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

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

Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013

Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners. The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation. With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration