security of the collecting terminal. The optimized RSA algorithm improves the encryption speed while ensuring security, and the ciphertext file is smaller, which is more suitable for the embedded environment with large data volume and limited hardware computing capacity.
Internet of vehicles is a specific application of Internet of things technology in the field of intelligent transportation. The rapid development of 5G communication technology promotes the development of Internet of vehicles. Car for cellular network communication node random distribution and complex multi-source interference and mobile terminal security calculation ability is limited, this article in view of the actual scene, was proposed based on random geometry contains eavesdropper (Eve) honeycomb - V2V heterogeneous physical layer security system model, the introduction of automatic (PB) as artificial floating vehicle noise, the analysis of cellular network users in the system (CU), V2V users (VU) and interference of the eavesdropper, each user letter simulation with dry to noise ratio (SINR) of the cumulative distribution function, and by using the random geometry tools related safety expression deduction, Then, data mining was carried out on the distance between PB and VU receiver, PB transmitting power and other related variables through genetic algorithm, and the value process was visualized to extract valuable information, providing a mathematical analysis framework and theoretical guidance for the future design, deployment and operation of cellular vehicle network. The results show that the proposed system model can significantly improve the security of vehicle-network communication.
Internet of Vehicles (IoV) is treated as an extension of Vehicle-to-Vehicle (V2V) communication network. IoV helps in enhancing driving aids with the help of vehicle Artificial Intelligence (AI) awareness of other vehicles and their actions. IoV is connected in an adhoc networking environment which utilizes each vehicle in the network as a node, called Vehicular Ad Hoc Network (VANET), where the vehicles may be also connected to the public Internet. It is specifically important for the autonomous vehicles because they can instantaneously communicate with other vehicles surrounding them. In addition, safely avoiding accident prone zones is crucial in order to continue secure and smart transportation. Since the communication among various entities involved in the IoV environment is via open channel, it gives an opportunity to a passive/active adversary to intercept, modify, delete or even insert fake information during communication. It is then a serious concern for the vehicles users to determine whether the received information is genuine. In this survey paper, various security aspects, threats and attacks, network and threat models related to the IoV environment are discussed. Next, a taxonomy of security protocols is given that is essential to provide IoV data security. In particular, focus on various authentication protocols is given that is needed for mutual authentication among the involved entities in the IoV environment for secure communication. A detailed comparative analysis among various state-of-art authentication protocols proposed in the related IoV environment is provided to show their effectiveness as well as security and functionality features. Moreover, some testbeds are described that were designed and implemented for the IoV environment. In addition, some future challenges for IoV security protocols are also highlighted that are necessary to address in the future.
Nowadays with the help of advanced technology, modern vehicles are not only made up of mechanical devices but also consist of highly complex electronic devices and connections to the outside world. There are around 70 Electronic Control Units (ECUs) in modern vehicle which are communicating with each other over the standard communication protocol known as Controller Area Network (CAN-Bus) that provides the communication rate up to 1Mbps. There are different types of in-vehicle network protocol and bus system namely Controlled Area Network (CAN), Local Interconnected Network (LIN), Media Oriented System Transport (MOST), and FlexRay. Even though CAN-Bus is considered as de-facto standard for in-vehicle network communication, it inherently lacks the fundamental security features by design like message authentication. This security limitation has paved the way for adversaries to penetrate into the vehicle network and do malicious activities which can pose a dangerous situation for both driver and passengers. In particular, nowadays vehicular networks are not only closed systems, but also they are open to different external interfaces namely Bluetooth, GPS, to the outside world. Therefore, it creates new opportunities for attackers to remotely take full control of the vehicle. The objective of this research is to survey the current limitations of CAN-Bus protocol in terms of secure communication and different solutions that researchers in the society of automotive have provided to overcome the CAN-Bus limitation on different layers.
Abstract— Analysis of the security situation of networks is an important area in the information security research field. Furthermore, situation awareness is critical to the Internet of Things (IoT) given the limited lifetime, and autonomous nature of wireless sensor networks (WSN).
In this work, a measurement for situation awareness for the IoT is presented. This measurement can then be used to determine the security situation of a multi-application self-determining network to facilitate the deployment of object applications to a secured environment.
Using a simulation to compare the presented measurement to a power based approach provides that the presented approach did select different zones than the zones selected within the controlled set. Thus, resulting in a more accurate indication of the current security state of the WSN.
Potentially, utilization of this approach can contribute to the situation awareness of the cyber space in general to support ubiquitous computing; however, fundamentally it is a diagnostic tool that can be used to facilitate security within IoT. Thus, on both a local and global scale, it has the potential to predict the effectiveness of the location when considering deployment of an object application to IoT
With the development of railway transportation, it has put forward higher requirements for the safety of freight train. The present ground vehicle safety monitoring system, due to technical limitations, can’t meet the security requirement for real time information report of the train. Vehicular sensor can collect real-time vehicle information, to guarantee the safety of the train. Vehicle network is the basic of the communications between vehicular sensors. Because of the particularity of the freight train, a security vehicle network organization algorithm is proposed for the railway freight train based on lightweight authentication and property verification. Distance measured by distance sensor is the trigger event of the algorithm. The lightweight authentication makes the node trusted. Authenticating with speed and direction make the nodes belong to the same train. And ultimately vehicle network is established. Through the vehicle network, vehicle sensors collect data in real time and transmit to the ground processing system. Finally, ensure the safety of railway freight train.
The shared charging pile has the advantages of wide coverage, fast charging, negotiated electricity price, energy saving and environmental protection, and is an important part of the electric vehicle charging service network. With the popularity of electric vehicles and the large increase in the number of private rechargeable makeup accesses, the network security requirements for shared charging makeup systems are also increasing. A network security situational awareness model for shared charging makeup system is proposed. This model introduces network security detection, threat early warning analysis, risk decision response and security trend assessment for shared charging makeup system by introducing machine learning and data mining technology. The location addresses the security risks posed by cyber attacks and security breaches to ensure smooth operation of the shared charging makeup system.
Internet of Vehicles (IoV) is an emerging concept in
intelligent transportation systems (ITS) to enhance the existing
capabilities of VANETs by integrating with the Internet of Things
(IoT). IoV has dominated the transportation systems due to
numerous special traits like dynamic topological structures, huge
network scale, reliable internet connection, compatibility with
personal devices and high processing capability, etc. In this review,
an in-depth survey of IoV is carried out by discussing the
applications of IoV in different areas, as well as the comparative
study of IoV and VANETs, is being done. Intelligent transportation
system involves a huge amount of dynamic real-time critical data
so its security is a major concern. Different security aspects of IoV
are studied in this review which includes security requirements,
security challenges, and security attacks. After this, existing
security solutions of all attacks are elaborated and discussion
section is provided to highlight the drawbacks of security solutions
deployed for each attack as well as it emphasizes on the attacks for
which no security solutions are available. Based on the extensive
study conducted on this, it has been found that existing security
solutions use conventional cryptographic techniques that affect the
performance of the delay sensitive network i.e. IoV and VANETs.
So, a lightweight authentication protocol for RFID (RadioFrequency Identification devices) has also been proposed to
overcome the drawbacks of existing solutions and to provide better
performance in terms of low detection time, low CPU and memory
consumption to strengthen the existing IoV environment
The rapid growth of Internet of Vehicles (IoV) has brought huge challenges for large data storage, intelligent management, and information security for the entire system. The traditional centralized management approach for IoV faces the difficulty in dealing with real time response. The blockchain, as an effective technology for decentralized distributed storage and security management, has already showed great advantages in its application of Bitcoin. In this paper, we investigate how the blockchain technology could be extended to the application of vehicle networking, especially with the consideration of the distributed and secure storage of big data. We define several types of nodes such as vehicle and roadside for vehicle networks and form several sub-blockchain networks. In the paper, we present a model of the outward transmission of vehicle blockchain data, and then give detail theoretical analysis and numerical results. Our study has shown the potential to guide the application of Blockchain for future vehicle networking.
We present a new trust architecture-Situation-Aware Trust-to address several important trust issues in vehicular networks. SAT includes three main components: an attribute-based policy control model for highly dynamic communication environments, a proactive trust model to build trust among vehicles, and prevent the breakage of existing trust, and an email-based social network trust system to enhance trust and to allow the set up of a decentralized trust framework. To deploy SAT, we utilize identity-based cryptography to integrate entity trust, data trust, security policy enforcement, and social network trust, allocating a unique identity, and a set of attributes for each entity. We conclude by presenting research challenges and potential research directions that extend this work.
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