Detection Method and Mitigation of Server-Spoofing Attacks on SOME/IP at the Service Discovery Phase

Open AccessArticle

Detection Method and Mitigation of Server-Spoofing Attacks on SOME/IP at the Service Discovery Phase

Volume 11, Issue 1, Page No 25–32, 2026

Author’s Name: Kazuki Iehira* 1Email, Hiroyuki Inoue 2
1 Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, 603-8555, Japan
2 Faculty of Information Science and Engineering, Kyoto Sangyo University, Kyoto, 603-8555, Japan
*whom correspondence should be addressed. E-mail: i2386157@cc.kyoto-su.ac.jp

Adv. Sci. Technol. Eng. Syst. J. 11(1), 25–32 (2026); crossref symbol DOI: 10.25046/aj110103

Keywords: Control system security, Ethernet, IDS, SOME/IP, SOME/IP-IDS, Spoofing attack

Received: 14 November 2025, Revised: 18 December 2025, Accepted: 20 December 2025, Published Online: 11 January 2026
(This article belongs to the SP19 (Special Issue on Innovation in Computing, Engineering Science & Technology 2025-26) & Section Information Systems in Computer Science (CIS))
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Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes a method for detecting attacks in which an attacker spoofs a server during service discovery using a packet switch in a network employing SOME/IP. In addition, a mitigation method is proposed to discard malicious messages. The proposed method addresses the limitations of conventional encryption-based approaches by reducing both processing and communication loads. It also improves anomaly detection rate and detection timing, which have been identified as shortcomings in intrusion detection systems proposed in previous studies. In this study, we evaluated the method using a dataset consisting of 36 attack patterns that combined attack types, attack initiation timing, and message categories. Real-world evaluations demonstrated that the proposed method detected all server spoofing attempts. Further analysis of processing time and memory resource usage confirmed its feasibility for in-vehicle system.

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