Biblio

Controller Area Network is the bus standard that works as a central system inside the vehicles for communicating in-vehicle messages. Despite having many advantages, attackers may hack into a car system through CAN bus, take control of it and cause serious damage. For, CAN bus lacks security services like authentication, encryption etc. Therefore, an anomaly detection system must be integrated with CAN bus in vehicles. In this paper, we proposed an Artificial Neural Network based anomaly detection method to identify illicit messages in CAN bus. We trained our model with two types of attacks so that it can efficiently identify the attacks. When tested, the proposed algorithm showed high performance in detecting Denial of Service attacks (with accuracy 100%) and Fuzzy attacks (with accuracy 99.98%).

In most produced modern vehicles, Passive Keyless Entry and Start System (PKES), a newer form of an entry access system, is becoming more and more popular. The PKES system allows the consumer to enter within a certain range and have the vehicle's doors unlock automatically without pressing any buttons on the key. This technology increases the overall convenience to the consumer; however, it is vulnerable to attacks known as relay and amplified relay attacks. A relay attack consists of placing a device near the vehicle and a device near the key to relay the signal between the key and the vehicle. On the other hand, an amplified relay attack uses only a singular amplifier to increase the range of the vehicle sensors to reach the key. By exploiting these two different vulnerabilities within the PKES system, an attacker can gain unauthorized access to the vehicle, leading to damage or even stolen property. To minimize both vulnerabilities, we propose a coordinate tracing system with an additional Bluetooth communication channel. The coordinate tracing system, or PKES Forcefield, traces the authorized key's longitude and latitude in real time using two proposed algorithms, known as the Key Bearing algorithm and the Longitude and Latitude Key (LLK) algorithm. To further add security, a Bluetooth communication channel will be implemented. With an additional channel established, a second frequency can be traced within a secondary PKES Forcefield. The LLK Algorithm computes both locations of frequencies and analyzes the results to form a pattern. Furthermore, the PKES Forcefield movement-tracing allows a vehicle to understand when an attacker attempts to transmit an unauthenticated signal and blocks any signal from being amplified over a fixed range.