A secure cross-layer architecture for reactive routing in vehicle to vehicle (V2V) communications

Abstract

Vehicular communication is one of the essential technologies for increasing road safety, traffic efficiency, and comfort for pedestrians and drivers. In this context, the internet of vehicles is an emerging paradigm. However, with advances in vehicular communication, security threats have also emerged. Several vulnerabilities exist in vehicular communications, including Denial of Service (DoS), black hole attacks, and fabrication attacks. A malicious attack alters the packet information in a fabrication attack, causing congestion and high delays in the vehicular network. We propose two algorithms to protect the routing protocols in a vehicle-to-vehicle scenario against several attacks that target confidentiality, authentication, privacy, and integrity. The first algorithm detects the malicious behavior of each vehicle by calculating the percentage of modified destination addresses. If it exceeds a predetermined threshold, this vehicle is classified as malicious. Otherwise, it is a normal vehicle. The second algorithm detects malicious modifications based on the Signal to Interference Ratio (SIR) by monitoring the SIR value, adjusting the distance, altering the power received, and changing the transmitted power value. We performed simulations using the SUMO 0.22 simulator and Network Simulator (NS). The results obtained show an improvement in End-to-End (E2E) delay, Packet Delivery Ratio (PDR), and reduced overhead.

Introduction

Vehicular networks are now widely regarded as an effective technology for providing safety and comfort to both drivers and pedestrians. If drivers receive an urgent message half a second before the collision, 60 percent of accidents can be prevented [1]. Vehicular networks face many attacks [2], [3], [4], [5]. To offer predictable services, the networks' security should be ensured. The Dedicated Short-Range Communication (DSRC) channels are assigned by the Federal Communications Commission (FCC) and the European Intelligent Transportation System (ETSI) [6], [7]. The DSRC uses seven 10 MHz channels, numbered 172 to 184, that are currently dispersed across the spectrum between 5.860 and 5.925 GHz bands. FCC uses control channel 178 for secure communication only, while channels 174, 176, 180, and 182 are used to report insecure communications. Channels 172 and 184, the first and last channels respectively, are used for specific purposes such as high priority applications that prevent lower priority transmissions and intersection collision applications [4], [8]. However, in ETSI, the control channel 180 and the four service channels 176, 178, 182, and 184 are used for safety and traffic efficiency, while channels 172 and 174 are for non-safety applications such as traffic efficiency and service announcements [7] (Fig. 1).

Our work is based on a reactive routing protocol that starts by broadcasting a Route REQuest (RREQ) message from the source to find different paths to the destination. Next, in the reverse direction, the destination vehicle sends a Route REPly (RREP) message [9]. The intermediate vehicle measures the Signal to Interference Ratio (SIR) on the available CHannels (CH) during the reply state. Next, the vehicle chooses the maximum SIR value. The previously stated maximum SIR value is compared with the minimum SIR threshold. If the maximum SIR value is greater than the minimum SIR threshold, the maximum SIR value is sent in the reply message. Otherwise, the route reply is dropped. Each vehicle executes the proposed technique, with the maximum SIR value being compared to the maximum SIR value obtained from the RREP. The new maximum SIR value that will be delivered in the new route reply is the minimum value established between the previous two maxima. Finally, when the source receives many RREPs with various SIR values, the largest SIR value is used as the selection criterion. As a special case, when the source receives several RREPs with same SIR values, the shortest path is used as selection criterion.

In our work, we focus on detecting two types of attacks that occur at the network layer and MAC layer in the vehicle to reduce E2E delay and overhead as well as increase the PDR. In the first algorithm, we focus on detecting the attacks done by malicious vehicles in the destination address field. We implemented the proposed algorithm by creating a buffer that contains the input address and the output address. After every periodic time T, we checked the buffer of each vehicle. If the percentage of the changed destination addresses is greater than the $Threshold$, then the vehicle is considered malicious. In the second algorithm, we focus on detecting the attack on the SIR value. The attack occurs in three ways: in the first approach, the attack is made by modifying the SIR value. In the second approach, the power received is adjusted according to the sending of the periodic message with fake position to the current vehicle from its neighbors. In the third approach, the attack is done by modifying the power transmitted by the vehicle.

We organize the rest of the paper as follows. Section 2 presents a review of related works. Section 3 describes our previous work. Section 4 describes our proposed algorithms namely, the destination anti-attack and SIR anti-attack. Section 5 presents an evaluation of the effectiveness of the proposed algorithms. Finally, section 6 concludes the paper.