TY - GEN
T1 - A novel intrusion detection method using deep neural network for in-vehicle network security
AU - Kang, Min Ju
AU - Kang, Je Won
N1 - Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF- 2014R1A1A2056587).
Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/5
Y1 - 2016/7/5
N2 - In this paper, we propose a novel intrusion detection technique using a deep neural network (DNN). In the proposed technique, in-vehicle network packets exchanged between electronic control units (ECU) are trained to extract low- dimensional features and used for discriminating normal and hacking packets. The features perform in high efficient and low complexity because they are generated directly from a bitstream over the network. The proposed technique monitors an exchanging packet in the vehicular network while the feature are trained off-line, and provides a real-time response to the attack with a significantly high detection ratio in our experiments.
AB - In this paper, we propose a novel intrusion detection technique using a deep neural network (DNN). In the proposed technique, in-vehicle network packets exchanged between electronic control units (ECU) are trained to extract low- dimensional features and used for discriminating normal and hacking packets. The features perform in high efficient and low complexity because they are generated directly from a bitstream over the network. The proposed technique monitors an exchanging packet in the vehicular network while the feature are trained off-line, and provides a real-time response to the attack with a significantly high detection ratio in our experiments.
UR - http://www.scopus.com/inward/record.url?scp=84979753503&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2016.7504089
DO - 10.1109/VTCSpring.2016.7504089
M3 - Conference contribution
AN - SCOPUS:84979753503
T3 - IEEE Vehicular Technology Conference
BT - 2016 IEEE 83rd Vehicular Technology Conference, VTC Spring 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 83rd IEEE Vehicular Technology Conference, VTC Spring 2016
Y2 - 15 May 2016 through 18 May 2016
ER -