Secure Trust-Based Blockchain Architecture to Prevent Attacks in VANET

Vehicular ad hoc networks (VANET) are also known as intelligent transportation systems. VANET ensures timely and accurate communications between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve road safety and enhance the efficiency of traffic flow. Due to its open wireless boundary and high mobility, VANET is vulnerable to malicious nodes that could gain access into the network and carry out serious medium access control (MAC) layer threats, such as denial of service (DoS) attacks, data modification attacks, impersonation attacks, Sybil attacks, and replay attacks. This could affect the network security and privacy, causing harm to the information exchange within the network by genuine nodes and increase fatal impacts on the road. Therefore, a novel secure trust-based architecture that utilizes blockchain technology has been proposed to increase security and privacy to mitigate the aforementioned MAC layer attacks. A series of experiment has been conducted using the Veins simulation tool to assess the performance of the proposed solution in the terms of packet delivery ratio (PDR), end-to-end delay, packet loss, transmission overhead, and computational cost.

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Toward Blockchain-Enabled Privacy-Preserving Data Transmission in Cluster-Based Vehicular Networks

Electronics ◽

10.3390/electronics9091358 ◽

2020 ◽

Vol 9 (9) ◽

pp. 1358 ◽

Cited By ~ 1

Author(s):

Gyanendra Prasad Joshi ◽

Eswaran Perumal ◽

K. Shankar ◽

Usman Tariq ◽

Tariq Ahmad ◽

...

Keyword(s):

Data Transmission ◽

Intelligent Transportation Systems ◽

Vehicular Ad Hoc Networks ◽

Privacy Preserving ◽

Transportation Systems ◽

Security And Privacy ◽

Driving Safety ◽

Delivery Ratio ◽

Blockchain Technology ◽

On The Road

In recent times, vehicular ad hoc networks (VANET) have become a core part of intelligent transportation systems (ITSs), which aim to achieve continual Internet connectivity among vehicles on the road. The VANET has been used to improve driving safety and construct an ITS in modern cities. However, owing to the wireless characteristics, the message transmitted through the network can be observed, altered, or forged. Since driving safety is a major part of VANET, the security and privacy of these messages must be preserved. Therefore, this paper introduces an efficient privacy-preserving data transmission architecture that makes use of blockchain technology in cluster-based VANET. The cluster-based VANET architecture is used to achieve load balancing and minimize overhead in the network, where the clustering process is performed using the rainfall optimization algorithm (ROA). The ROA-based clustering with blockchain-based data transmission, called a ROAC-B technique, initially clusters the vehicles, and communication takes place via blockchain technology. A sequence of experiments was conducted to ensure the superiority of the ROAC-B technique, and several aspects of the results were considered. The simulation outcome showed that the ROAC-B technique is superior to other techniques in terms of packet delivery ratio (PDR), end to end (ETE) delay, throughput, and cluster size.

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Secure Routing through Refining Reliability for WSN against DoS Attacks using AODSD2V2 Algorithm for AMI

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.i8178.0881019 ◽

2019 ◽

Vol 8 (10) ◽

pp. 282-289

Keyword(s):

Wireless Communication ◽

Denial Of Service ◽

Secure Routing ◽

Electricity Sector ◽

Sensor Nodes ◽

Delivery Ratio ◽

Dos Attacks ◽

Malicious Nodes ◽

Communication Infrastructure ◽

Reliable Routing

Secure and reliable routing expands the performance of wireless communication infrastructure of the Advanced Metering Infrastructure (AMI).This paper tries to deliver reliable routing using combination of AODV(Reactive type protocol) and DSDV(proactive type protocol) protocol considering WSN. Different kinds of Attack annoys the enactment of communication infrastructure of AMI. This paper defends communication infrastructure from DoS (Denial of service) attack. The main aim of this paper try to provide reliable routing with security. Communication infrastructure is a key element of AMI. Providing reliability and security for communication infrastructure we can improve the performance of AMI. Due to this electricity sector can save millions of dollars and we provide social awareness about importance of electricity security or Smart Grid. This paper calculates the security in terms of delay, energy consumption, throughput, PDR (Packet Delivery Ratio) and overhead. By considering these parameters we will calculate Confidentiality, Integrity, Availability and Accountability (non- repudiation). Wireless Sensor Network (WSN) considered for wireless communication infrastructure for the AMI. Sensor nodes are battered for attack. Intended for AODSD2V2 (Ad Hoc on Demand Destination Sequenced Distance Vector Routing Protocol) protects the data packets from malicious nodes and DoS attack. For the WSN network infrastructure two kinds of topologies are considered 1. Random deployment strategy 2. Grid deployment. Network Simulator2 (NS2) delivers comparatively simulation results intended for the calculation of reliability and security.

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An Effective Secure Mechanism using Fuzzy Hybrid DCR Technique for MANET

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4921.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 2591-2599

Keyword(s):

Denial Of Service ◽

Optimal Path ◽

Detection Threshold ◽

Attack Detection ◽

Packet Transmission ◽

Detection Technique ◽

Delivery Ratio ◽

Dos Attacks ◽

Malicious Nodes ◽

Control Packet

Due to various Denial-of-Service (DoS) attacks like blackhole and grayhole attacks, Mobile Ad-Hoc Networks (MANET) performance is degraded rapidly. These attacks have been detected and prevented separately by different techniques. In earlier research, hybrid black/grayhole attack detection was proposed in which blackhole and grayhole attacks were detected and prevented simultaneously based on the detection threshold. However, some malicious nodes are still present in the network by faking the threshold value and forwarding the fake message to the other nodes. Therefore, the hybrid black/grayhole attack detection is enhanced by integrating network metric measurements. In this paper, the Data-to-Control packet Ratio (DCR) is measured for removing malicious nodes from the network and also avoiding the false detection. In addition, fuzzybased mobility and traffic measurement is integrated with a hybrid DCR detection technique for removing malicious node links. Moreover, the optimal path for packet transmission is selected by measuring the queue delay based on fuzzy logic optimization. Finally, the efficiency of the proposed hybrid blackhole/grayhole attack detection technique is illustrated through the simulation results based on the throughput, packet drop rate, packet delivery ratio and routing overhead

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DoS Attacks at Cooperative MAC

10.31224/osf.io/h5rtc ◽

2018 ◽

Author(s):

Kiramat

Keyword(s):

Wireless Networks ◽

Performance Improvement ◽

Wireless Lan ◽

Denial Of Service ◽

Channel Access ◽

Cooperative Network ◽

Mac Layer ◽

Dos Attacks ◽

Cooperative Protocols ◽

Cooperative Mac

—Cooperative networking brings performance improvement to most of theissues in wireless networks, such as fading or delay due to slow stations. However, due tocooperation when data is relayed via other nodes, there network is more prone to attacks.Since, channel access is very important for cooperation, most of the attacks happens at MAC.One of the most critical attack is denial of service, which is reason of cooperation failure.Therefore, the cooperative network as well as simple wireless LAN must be defensive againstDOS attacks.In this article we analyzed all possible of DoS attacks that can happen at MAC layer ofWLAN. The cooperative protocols must consider defense against these attacks. This articlealso provided survey of available solutions to these attacks. At the end it described itsdamages and cost as well as how to handle these attacks while devising cooperative MAC.

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Detection and Identification of Malicious Cyber-Attacks in Connected and Automated Vehicles’ Real-Time Sensors

Applied Sciences ◽

10.3390/app10217833 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7833

Author(s):

Elvin Eziama ◽

Faroq Awin ◽

Sabbir Ahmed ◽

Luz Marina Santos-Jaimes ◽

Akinyemi Pelumi ◽

...

Keyword(s):

Real Time ◽

Information Exchange ◽

Information Dissemination ◽

Transportation Systems ◽

Cyber Attacks ◽

Security And Privacy ◽

Discrete Wavelet ◽

Automated Vehicles ◽

Sensor Reading ◽

Detection And Identification

Connected and automated vehicles (CAVs) as a part of Intelligent Transportation Systems (ITS) are projected to revolutionise the transportation industry, primarily by allowing real-time and seamless information exchange of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). However, these connectivity and automation are expected to offer vast numbers of benefits, new challenges in terms of safety, security and privacy also emerge. CAVs continue to rely heavily on their sensor readings, the input obtained from other vehicles and the road side units to inspect roadways. Consequently, anomalous reading of sensors triggered by malicious cyber attacks may lead to fatal consequences. Hence, like all other safety-critical applications, in CAVs also, reliable and secure information dissemination is of utmost importance. As a result, real time detection of anomaly along with identifying the source is a pre-requisite for mass deployment of CAVs. Motivated by this safety concerns in CAVs, we develop an efficient anomaly detection method through the combination of Bayesian deep learning (BDL) with discrete wavelet transform (DWT) to improve the safety and security in CAVs. In particular, DWT is used to smooth sensor reading of a CAV and then feed the data to a BDL module for analysis of the detection and identification of anomalous sensor behavior/data points caused by either malicious cyber attacks or faulty vehicle sensors. Our numerical experiments show that the proposed method demonstrates significant improvement in detection anomalies in terms of accuracy, sensitivity, precision, and F1-score evaluation metrics. For these metrics, the proposed method shows an average performance gain of 7.95%, 9%, 8.77% and 7.33%, respectively when compared with Convolutional Neural Network (CNN-1D), and when compared with BDL, the corresponding numbers are 5%, 7.9%, 7.54% and 4.1% respectively.

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Cyber DoS attack based security simulator for VANET

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i6.pp5832-5843 ◽

2020 ◽

Vol 10 (6) ◽

pp. 5832

Author(s):

Muntadher Naeem Yasir ◽

Muayad Sadik Croock

Keyword(s):

Cyber Security ◽

Information Exchange ◽

Network Performance ◽

Ad Hoc ◽

High Efficiency ◽

Denial Of Service ◽

Attack Detection ◽

Dos Attack ◽

Dos Attacks ◽

High Importance

At the late years, researches focused on the cyber Denial of Service (DoS) attacks in the Vehicle Ad hoc Networks (VANETS). This is due to high importance of ensuring the save receiving of information in terms of Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I) and Vehicle to Road Side Unit (V2R). In this paper, a cyber-security system is proposed to detect and block the DoS attacks in VANET. In addition, a simulator for VENAT based on lightweight authentication and key exchange is presented to simulate the network performance and attacks. The proposed system consists of three phases: registration, authentication as well as communications and DoS attack detection. These phases improve the system ability to detect the attacks in efficient way. Each phase working is based in a proposed related algorithm under the guidance of lightweight protocol. In order to test the proposed system, a prototype is considered includes six cars and we adopt police cars due to high importance of exchanged information. Different case studies have been considered to evaluate the proposed system and the obtained results show a high efficiency of performance in terms of information exchange and attack detection.

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Resilient Self-Triggered Control for Voltage Restoration and Reactive Power Sharing in Islanded Microgrids under Denial-of-Service Attacks

Applied Sciences ◽

10.3390/app10113780 ◽

2020 ◽

Vol 10 (11) ◽

pp. 3780

Author(s):

Gang Xu ◽

Liang Ma

Keyword(s):

Information Exchange ◽

Reactive Power ◽

Denial Of Service ◽

Control Level ◽

Power Sharing ◽

Accurate Estimation ◽

Secondary Control ◽

Dos Attacks ◽

Control Scheme ◽

Average Information

This paper addresses the problem of voltage restoration and reactive power sharing of inverter-based distributed generations (DGs) in an islanded microgrid subject to denial-of-service (DoS) attacks. Note that DoS attacks may block information exchange among DGs by jamming the communication network in the secondary control level of a microgrid. A two-layer distributed secondary control framework is presented, in which a state observer employing the multiagent system (MAS)-based ternary self-triggered control is implemented for discovering the average information of voltage and reactive power in a fully distributed manner while highly reducing communication burden than that the periodic communication way. The compensation for the reference signal to the primary control is acquired according to the average estimates to achieve voltage restoration while properly sharing reactive power among DGs. An improved ternary self-triggered control strategy integrating an acknowledgment (ACK)-based monitoring mechanism is established, where DoS attacks are modeled by repeated cycles of jamming and sleeping. A new triggering condition is developed to guarantee the successful information exchange between DGs when the sleep period of DoS attacks is detected. Using the Lyapunov approach, it is proved that the proposed algorithm allows agents to reach consensus regardless of the frequency of the DoS attacks, which maintains the accurate estimation of average information and the implementation of the secondary control objectives. The performance of the proposed control scheme is evaluated under simulation and experimental conditions. The results show that the proposed secondary control scheme can highly reduce the inter-agent communication as well as improve the robustness of the system to resist DoS attacks.

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Modified fuzzy-based greedy routing protocol for VANETs

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189154 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8357-8364

Author(s):

Thompson Stephan ◽

Ananthnarayan Rajappa ◽

K.S. Sendhil Kumar ◽

Shivang Gupta ◽

Achyut Shankar ◽

...

Keyword(s):

Fuzzy Logic ◽

Routing Protocol ◽

Intelligent Transportation Systems ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Research Area ◽

Transportation Systems ◽

Delivery Ratio ◽

Greedy Routing ◽

Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

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Highway Speed Prediction Using Gated Recurrent Unit Neural Networks

Applied Sciences ◽

10.3390/app11073059 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3059

Author(s):

Myeong-Hun Jeong ◽

Tae-Young Lee ◽

Seung-Bae Jeon ◽

Minkyo Youm

Keyword(s):

Neural Network ◽

Intelligent Transportation Systems ◽

Moving Average ◽

Computational Cost ◽

Nonlinear Problems ◽

Transportation Systems ◽

Mobility Data ◽

Challenges And Opportunities ◽

Moving Average Model ◽

Gated Recurrent Unit

Movement analytics and mobility insights play a crucial role in urban planning and transportation management. The plethora of mobility data sources, such as GPS trajectories, poses new challenges and opportunities for understanding and predicting movement patterns. In this study, we predict highway speed using a gated recurrent unit (GRU) neural network. Based on statistical models, previous approaches suffer from the inherited features of traffic data, such as nonlinear problems. The proposed method predicts highway speed based on the GRU method after training on digital tachograph data (DTG). The DTG data were recorded in one month, giving approximately 300 million records. These data included the velocity and locations of vehicles on the highway. Experimental results demonstrate that the GRU-based deep learning approach outperformed the state-of-the-art alternatives, the autoregressive integrated moving average model, and the long short-term neural network (LSTM) model, in terms of prediction accuracy. Further, the computational cost of the GRU model was lower than that of the LSTM. The proposed method can be applied to traffic prediction and intelligent transportation systems.

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A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Electronics ◽

10.3390/electronics10111244 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1244

Author(s):

Hana Rhim ◽

Damien Sauveron ◽

Ryma Abassi ◽

Karim Tamine ◽

Sihem Guemara

Keyword(s):

Denial Of Service ◽

Base Station ◽

Hierarchical Organization ◽

Secure Routing ◽

Sensor Nodes ◽

Dos Attacks ◽

Linear Network ◽

Secure Protocol ◽

Misbehaving Nodes ◽

Pollution Attacks

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

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