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Blockchain-Assisted UAV-Employed Casualty Detection Scheme in Search and Rescue Mission in the Internet of Battlefield Things
Abstract
As the unmanned aerial vehicle (UAV) can play a vital role to collect information remotely in a military battlefield, researchers have shown great interest to reveal the domain of internet of battlefield Things (IoBT). In a rescue mission on a battlefield, UAV can collect data from different regions to identify the casualty of a soldier. One of the major challenges in IoBT is to identify the soldier in a complex environment. Image processing algorithm can be helpful if proper methodology can be applied to identify the victims. However, due to the limited hardware resources of a UAV, processing task can be handover to the nearby edge computing server for offloading the task as every second is very crucial in a battlefield. Furthermore, to avoid any third-party interaction in the network and to store the data securely, blockchain can help to create a trusted network as it forms a distributed ledger among the participants. This paper proposes a UAV assisted casualty detection scheme based on image processing algorithm where data is protected using blockchain technology. Result analysis has been conducted to identify the victims on the battlefield successfully using image processing algorithm and network issues like throughput and delay has been analyzed in details using public-key cryptography.
... When a soldier is injured while performing a task on a mission, it might be difficult for him to connect with the base station, and there are occasions when data-calling alternatives are not accessible on the battlefield. Therefore, it is required to collect the injured soldier's information promptly and take necessary actions within a minimum time frame [2]. ...
This study proposes an intelligent approach to identifying an injured soldier on blockchain-integrated internet-of-battlefield things (IoBT) employing unmanned aerial vehicles (UAVs). The intelligent approach combines a unique deep learning (DL) model with a smartwatch-based heart-rate (HR) data collection technique. Different activation functions (i.e., MISH and Leaky rectified linear unit) are used in the proposed DL model to enhance the identification task by extracting the in-depth features from the images. Furthermore, a smart-watch-based HR data analyzing technique is introduced to confirm the injury of a soldier. However, due to the UAV's low battery capacity, the identification task is offloaded to the neighboring edge computing server to improve system performance. Moreover , to restrict the access of registered IoT devices (e.g., UAV, smartwatch, etc.) and protect the sensitive data leakage on IoBT, a blockchain-integrated access control (ACL) mechanism is utilized. Detailed experimental results are provided for the proposed DL model that outperforms existing DL models. Besides, implementing a smartwatch-based HR data analysis technique for the soldiers improves the outcome of the proposed DL model. To provide a fine-grained data protection mechanism in the proposed system, a private blockchain-based ACL management policy is constructed utilizing hyperledger, and various assessment metrics have been scrutinized.
... Therefore, a blockchain-based secure parcel delivery system is developed in this article. The blockchain is a distributed and decentralized ledger that protects the information to avoid third-party interaction [13]. It is possible to utilize the blockchain to improve the transparency and safety of aerial communication networks ( Figure 1), as well as to ensure the dependability of the data. ...
The optimization of parcel delivery services to consumers has become a priority due to the rapid development of the logistics industry, particularly in relation to the primary application of Industry 4.0. It is difficult to maintain trust between a travel company and its consumers. Although many of the current solutions identified in the research address trust issues, most of them are based on centralized architectures, such as cloud computing, where data is vulnerable to a variety of security threats. In this article, a multi-UAV-based secure parcel delivery system using blockchain has been proposed to increase trust among entities. Moreover, genetic algorithms (GA) are exploited to generate routing paths for multiple heterogeneous UAVs. Initially, optimizing fitness function, selection, crossover, and mutation operators are generated by utilizing the GA. The novelty of this research is to propose a secure delivery system using GA for heterogeneous multiple UAVs. Finally, the GA method is constructed to optimize the time constraint issue, and different consensus mechanisms are scrutinized to verify the performance (e.g., latency and average transaction) while storing the parcel delivery information in the blockchain network.
... The Internet of Things (IoT) is an interconnected infrastructure of connecting devices integrated into common things that can send and receive data and instruction [1]. The industrial Internet of things (IIoT) refers to using intelligent sensors and actuators attached to the IoT devices to improve manufacturing and industrial operational processes. ...
The Industrial Internet of Things (IIoT) focuses on connecting devices to gather real-time data and manually analyze it to make decisions. The IIoT devices could be equipped with some intelligence that empowers them to automatically create an informed choice and act with the ability for self-correction. This paper presents an innovative and secure approach to using industrial intelligence of things (IIoT 2.0) devices for designing an automated smart factory management system. Firstly, a blockchain-based secure order placement technique is proposed in a smart factory management system to store the production record permanently and avoid third-party interaction. This paper also introduces cooperative autonomous product tracking and maintenance systems using automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) to minimize human interaction inside a smart factory. Moreover, a deep learning model-based automated anomaly detection and prevention approach is demonstrated to take proactive action by the UAV and AGV inside a smart factory. Finally, to address the security issue
among IIoT 2.0 devices, a secure data transfer approach based on public-key infrastructure (PKI) is utilized. Result analysis of the proposed system shows that the blockchain network can form the blocks very rapidly using the private blockchain network.
Furthermore, PKI implementation confirms that the proposed smart factory management system’s IIoT 2.0 devices can swiftly transfer secure data and instructions from one device to another.
... In [31], the authors propose a blockchain-based framework for resource-constrained IoT devices. This framework focuses of three points; (i) split the global blockchain into smaller disjoint local blockchains in a spatial domain to take less space on IoT devices, (ii) limit the size of the local blockchains in the temporal domain; a temporal constraint is imposed on their lifetime, (iii) maintain at-least one block of the blockchain in the memory of a sensor node. ...
In the Internet of Battlefield Things (IoBT), users and sensor-equipped entities send multiple messages to the Command Control Center (CCC) over the network. The authentication and integrity of these messages are crucial because if an adversary or malicious node transmits, alters, or replays these messages, the consequences will be disasters. Current centralized authentication systems are not suitable for the distributed environment because such schemes are prone to a single point of failure, privacy, and scalability issues. Moreover, the high communication overhead caused by centralization increases energy consumption. In this work, we propose a technique called Blockchain-based Autonomous Authentication and Integrity for the Internet of Battlefield Things (BIoBT) for the C3I system. The proposed technique does not require an explicit authentication channel for the authentication of entities because it is performed on the blockchain side when receiving the data. In addition, it provides data integrity and non-repudiation. BIoBT prototype is created, deployed, and tested on the Ethereum test network. The results prove that BIoBT is efficient, cost-effective, and satisfies the security requirements of a distributed environment for IoBT. BIoBT also outperforms contemporary mechanisms in terms of the number of messages required to establish a secure channel, thereby reducing communication overhead and resource consumption.
... Moreover, comparing to region proposal based methods like RCNN or Faster RCNN, YOLO has relatively low recall and more localization error. Therefore, to overcome the existing issues of YOLO and use a DL model in a device with limited hardware capacity like UAV, YOLOv3-tiny can be effective in detecting any object in a real-time environment [45]. ...
In this paper, an automated real-time traffic management scheme is proposed by using unmanned aerial vehicles (UAV) in an effective and secured way. However, owing to the low computational capability and limited battery capacity of a UAV, multi-access edge computing (MEC) is applied to enhance the performance of an automated UAV-based traffic management scheme. Additionally, blockchain technology is introduced in the automated traffic management scheme to store the traffic record for providing network repudiation and avoiding any third-party interference with the network. An algorithm is developed based on the concept of a pairwise compatibility graph for the UAV-assisted automated traffic management scheme wherein a deep learning (DL) model is used for vehicle detection. Moreover, a two-phase authentication mechanism is proposed for a faster and secure verification process of the registered devices in the proposed scheme. Finally, a result analysis is conducted based on the security analysis and performance analysis to verify the effectiveness of the proposed scheme.
... The distributed ledger technology of blockchain can prevent any third-party involvement in the MEC server and establish an automatic emergency alert system if the CO 2 level in a smart factory drops. The blockchain contains a smart contract that can execute automatically when any specific condition satisfies the terms and conditions [8]. Therefore, the smart contract can prevent third-party involvement in the MEC server when declaring an emergency for evacuating a smart factory. ...
Monitoring the CO2 gas level in a smart factory is essential as the high levels of CO2 gas negatively affect the human body, causing various physical problems. This paper presents an Internet of Things (IoT) based CO2 gas level monitoring and automated decision-making system inside a smart factory using the unmanned aerial vehicle (UAV) and multi-access edge computing (MEC) technique. Firstly, different IoT device is used to continuously monitor and detect the CO2 gas level data using gas sensors. Due to the drawback of sink node failure and the centralized data collection technique of wireless sensor networks, a UAV-based continuous CO2 gas level monitoring approach has been introduced in this study. Moreover, the MEC-enabled data processing technique is utilized by offloading the sensor data from the UAV considering its limited battery capacity and low processing power. Finally, a blockchain-based secure decision-making system is designed to evacuate the smart factory premises by alerting all employees in an emergency case of an excessive level of CO2 gas existence. Result analysis shows that the IoT devices can successfully monitor and detect the CO2 gas level in the smart factory using the UAV. Furthermore, the UAV can securely offload sensor data to the MEC server to analyze and make an automated decision to alert all employees in a smart factory to evacuate if CO2 levels are too high.
Sharding is a promising technique to tackle the critical weakness of scalability in blockchain-based unmanned aerial vehicle (UAV) search and rescue (SAR) systems. By breaking up the blockchain network into smaller partitions called shards that run independently and in parallel, sharding-based UAV systems can support a large number of search and rescue UAVs with improved scalability, thereby enhancing the rescue potential. However, the lack of adaptability and interoperability still hinder the application of sharded blockchain in UAV SAR systems. Adaptability refers to making adjustments to the blockchain towards real-time surrounding situations, while interoperability refers to making cross-shard interactions at the mission level. To address the above challenges, we propose a blockchain UAV system for SAR missions based on dynamic sharding mechanism. Apart from the benefits in scalability brought by sharding, our system improves adaptability by dynamically creating configurable and mission-exclusive shards, and improves interoperability by supporting calls between smart contracts that are deployed on different shards. We implement a prototype of our system based on Quorum, give an analysis of the improved adaptability and interoperability, and conduct experiments to evaluate the performance. The results show our system can achieve the above goals and overcome the weakness of blockchain-based UAV systems in SAR scenarios.
The open and unreliable environment of the drone could make data transfer and authentication challenging. Given the proliferation of drone applications, the Internet of Drones (IoD) represents a promising phenomenon to enhance flight reliability and security. IoD has recently acquired pace due to its exceptional flexibility in numerous challenging circumstances. Furthermore, the incorporation of drones holds the potential to enhance many network systems’ performance metrics, such as throughput, scalability, connection, and latency. Regardless of its diverse domain, IoD is susceptible to malicious attacks owing to the wireless medium’s inherent unreliability. Drone communication can be made secure, reliable, and affordable by utilizing blockchain concepts that can be used to develop security mechanisms for addressing IoD’s shortcomings. This paper reviews emerging blockchain-powered schemes, focusing on their application in drone communication, authentication, and security. Our study explores various drone applications and intricacies associated with blockchain-based drone technology. By leveraging blockchain concepts, security mechanisms can mitigate IoD’s shortcomings. Unlike previous works, this survey offers a detailed examination of blockchain applications in drone technology. The research includes a thorough investigation into current IoD challenges and proposes insightful recommendations to fortify its security framework. Additionally, we conduct experiments on the runtime of consensus algorithms, providing a detailed comparison along with various security models. An analysis of recent work shows diverse approaches in blockchain for IoD, with a comparative study aimed at mitigating challenges. An overview of ML in IoD along with insightful research recommendations are also given that provide ways to improve IoD’s security.
UAVs have found their applications in numerous applications from recreational activities to business in addition to military and strategic fields. However, research on UAVs is not going on as quickly as the technology. Especially, when it comes to the security of these devices, the academia is lagging behind the industry. This gap motivates our work in this paper as a stepping stone for future research in this area. A comprehensive survey on the security of UAVs and UAV-based systems can help the research community keep pace with, or even lead the industry. Although there are several reviews on UAVs or related areas, there is no recent survey broadly covering various aspects of security. Moreover, none of the existing surveys highlights current and future trends with a focus on the role of an omnipresent technology such as AI. This paper endeavors to overcome these shortcomings. We conduct a comprehensive review on security challenges of UAVs as well as the related security controls. Then we develop a future roadmap for research in this area with a focus on the role of AI. The future roadmap is established based on the identified current trends, under-researched topics, and a future look-ahead.
The advancements in the internet of things, artificial intelligence, and state-of-the-art computing techniques are the main pillars of the next generation defense technology. The internet of battlefield things (IoBT) with edge intelligence offers new opportunities for defense professionals for smart and effective military operations. The IoBT network connects soldiers by placing smart sensors on armors, weapons, body, and surroundings. This paper presents a novel edge intelligence based estimation of gunshot direction from the sensor-enabled glove for smart IoBT wearables. A multi-agent multi-layer perceptron (MA-MLP) and other regression models are developed and tested on the experimental dataset collected during this study. The MA-MLP model consists of two distinct MLP networks and a fusion block to estimate the gunshot direction. This paper demonstrates the effect of multiple subjects, sensor positions, and gun material on mean absolute error (MAE) of MA-MLP prediction. The software simulation results show that our proposed MA-MLP model has outperformed traditional machine learning techniques like linear regression, SVM and MLP with an MAE of 4.09°. Two different hardware designs i.e., intellectual property (IP) cores of the pre-trained MA-MLP model are implemented and tested on a field-programmable gate array (FPGA) for a system on a chip (SoC) based edge gateway. The first IP core requires 280 nanoseconds with a power consumption of 354 milliwatts while the second IP core requires 380 nanoseconds with 178 milliwatts power consumption per inference. Prediction accuracy of 97.48% with a reduction of throughput to 92.2% is achieved for both IP cores. This work is one of the first attempts to implement the FPGA-based edge intelligence for the IoBT wearables. The short computation time, low power consumption, small footprint, significant throughput reduction, desired accuracy, and processor offloading are achieved by both flexible hardware models designed explicitly for the edge intelligence.
Voting is a very important issue that can be beneficial in terms of choosing the right leader in an election. A good leader can bring prosperity to a country and also can lead the country in the right direction every time. However, elections are surrounded by ballot forgery, coercion, and multiple voting issues. Moreover, while giving votes, a person has to wait in a long queue and it is a very time-consuming process. Blockchain is a distributed database in which data are shared with the participant of the node and each participant holds the same copy of the data. Blockchain has properties like transparency, pseudonymity, and data integrity. In this paper, a fully decentralized e-voting system based on blockchain technology is proposed. This protocol utilizes smart contracts in the e-voting system to deal with security issues, accuracy, and voters’ privacy during the vote. The protocol results in a transparent, non-editable, and independently verifiable procedure. The protocol discards all the intended fraudulent activities occurring during the election process by removing the least participation of the third party. Both transparency and coercion are obtained at the same time.
Controlling greenhouse effect especially reducing carbon-di-oxide (CO2) gas emission rate is one of the biggest difficulties of the 21st Century. This paper comprehensively described the issues regarding the greenhouse effect and possible controlling mechanism of the Green House Effect to save the world. As excessive CO2 gas emission in the atmosphere is the main reason for the Green House Effect (GHE), a simple and secure system can restrain the CO2 gas emission rate in the Universe. Blockchain Technology is introduced to protect the data from third-party alteration and to make the system more robust against the threats (i.e., cyber threats and data integrity). This paper endeavors to introduce a new dimension of research about controlling the GHE by collecting data with sensors and transmit these data to the blockchain with the assistance of the internet of things.
This paper presents a blockchain enabled secure data acquisition scheme utilizing an Unmanned Aerial Vehicle (UAV) swarm where data are collected from internet of things (IoT) devices and subsequently, forwarded to the nearest server through the UAV swarm. Before initiating data acquisition, the UAV swarm shares a shared key with IoT devices in order to maintain communications. However, prior to transmitting data, IoT devices encrypt the data and forward it to the UAV swarm. Upon receiving the data, the UAV swarm implements a two-phase validation utilizing the π-hash bloom filter and the digital signature algorithm to validate the sender; in addition, prior to forwarding data to the nearest server, it performs encryption. However, before adding data in blockchain, consent from all validators is required. Finally, the data are stored in blockchain with the approval of validators. A security analysis is performed to demonstrate the feasibility of the proposed scheme. Finally, the effectiveness of the proposed scheme is manifested through implementation and simulation. The security analysis and the performance results show that UAV assist IoT devices both in terms of connectivity and energy consumption, and provides security against the threats mentioned in the paper.
Voting is a very important issue which can be beneficial in term of choosing the right leader in an election. A good leader can bring prosperity to a country and also can lead the country in the right direction every time. However, elections are surrounds with ballot forgery, coercion and multiple voting issues. Moreover, while giving votes, a person has to wait in a long queue and it is a very time-consuming process. Blockchain is a distributed database in which data are shared with the participant of the node and each participant holds the same copy of the data. Blockchain has properties like distributed, pseudonymity, data integrity etc. In the paper, a fully decentralized e-voting system based on blockchain technology is proposed. This protocol utilizes smart contract into the e-voting system to deal with security issues, accuracy and voters’ privacy during the vote. The protocol results in a transparent, non-editable and independently verifiable procedure that discards all the intended fraudulent activities occurring during the election process by removing the least participation of the third party and enabling voters’ right during the election. Both transparency and coercion are obtained at the same time.
The battlefield of the future will be densely populated by a variety of entities ("things") -- some intelligent and some only marginally so -- performing a broad range of tasks: sensing, communicating, acting, and collaborating with each other and human warfighters. We call this the Internet of Battle Things, IoBT. In some ways, IoBT is already becoming a reality, but 20-30 years from now it is likely to become a dominant presence in warfare. To become a reality, however, this bold vision will have to overcome a number of major challenges. As one example of such a challenge, the communications among things will have to be flexible and adaptive to rapidly changing situations and military missions. In this paper, we explore this and several other major challenges of IoBT, and outline key research directions and approaches towards solving these challenges.
Wireless capsule endoscopy (WCE) is a process in which a patient swallows a camera-embedded pill-shaped device that passes through the gastrointestinal (GI) tract, captures and transmits images to an external receiver. WCE devices are considered as a replacement of conventional endoscopy methods which are usually painful and distressful for the patients. WCE devices produce over 60,000 images typically during their course of operation inside the GI tract. These images need to be examined by expert physicians who attempt to identify frames that contain inflammation / disease. It can be hectic for a physician to go through such a large number of frames, hence computer-aided detection methods are considered an efficient alternative. Various anomalies can take place in the GI tract of a human being but the most important and common ones and the aim of this survey are ulcers, polyps, and tumors. In this paper, we have presented a survey of contemporary computer-aided detection methods that take WCE images as input and classify those images in a diseased/abnormal or disease-free/ normal image. We have considered methods that detect tumors, polyps and ulcers, as these three diseases lie in the same category. Furthermore bleeding inside the GI tract may be the symptoms of these diseases; so an attempt is also made to enlighten the research work done for bleeding detection inside WCE. Several studies have been included with in-depth detail of their methodologies, findings, and conclusions. Also, we have attempted to classify these methods based on their technical aspects. This paper also includes a potential proposal for joint classification of aforementioned three diseases.
The real-time information of enemy locations is capable to transform the outcome of combat operations. Such information gathered using connected soldiers on the Internet of Battlefield Things (IoBT) is highly beneficial to create Situational Awareness (SA) and to plan an effective war strategy. The paper presents the novel enemy localization method that uses the soldier’s own locations and their gunshot direction. The hardware prototype has been developed that uses a triangulation for an enemy localization in two soldiers and a single enemy scenario. 4.24±1.77 meter of average localization error and ±4 of gunshot direction error has been observed during this prototype testing. This basic model is further extended using three-stage software simulation for multiple soldiers and multiple enemy scenarios with the necessary assumptions. The effective algorithm has been proposed, which differentiates between the ghost and true predictions by analyzing the groups of subsequent shooting intents (i.e frames). Four different complex scenarios are tested in the first stage of the simulation, around 3 to 6 frames are required for the accurate enemy localization in the relatively simple cases and 9 frames are required for the complex cases. The random error within ±4 in gunshot direction is included in the second stage of the simulation which required almost double the number of frames for similar four cases. As the number of frames increases, the accuracy of the proposed algorithm improves and better ghost point elimination is observed. In the third stage, two conventional clustering algorithms are implemented to validate the presented work. The comparative analysis shows that the proposed algorithm is faster, computationally simple, consistent and reliable compared with others. Detailed analysis of hardware and software results for various scenarios has been discussed in this paper.
Original Paper Link: https://ieeexplore.ieee.org/abstract/document/9106345
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This paper introduces a blockchain-based secure healthcare scheme in which health data (HD) are collected from users via an unmanned aerial vehicle (UAV) and stored on the nearest server. In the proposed scheme, a UAV first establishes a relation with body sensor hives (BSHs) via a token and then shares a shared key with BSHs to enable low-power secure communication. After retrieving the HD, the UAV decrypts the encrypted HD (encrypted by a BSH) using the shared key and exercises a two-phase authentication mechanism. Upon successful validation, the UAV transmits the HD to the nearest server to store it securely in blockchain. A security analysis is discussed to show the feasibility of the proposed secure healthcare scheme. Finally, the performance of the proposed scheme is investigated through simulation and implementation. The security and the performance analysis demonstrate that the proposed scheme supports better assistance to BSHs while maintaining security.
Trespassing in the marine area is a very critical issue. As a result, countries are losing revenue as well as it's a threat against the sovereignty of the country. As sea area is large, it's not always possible to monitor every part in real-time. Unmanned aerial vehicle (UAV) is a promising technology that can assist to alleviate this issue. However, communication between the control center and a UAV encircles with cyber threats as well as data in the surveillance may experience unauthorised modification. This paper represents a blockchain-empowered smart surveillance architecture in which UAV performs surveillance and uses a two-phase authentication process to verify the marine vehicles. The experimental result manifests that the proposed scheme is faster and consumes less energy than the existing authentication algorithms.
Internet of things (IoT), mobile edge computing (MEC), and unmanned aerial vehicle (UAV) have attracted significant attention in both industry and academic research. By consolidating these technologies, IoT can be facilitated with improved connectivity, better data transmission, energy saving, and other advantages. However, the communication between these entities is subject to potential cyber threats. In addition, the integrity of the data must be maintained after storing into local storage. Blockchain is a data structure that supports features like pseudonymity, data integrity etc. This paper represents a blockchain based data acquisition process in which information is gathered from IoTs using UAV as a relay and is securely kept in blockchain at MEC server. In the proposed scheme, data are encrypted prior to transfer to MEC server with the assistance of a UAV. Upon receiving the data, MEC server validates the data and the identity of the sender. Successful validation is followed by stocking of the data into blockchain, subsequent to obtaining consent from the validators. Security analysis is conducted in order to show the feasibility of the proposed secure scheme. Finally, the performance of the proposed scheme is analyzed via simulation and implementation.
