Abnormal Behavioral Pattern Detection in Closed-Loop Robotic Systems for Zero-Day Deceptive Threats

In recent years, attacks against cyber-physical systems have become increasingly frequent and widespread. The inventiveness of such attacks increases significantly. In particular, zero-day attacks are widely used. The rapid development of the industrial Internet of things, the expansion of the application areas of service robots, the advent of the Internet of vehicles and the Internet of military things have led to a significant increase of attention to deceptive attacks. Especially great threat is posed by deceptive attacks that do not use hiding malicious components. Such attacks can naturally be used against robotic systems. In this paper, we consider an approach to the development of an intrusion detection system for closed-loop robotic systems. The system is based on an abnormal behavioral pattern detection technique. The system can be used for detection of zero-day deceptive attacks. We provide an experimental comparison of our approach and other behaviorbased intrusion detection systems.

[1]  Kamil Kulesza,et al.  Humans cannot consciously generate random numbers sequences: Polemic study. , 2008, Medical hypotheses.

[2]  Hsiao-Hwa Chen,et al.  Intrusion Detection in Cyber-Physical Systems: Techniques and Challenges , 2014, IEEE Systems Journal.

[3]  Lalu Banoth,et al.  A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection , 2017 .

[4]  Shuzhi Sam Ge,et al.  Filter-Based Secure Dynamic Pose Estimation for Autonomous Vehicles , 2019, IEEE Sensors Journal.

[5]  Herbert J. Mattord,et al.  Principles of Information Security , 2004 .

[6]  Ravi Sankar,et al.  A Survey of Intrusion Detection Systems in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[7]  Ing-Ray Chen,et al.  Specification based intrusion detection for unmanned aircraft systems , 2012, Airborne '12.

[8]  Ing-Ray Chen,et al.  Behavior-Rule Based Intrusion Detection Systems for Safety Critical Smart Grid Applications , 2013, IEEE Transactions on Smart Grid.

[9]  Robert C. Green,et al.  Intrusion Detection System in A Multi-Layer Network Architecture of Smart Grids by Yichi , 2015 .

[10]  Jon Crowcroft,et al.  Honeycomb , 2004, Comput. Commun. Rev..

[11]  Louella Colaco,et al.  Real Time Intrusion Detection and Prevention System , 2014, FICTA.

[12]  Federica Pascucci,et al.  Improving Security in Industrial Internet of Things: A Distributed Intrusion Detection Methodology , 2019, Security and Privacy Trends in the Industrial Internet of Thing.

[13]  Jugal K. Kalita,et al.  Network Anomaly Detection: Methods, Systems and Tools , 2014, IEEE Communications Surveys & Tutorials.

[14]  Qian He,et al.  Smart grid monitoring for intrusion and fault detection with new locally optimum testing procedures , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[15]  Iqbal Gondal,et al.  Survey of intrusion detection systems: techniques, datasets and challenges , 2019, Cybersecurity.

[16]  Guanrong Chen,et al.  Stability analysis of controlled multiple-link robotic manipulator systems with time delays , 1998 .

[17]  Vangelis Metsis,et al.  Abnormal human behavioral pattern detection in assisted living environments , 2010, PETRA '10.

[18]  Chun-Hung Richard Lin,et al.  Intrusion detection system: A comprehensive review , 2013, J. Netw. Comput. Appl..

[19]  Ing-Ray Chen,et al.  A survey of intrusion detection techniques for cyber-physical systems , 2014, ACM Comput. Surv..

[20]  CasalePierluigi,et al.  Personalization and user verification in wearable systems using biometric walking patterns , 2012 .

[21]  Fritz Allhoff,et al.  Binary Bullets: The Ethics of Cyberwarfare , 2016 .

[22]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[23]  V. Y. Popov,et al.  Multiple genome rearrangement by swaps and by element duplications , 2007, Theor. Comput. Sci..

[24]  Jemal H. Abawajy,et al.  Using feature selection for intrusion detection system , 2012, 2012 International Symposium on Communications and Information Technologies (ISCIT).

[25]  Cristina Alcaraz.  Security and Privacy Trends in the Industrial Internet of Things , 2019, Advanced Sciences and Technologies for Security Applications.

[26]  R. Sekar,et al.  Experiences with Specification-Based Intrusion Detection , 2001, Recent Advances in Intrusion Detection.

[27]  Jeong Seop Sim,et al.  Approximate periods of strings , 2001, Theor. Comput. Sci..

[28]  Ing-Ray Chen,et al.  Behavior Rule Specification-Based Intrusion Detection for Safety Critical Medical Cyber Physical Systems , 2015, IEEE Transactions on Dependable and Secure Computing.