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Jens Gramm

Publications and source records attributed to Jens Gramm.

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From ECU to VSOC: UDS Security Monitoring Strategies

Increasing complexity and connectivity of modern vehicles have heightened their vulnerability to cyberattacks. This paper addresses security challenges associated with the Unified Diagnostic Services (UDS) protocol, a critical communication framework for vehicle diagnostics in the automotive industry. We present security monitoring strategies for the UDS protocol that leverage in-vehicle logging and remote analysis through a Vehicle Security Operations Center (VSOC). Our approach involves specifying security event logging requirements, contextual data collection, and the development of detection strategies aimed at identifying UDS attack scenarios. By applying these strategies to a comprehensive taxonomy of UDS attack techniques, we demonstrate that our detection methods cover a wide range of potential attack vectors. Furthermore, we assess the adequacy of current AUTOSAR standardized security events in supporting UDS attack detection, identifying gaps in the current standard. This work enhances the understanding of vehicle security monitoring and provides an example for developing robust cybersecurity measures in automotive communication protocols.

cs.CR

Parameterized Intractability of Motif Search Problems

We show that Closest Substring, one of the most important problems in the field of biological sequence analysis, is W[1]-hard when parameterized by the number k of input strings (and remains so, even over a binary alphabet). This problem is therefore unlikely to be solvable in time O(f(k)\cdot n^{c}) for any function f of k and constant c independent of k. The problem can therefore be expected to be intractable, in any practical sense, for k>=3. Our result supports the intuition that Closest Substring is computationally much harder than the special case of Closest String, although both problems are NP-complete. We also prove W[1]-hardness for other parameterizations in the case of unbounded alphabet size. Our W[1]-hardness result for Closest Substring generalizes to Consensus Patterns, a problem of similar significance in computational biology.

cs.CC