Project

System security to protect automobiles from black-hat hackers

Various systems such as the automobiles, buses, wrist watches, are connected to the Internet and are closely related to our lives. In the automobiles, ECU (Electronic Control Unit) related to engine control and ADAS (Advanced Driver Assistance System) ralated to advance driving support system are Indirectly connected to the Internet. Therefore, if a adversary intrudes into in-vehicle systems and attack on it, our life is threatened. Hence, it is important to consider adversaries (malware, hardware trojans, etc...) in the in-vehicle systems, consider how to preserve evidence of malware, and how to detect and prevent DoS attacks on in-vehicle networks.

Research subject

In our laboratory, we focus on threat analysis and defense methods in the in-vehicle systems (automotive network, automotive infotainment system, ECU). We actually reverse engineer the in-vehicle network to understand the viewpoint of black-hat hackers, and conduct research. Also, Unlike the general information security, the information security in in-vehicle systems needs to consider both safety and security.
Therefore, we are conducting research on methods to preserve malicious activity on in-vehicle system and to detect/prevent DoS attack on in-vehicle network take into consideration safety concerns such as the delay constraint in the in-vehicle network.

Publication

  • [ASIACCS] Shuji Ohira, Araya Kibrom Desta, Ismail Arai, Kazutoshi Fujikawa, "PLI-TDC: Super Fine Delay-Time Based Physical-Layer Identification with Time-to-Digital Converter for In-Vehicle Networks," 2021 The 16th ACM ASIA Conference on Computer and Communications Security (ASIACCS), pp.1-11, June. 2021. (accepted) [Code]
  • [ITNAC] Araya Kibrom Desta, Shuji Ohira, Ismail Arai, Kazutoshi Fujikawa, "MLIDS: Handling Raw High-Dimensional CAN Bus Data using Long Short-Term Memory Networks for Intrusion Detection in In-Vehicle Networks," International Telecommunication Networks and Applications Conference (ITNAC), IEEE, pp.1-7, Nov. 2020.
  • [IPSJ Journal] Araya Kibrom Desta, Shuji Ohira, Ismail Arai, Kazutoshi Fujikawa, "Long Short-Term Memory Networks for Intrusion Detection Using Reverse Engineered Automotive Packets," Journal of Information Processing, Vol.61, No.9 pp.1-12, Sep. 2020. [PDF]
  • [COMPSAC, arxiv] Shuji Ohira, Araya Kibrom Desta, Tomoya Kitagawa, Ismail Arai, Kazutoshi Fujikawa, "Divider: Delay-Time Based Sender Identification in Automotive Networks," 2020 IEEE 44th Annual Computer Software and Applications Conference (COMPSAC), IEEE, pp.1490-1497, July. 2020. [PDF]
  • [PerCom Workshop] Araya Kibrom Desta, Shuji Ohira, Ismail Arai and Kazutoshi Fujikawa, "ID Sequence Analysis for Intrusion Detection in the CAN bus using Long Short Term Memory Networks," IEEE PerCom 2020, 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, pp59-64, USA, Mar. 2020. [PDF]
  • [Access] Shuji Ohira, Araya Kibrom Desta, Ismail Arai, Hiroyuki Inoue, Kazutoshi Fujikawa, “Normal and Malicious Sliding Windows Similarity Analysis Method for Fast and Accurate IDS against DoS Attacks on In-Vehicle Networks,” IEEE Access, Vol.8, pp.42422-42435, Feb. 2020. [PDF]
  • [CCI Research Workshop] Ismail Arai, Shuji Ohira, Kibrom Araya Desta, Kazutoshi Fujikawa, Ahmad Salman, and Samy El-Tawab, "Two strategies of packet based or electric signal based IDS for CAN," Poster, CCI Research Workshop, USA, Oct. 2019.
  • [ISCIS Security Workshop] Tomoya Kitagawa, Ismail Arai, Masatoshi Kakiuchi, Atsuo Inomata and Kazutoshi Fujikawa, "Fingerprinting of ECUs using delay time on Controller Area Networks," ISCIS Security Workshop 2018, Feb. 2018.