Auflistung nach Autor:in "Schell, Oleg"
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- TextdokumentAssessment of Current Intrusion Detection System Concepts for Intra-Vehicle Communication(INFORMATIK 2020, 2021) Schell, Oleg; Reinhard, Jan Peter; Kneib, Marcel; Ring, MartinNowadays, vehicles incorporate a lot of electronics, which offer both advanced functionalities but also a great attack surface. Once having access to the communication network, an attacker can control critical functions like accelerating or steering. One possibility to detect these malicious intentions consists in the implementation of IDSs, which will even become mandatory via UN regulations in the future. Therefore, it is important for manufacturers and engineers to understand the opportunities and challenges of IDSs in the automotive environment. Giving an overview on these detection mechanisms is the primary goal of this elaboration. After the current vehicular communication architectures and protocols are outlined, potential attacks on the communication network are addressed. Afterwards, existing IDS concepts are presented, while the general requirements on these systems from an automotive perspective are stated and described next. Following the discussion on how to react to a detection, the elaboration is concluded with an outlook on what has still to be achieved to successfully integrate present IDSs into a vehicle.
- TextdokumentEffects of the Sampling Technique on Sender Identification Systems for the Controller Area Network(INFORMATIK 2020, 2021) Kneib, Marcel; Schell, OlegAs a result of the ongoing development of vehicle electronics and additional wireless communication interfaces, the possibilities for attacks and their negative consequences are increasing. Once an attacker has obtained access to the internal vehicle communication, in the case of the Controller Area Network (CAN) the attacker is able to forge all messages of the connected Electronic Control Units (ECUs) without a receiving ECU being able to recognize any suspicious behavior. The use of cryptographic methods is only possible to a limited extent due to restricted resources of the ECUs, which is why sender identification systems have been presented which are able to detect these kind of attacks. Presented approaches use different procedures to capture the analog signals on which the detection of attacks respectively the identification of the sender is based. This work shows that the impact on the performance of the sender identification system by the different sampling methods is minimal and therefore the selection of the appropriate technique can be mainly based on the available resources and the communication structure of the corresponding vehicle platform. This is shown on the one hand by the direct analysis of the analog signals captured from a real vehicle as well as by an evaluation of the previously introduced sampling methods using a recently published sender identification system. In addition, an assessment of the procedures based on different parameters shows which method is to be preferred for which application.
- AbstractMachine Learning Based Sender Identification for Controller Area Network(crypto day matters 29, 2018) Schell, Oleg; Kneib, Marcel