In this paper we propose ROS-Defender, a holistic approach to secure robotics systems, which integrates a Security Event Management System (SIEM), an intrusion prevention system (IPS) and a firewall for a robotic system. ROS-Defender combines anomaly detection systems at application (ROS) level and network level, with dynamic policy enforcement points using software defined networking (SDN) to provide protection against a large class of attacks. Although SIEMs, IPS, and firewall have been previously used to secure computer networks, ROS-Defender is applying them for the specific use case of robotic systems, where security is in many cases an afterthought.

Abstract. The current underutilization of IPv6 enabled services makes accesses to them very attractive because of higher availability and better response time, like the IPv6 specific services from Google and Youtube have recently got a lot of requests. In this paper, we describe a fuzzing framework for IPv6 protocols. Fuzzing is a process by which faults are injected in order to find vulnerabilities in implementations. Our paper describes a machine learning approach, that leverages reinforcement based fuzzing method. We describe a reinforcement learning algorithm to allow the framework to autonomically learn the best fuzzing mechanisms and to automatically test stability and reliability of IPv6.

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