A real-time remote IDS testbed for connected vehicles

Abstract

Connected vehicles are becoming commonplace. A constant connection between vehicles and a central server enables new features and services. This added connectivity raises the likelihood of exposure to attackers and risks unauthorized access.A possible countermeasure to this issue are intrusion detection systems (IDS), which aim at detecting these intrusions during or after their occurrence. The problem with IDS is the large variety of possible approaches with no sensible option for comparing them.Our contribution to this problem comprises the conceptualization and implementation of a testbed for an automotive real-world scenario. That amounts to a server-side IDS detecting intrusions into vehicles remotely. To verify the validity of our approach, we evaluate the testbed from multiple perspectives, including its fitness for purpose and the quality of the data it generates.Our evaluation shows that the testbed makes the effective assessment of various IDS possible. It solves multiple problems of existing approaches, including class imbalance. Additionally, it enables reproducibility and generating data of varying detection difficulties. This allows for comprehensive evaluation of real-time, remote IDS.

Towards a Lightweight Intrusion Detection Framework for In-Vehicle Networks

“…Valentin Zieglmeier et al [27] testbed is implemented on the use case based on a client-server architecture that is used popularly in the automobile industry. Here, the server will be a reference, and vehicles are abstracted from the outer perspective that sends a data-request to the server.…”

Um Testbed para o Ensino de Abordagens de IDS Baseadas em IA em Redes Emuladas

“…Em sua pesquisa [Mishra et al 2019] apresentam uma revisão sistemática abrangente sobre o uso de técnicas de aprendizagem para IDS. [Zieglmeier et al 2018] implementou um testbed para um cenário real de ataques automotivos. [Sai Kiran et al 2020] criaram um sistema de detecc ¸ão de intrusão para ambiente IoT usando técnicas de aprendizado de máquina.…”

Evaluation of the architecture alternatives for real-time intrusion detection systems for connected vehicles

“…They evaluated the IDS with CAN data collected from vehicles and open source. This approach yielded high accuracy and low false positives.Zieglmeier et al[20] developed a testbed for the connected vehicle to compare various real-time IDSs in real-world scenarios. This solved the problem of comparing IDSs with multiple test environments.…”