With the rapid development of information and communication technology, vehicular AD hoc networks (VANETs) has attracted more and more attention. In order to provide traffic safety services, vehicles frequently share information related to road traffic, such as vehicle motion data and traffic flow data. Reliable key generation is the basis of VANET security system construction. Presently, most key generation schemes rely on a trusted third party, so there are security risks. Traditional key agreement protocols have high overhead, and is not suitable for the latency-sensitive requirements of VANET. The physical layer security technology extracts the fingerprint of the wireless channel and the identity of the device, and generates the key quickly and in real time without the third party distribution. A physical layer key generation scheme based on received signal strength (RSS) is proposed to realize Vehicle-to-Vehicle (V2V) secure communications. First, a network model based on long short-term memory (LSTM) network and the Kalman filtering is proposed to effectively enhance the reciprocity of physical layer information in dynamic environment. Second, a lossless quantization scheme is proposed, which achieves a lower bit disagreement rate and a higher bit generation rate. Third, the inconsistent bits are corrected by fuzzy extractor, the confidentiality of the key exchange process is enhanced by zero knowledge proof, and the security of the key is improved by using hash function for privacy amplification. Finally, the experimental results show that the proposed scheme has great improvements in data correlation, bit disagreement rate, bit generation rate and bit distribution randomness.
T. Gobinath, Sanjay Kumar Sonkar, Vinod N. Alone, C. Thiripurasundari
As a distributed and decentralized ledger that ensures secure and transparent transactions, blockchain technology has attracted considerable interest. In the context of wireless sensor networks (WSNs), where nodes with limited resources conduct transactions, ensuring efficient and trustworthy validation becomes a challenge. Using random forests, this paper proposes a novel method for enhancing blockchain transaction validation in WSNs. The proposed method enhances the accuracy and efficiency of transaction validation in WSNs by leveraging the ensemble-learning capabilities of random forests. The random forests model is trained with transaction content, originating node information, and network metrics extracted from WSN transactions. Experimental results indicate that the proposed method improves transaction validation precision and decreases validation time in comparison to conventional methods. In addition, the random forests model is resistant to multiple types of attacks, assuring the security and integrity of WSN transactions. The results demonstrate that random forests are a promising technique for improving blockchain transaction validation in wireless sensor networks.
The Internet of Drones (IoD) manages and coordinates communications between drones in Internet of Things (IoT) applications. Ensuring security and privacy in unmanned aerial vehicles (UAVs) networks, i.e., drones, is essential to protect data from cyber attacks. In this context, providing authentication is a major challenge due to the fact that drones are devices limited in power capabilities. The problem is aggravated by the dynamism of IoD networks due to the high mobility of drones, being sensitive to packet loss and handovers. Blockchain technology is attractive to address the problem of centralization of existing authentication protocols. In this article, we provide a decentralized, secure, and efficient authentication protocol, based on$\mu $Tesla, that relies on Blockchain to manage drone authentication. We analyze the security and performance of the proposed solution. Simulation results show that the proposed solution outperforms several approaches in the literature, achieving an authentication delay of less than 250 ms with a low information exchange of 1024 bits for 128-bit security level while maintaining low computational requirements.
MANETs aredecentralized network that involves mobile nodes. As the overall network is mobile and has no centralization, network management, routing, and security become very challenging. Though many works have been presented, still there is a lack in organizing the network due to unauthorized access, centralized security schemes, and the dynamic nature of the nodes. This paper proposed a novel Blockchain-assisted Secure Routing (Block-Sec) protocol for MANETs. All mobile nodes are authenticated by Distributed One-Time Passcode (DOT) based authorization scheme. All authorized nodes are segregated into multiple clusters based on Weight based Dynamic Clustering (WDC) algorithm in which multiple metrics are considered in clustering and re-clustering processes. After cluster formation, each cluster is elected with optimal Cluster Head (CH) by Strawberry Optimization (SBO) algorithm with a new objective function. After cluster formation, the optimal route is selected by Fast Neural Net-assisted Fuzzy (FNNF) algorithm by combining multiple variables. Data transmission is secured by Efficient Elliptic Curve (E2C2) algorithm. With the combined algorithms, the proposed approach obtainedimproved efficiency in packet delivery ratio (PDR), throughput, time analysis, and security level.
Abstract In view of the node security risks and key management vulnerabilities in heterogeneous sensor networks, a key management protocol for heterogeneous sensor networks based on zero trust security and chaotic neural networks (KMPHSN-ZTSCNN) was proposed. Taking advantages of the decomposition difficulty of singular matrix and chaotic classification characteristics of Hopfield overload chaotic neural network, the node registration and authentication of sensor network were achieved by blockchain and zero-knowledge proof. The channel state information (CSI) and the adjustable mathematical function were relied on to generate a dynamically changing key to complete continuous verification and achieve zero trust security authentications, thus ensuring data security. The protocol can dynamically allocate different keyspace sizes according to the security level of the group, the storage capacity if the nodeand computing capacity and can adapt to the asymmetric structure of heterogeneous sensor networks. Theoretical proof and experimental performance analysis results show that the protocol is feasible and can meet the security requirements of heterogeneous sensor networks.
D. Paulraj, R Lavanya, T Jayasudha, M. Ishwarya Niranjana · 6 authors
Internet of Things node authentication via blockchain is discussed in this study (loST). Each node's credentials are verified as part of network security. Cluster leaders receive this data from sensor nodes and process it using loST. CHs gather information. They are exhausted by the additional workload. DDR-LEACHE was suggested as a solution to this issue. DDR-LEACH can replace CHs with conventional nodes if distance from the BS, residual energy and degree are taken into account. The cost of adding additional data to the blockchain is prohibitive. This problem can be solved by utilising IPFS, an external data store. Because AES 128-bit encryption is superior to other approaches, IPFS employs it to safeguard data. For transactions, proof-of-work requires too much computational resources. Consensus proof of authority is used as a basis for this solution (PoA). The model's efficiency and efficacy are demonstrated by the simulation results. According to a comparison, DDR-LEACH improves network lifetime while consuming less energy than LEACH. IPFS storage and service provisioning transaction costs can be reduced by using PoA. We can forecast how long it will take by comparing AES 128-bit encryption to the existing method. Smart contract security is examined. MITM and Sybil were used to test our system's resilience.
Siti Noor Farwina Mohamad Anwar Antony, Muhammad Fatihin Afiq Bahari
One of the challenges in securing wireless sensor networks (WSNs) is the key distribution; that is, a single shared key must first be known to a pair of communicating nodes before they can proceed with the secure encryption and decryption of the data. In 1984, Blom proposed a scheme called the symmetric key generation system as one method to solve this problem. Blom’s scheme has proven to be λ-secure, which means that a coalition of λ+1 nodes can break the scheme. In 2021, a novel and intriguing scheme based on Blom’s scheme was proposed. In this scheme, elliptic curves over a finite field are implemented in Blom’s scheme for the case when λ=1. However, the security of this scheme was not discussed. In this paper, we point out a mistake in the algorithm of this novel scheme and propose a way to fix it. The new fixed scheme is shown to be applicable for arbitrary λ. The security of the proposed scheme is also discussed. It is proven that the proposed scheme is also λ-secure with a certain condition. In addition, we also discuss the application of this proposed scheme in distributed ledger technology (DLT).
Gebrekiros Gebreyesus Gebremariam, Jeebananda Panda, S. Indu
Wireless sensor networks are the core of the Internet of Things and are used in healthcare, locations, the military, and security. Threats to the security of wireless sensor networks built on the Internet of Things (IoT-WSNs) can come from a variety of sources. This study proposes secure attack localization and detection in IoT-WSNs to improve security and service delivery. The technique used blockchain-based cascade encryption and trust evaluation in a hierarchical design to generate blockchain trust values before beacon nodes broadcast data to the base station. Simulation results reveal that cascading encryption and feature assessment measure the trust value of nodes by rewarding each other for service provisioning and trust by removing malicious nodes that reduce localization accuracy and quality of service in the network. Federated machine learning improves data security and transmission by merging raw device data and placing malicious threats in the blockchain. Malicious nodes are classified through federated learning. Federated learning combines hybrid random forest, gradient boost, ensemble learning, <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>K</a:mi> </a:math> -means clustering, and support vector machine approaches to classify harmful nodes via a feature assessment process. Comparing the proposed system to current ones shows an average detection and classification accuracy of 100% for binary and 99.95% for multiclass. This demonstrates that the suggested approach works well for large-scale IoT-WSNs, both in terms of performance and security, when utilizing heterogeneous wireless senor networks for the providing of secure services.
Wireless Sensor Networks—WSNs, an important part of IoT—consist of sensor nodes with limited processing, memory capacities, and energy. Wireless Sensor Networks face many dangers as they are often distributed into untrusted regions. The accuracy of the data obtained in a WSN, where security threats cannot be prevented, is also questioned. In WSNs, the authentication of the resources and the data can be verified with the authentication mechanism. Authentication in WSNs allows the node to verify whether data have been sent from authorized sources and protects the original data from changes. However, there are some deficiencies in terms of security in existing authentication protocols such as ID spoofing attacks. In addition, blockchain, one of the emerging technologies, gives significant successful results in security applications. Cryptographically secured, immutable, non-repudiable, irrevocable, auditable, and verifiable can be given as security-related characteristics of the blockchain. This study aims to use these features of the blockchain in WSNs. In this study, a new blockchain-based authentication protocol was developed for WSNs. Based on the study’s system model, sensor nodes, cluster nodes, base station, and blockchain networks were created using a private blockchain, and users. A detailed security analysis was carried out for the study. At the same time, efficiency analysis was performed by implementing the proposed model on the WiSeN sensor node.
Mahmoud A. Shawky, Abdul Jabbar, Muhammad Usman, Muhammad Ali Imran · 7 authors
This letter proposes a group key distribution scheme using smart contract-based blockchain technology. The smart contract’s functions allow for securely distributing the group session key, following the initial legitimacy detection using public key infrastructure-based authentication. For message authentication, we propose a lightweight symmetric key cryptography-based group signature method, supporting the security and privacy requirements of vehicular ad hoc networks (VANETs). Our discussion examined the scheme’s robustness against typical adversarial attacks. To evaluate the gas costs associated with smart contracts functions, we implemented it on the Ethereum main network. Finally, comprehensive analyses of computation and communication costs demonstrate the scheme’s effectiveness.
Zahoor Ali Khan, Sana Amjad, Farwa Ahmed, Abdullah M. Almasoud · 6 authors
Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities.
Distributed detection over a blockchain-aided Internet of Things (BIoT) network in the presence of attacks is considered, where the integrated blockchain is employed to secure data exchanges over the BIoT as well as data storage at the agents of the BIoT. We consider a general adversary model where attackers jointly exploit the vulnerability of IoT devices and that of the blockchain employed in the BIoT. The optimal attacking strategy which minimizes the Kullback-Leibler divergence is pursued. It can be shown that this optimization problem is nonconvex, and hence it is generally intractable to find the globally optimal solution to such a problem. To overcome this issue, we first propose a relaxation method that can convert the original nonconvex optimization problem into a convex optimization problem, and then the analytic expression for the optimal solution to the relaxed convex optimization problem is derived. The optimal value of the relaxed convex optimization problem provides a detection performance guarantee for the BIoT in the presence of attacks. In addition, we develop a coordinate descent algorithm which is based on a capped water-filling method to solve the relaxed convex optimization problem, and moreover, we show that the convergence of the proposed coordinate descent algorithm can be guaranteed.
Vankamamidi S. Naresh, V. V. L. Divakar Allavarpu, Sivaranjani Reddi
The advent of group-oriented communication applications has triggered research on secure group communication (SGC) in vehicular ad hoc networks (VANETs). Given this, some researchers worked in this area and proposed various schemes. However, these systems lacking the dynamic nature, and struggling with larger processing loads, enormous storage, increased communications, security, and privacy concerns. Further, with the increase in the size of VANET, it is challenging to manage processing loads and storage requirements of group controller (GC)-centric group key agreement (GKA). To address these drawbacks in existing VANET communications, we propose a blockchain IOTA sharding-based smart contract-centric GKA for SGC in large VANETs. In this scheme, we partition the main network into${r}$sharded subnetworks using blockchain sharding technique, with$G_{1}, G_{2}, G_{3},\ldots, G_{r}$as smart contract (SC) instances generated by GC, G, which functions as Sub-GC (Sub-GC) to their respective shards. Under the Elliptic curve decision Diffie–Hellman (ECDDH) and group-Elliptic curve Diffie-Hellman (GECCDH) assumptions, the proposed protocol is proven to be secure. The suggested protocol outperforms the other protocols for secure communication in large VANETs, according to the performance analysis.
Wireless Sensor Networks (WSNs) are becoming more popular for many applications due to their convenient services. However, sensor nodes may suffer from significant security flaws, leading researchers to propose authentication schemes to protect WSNs. Although these authentication protocols significantly fulfill the required protection, security enhancement with less energy consumption is essential to preserve the availability of resources and secure better performance. In 2020, Youssef et al. suggested a scheme called Enhanced Probabilistic Cluster Head Selection (LEACH-PRO) to extend the sensors' lifetime in WSNs. This paper introduces a new variant of the LEACH-PRO protocol by adopting the blockchain security technique to protect WSNs. The proposed protocol (SLEACH-PRO) performs a decentralized authentication mechanism by applying a blockchain to multiple base stations to avoid system and performance degradation in the event of a station failure. The security analysis of the SLEACH-PRO is performed using Burrows-Abadi-Needham (BAN) logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, the SLEACH-PRO is evaluated and compared to related protocols in terms of computational cost and security level based on its resistance against several attacks. The comparison results showed that the SLEACH-PRO protocol is more secure and requires less computational cost compared to other related protocols.
Autonomous inspection and measurement have become an integral part of smart IoT ecosystem. Low cost mobile and static sensing devices have leveraged the concept of smart factory in different industries such as healthcare, manufacturing, transportation etc. However, in case of remote sensing where the sensing devices are at distant locations it becomes infeasible for the central data aggregator or control center to evaluate the integrity and authenticity of the sensing data. This situation becomes even worse in case of compromised sensing devices due to cyber-attacks such as forged identity, spoofing, false data injection etc. This work in progress paper proposes a novel idea for blockchain based distributed sensing data aggregation scheme for UAV swarms. This distributed system could detect the malicious actors (sensors) without the intervention of central authority and thus enhances the integrity of the sensing data. In order to eliminate the payloads on the on-board UAVs, we have leveraged the storage capacity of the network edge components for storing the blockchain ledger of the network. We also explored and developed different threat models for UAV information acquisition networks.
For the past few years, centralized decision-making is being used for malicious node identification in wireless sensor networks (WSNs). Generally, WSN is the primary technology used to support operations, and security issues are becoming progressively worse. In order to detect malicious nodes in WSN, a blockchain-routing- and trust-model-based jellyfish search optimizer (BCR-TM-JSO) is created. Additionally, it provides the complete trust-model architecture before creating the blockchain data structure that is used to identify malicious nodes. For further analysis, sensor nodes in a WSN collect environmental data and communicate them to the cluster heads (CHs). JSO is created to address this issue by replacing CHs with regular nodes based on the maximum remaining energy, degree, and closeness to base station. Moreover, the Rivest–Shamir–Adleman (RSA) mechanism provides an asymmetric key, which is exploited for securing data transmission. The simulation outcomes show that the proposed BCR-TM-JSO model is capable of identifying malicious nodes in WSNs. Furthermore, the proposed BCR-TM-JSO method outperformed the conventional blockchain-based secure routing and trust management (BSRTM) and distance degree residual-energy-based low-energy adaptive clustering hierarchy (DDR-LEACH), in terms of throughput (5.89 Mbps), residual energy (0.079 J), and packet-delivery ratio (89.29%).
In recent years, with the continuous development of UAV technology, the application of the UAV swarm in the military has been a global focus of research. Although it can bring a series of benefits in autonomous cooperation, the traditional UAV management technology is prone to hacker attacks due to many security issues, such as a single point of failure brought by centralized management and the lack of reliable identity authentication. This paper studies the advantages and the recent advances of the blockchain in UAV swarm, proposes a blockchain-based UAV swarm identity management model (B-UIM-M), and establishes a distributed identity authentication scheme based on the distributed identity identifier (DID) under this model. Moreover, to ensure the safe transmission of UAV communication data, a secure communication architecture based on blockchain and a set of secure transmission protocols were designed, combined with cryptography. In the current military field, there is no similar application case of the UAV swarm identity management model and distributed identity authentication. The feasibility and security of the proposed scheme are proved through experiments and security analyses.
Abstract Aiming at the node security risks and key management vulnerabilities in heterogeneous sensor networks, a key management protocol for heterogeneous sensor networks based on zero-trust security and chaotic neural networks (KMPHSN-ZTSCNN) was proposed. Based on the singular matrix decomposition of difficulty and Hopfield overload chaos neural network classification features, using blockchain and zero-knowledge proof to realize sensor network node registration and authentication, it relies on channel state information (CSI) and adjustable mathematical function to generate dynamically changing keys to complete continuous verification and achieve zero-trust security authentication to ensure data security. The protocol can dynamically allocate different keyspace sizes according to the security level of the group, node storage capacity and computing capacity, and can adapt to the asymmetric structure of heterogeneous sensor networks. Theoretical proof and experimental performance analysis show that the protocol is feasible and can meet the security requirements of heterogeneous sensor networks.