Attack Classification and Detection for Misbehaving Vehicles using ML/DL

Vehicle ad hoc networks are a crucial component of the next Intelligent Transportation System created to build a reliable and secure connection between various network components to establish a safe and effective transportation network. Because of open nature of VANETs become vulnerable to numerous assaults such forgery, Denial-of-Service (DoS), and false reports, which can ultimately cause traffic jams or accidents The earlier study concentrated on misbehaving vehicles rather than RSUs. Proposed method integrates data from two subsequent BSMs for testing and training by employing machine learning (ML) methods. The framework merges the data from two BSMs in the right manner and utilizes machine learning/Deep learning methodology which identify the running vehicle as a legal or hostile one

An Event Based Digital Forensic Scheme for Vehicular Networks

The software in today's cars has become increasingly important in recent years. The development of high-tech driver assistance devices has helped fuel this movement. This tendency is anticipated to accelerate with the advent of completely autonomous vehicles. As more modern vehicles incorporate software and security-based solutions, "Event-Based digital forensics," the analysis of digital evidence of accidents and warranty claims, has become increasingly significant. The objective of this study is to ascertain, in a realistic setting, whether or not digital forensics can be successfully applied to a state-of-the-art automobile. We did this by dissecting the procedure of automotive forensics, which is used on in-car systems to track the mysterious activity by means of digital evidence. We did this by applying established methods of digital forensics to a state-of-the-art car.Our research employs specialized cameras installed in the study areas and a log of system activity that may be utilized as future digital proof to examine the effectiveness of security checkpoints and other similar technologies. The goal is to keep an eye on the vehicles entering the checkpoint, look into them if there is any reason to suspect anything, and then take the appropriate measures. The problem with analyzing this data is that it is becoming increasingly complex and time-consuming as the amount of data that has been collected keeps growing. In this paper, we outline a high-level methodology for automotive forensics to fill in the blanks, and we put it through its paces on a network simulator in a state-of-the-art vehicle to simulate a scenario in which devices are tampered with while the car is in motion. Here, we test how well the strategy functions. Diagnostics over IP (Diagnostics over IP), on-board diagnostics interface, and unified diagnostic services are all used during implementation. To work, our solution requires vehicles to be able to exchange diagnostic information wirelessly.These results show that it is possible to undertake automotive forensic analysis on state-of-the-art vehicles without using intrusion detection systems or event data recorders, and they lead the way towards a more fruitful future for automotive forensics. The results also show that modern autos are amenable to forensic automotive analysis

BLACK HOLE ATTACK IN AODV & FRIEND FEATURES UNIQUE EXTRACTION TO DESIGN DETECTION ENGINE FOR INTRUSION DETECTION SYSTEM IN MOBILE ADHOC NETWORK

Ad-hoc network is a collection of nodes that are capable to form dynamically a temporary network without the support of any centralized fixed infrastructure. Since there is no central controller to determine the reliable & secure communication paths in Mobile Adhoc Network, each node in the ad hoc network has to rely on each other in order to forward packets, thus highly cooperative nodes are required to ensure that the initiated data transmission process does not fail. In a mobile ad hoc network (MANET) where security is a crucial issue and they are forced to rely on the neighbor node, trust plays an important role that could improve the number of successful data transmission. Larger the number of trusted nodes, higher successful data communication process rates could be expected. In this paper, Black Hole attack is applied in the network, statistics are collected to design intrusion detection engine for MANET Intrusion Detection System (IDS). Feature extraction and rule inductions are applied to find out the accuracy of detection engine by using support vector machine. In this paper True Positive generated by the detection engine is very high and this is a novel approach in the area of Mobile Adhoc Intrusion detection system

Spline Based Intrusion Detection in Vehicular Ad Hoc Networks (VANET)

Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are particularly difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that can satisfy these requirements. Spline function-based IDSs have shown to be effective in traditional network settings. By examining the various construction of splines and testing their robustness, the viability for a spline-based IDS can be determined

Knot Flow Classification and its Applications in Vehicular Ad-Hoc Networks (VANET)

Intrusion detection systems (IDSs) play a crucial role in the identification and mitigation for attacks on host systems. Of these systems, vehicular ad hoc networks (VANETs) are difficult to protect due to the dynamic nature of their clients and their necessity for constant interaction with their respective cyber-physical systems. Currently, there is a need for a VANET-specific IDS that meets this criterion. To this end, a spline-based intrusion detection system has been pioneered as a solution. By combining clustering with spline-based general linear model classification, this knot flow classification method (KFC) allows for robust intrusion detection to occur. Due its design and the manner it is constructed, KFC holds great potential for implementation across a distributed system. The purpose of this thesis was to explain and extrapolate the afore mentioned IDS, highlight its effectiveness, and discuss the conceptual design of the distributed system for use in future research

A novel secure routing scheme using probabilistic modelling for better resistivity against lethal attacks

Study towards Wireless Adhoc Network dates two decades back with various researchers evolving up with new solutions towards addressing its problems. Irrespective of various other problems, the issues related to the secure routing is yet unsolved owing to massively increasing fatal strategies of the adversary. Review of existing literature shows that the existing secure routing scheme can only govern over the stated attacks reducing the applicability in case of dynamic attacks. Therefore, this manuscript introduces a novel probabilistic model which offers the capability to wireless nodes to identify the malicious behavior and react accordingly. Different from existing intrusion prevention system, the proposed system allows the malicious node to participate in the data forwarding process and exhaust its resources with no chance of launching an attack. The simulated outcome of the study shows that the proposed secure routing scheme offers better data forwarding characteristic in contrast to the existing system in the aspect of intrusion detection and secure data transmission