International Conference on Artificial Intelligence, Robotics & IoT
City University of New York, USA
Title: Artifi cial Immune System Based Approach to Cyber Attack Detection
Biography: Tarek Saadawi
Cyber Attacks have been increaing at an alraming rate. For example, the attack on DYN compnay on October, 2016 have resulted in the cutoff of Internet services in the North East of the USA. The Dyn company is an organization that controls many of the Domain Name Servers that service American domains. This widely successful attack utilized the now infamous Mirai – a nasty piece of malware that powers an extensive botnet largely populated by Internet of Things (IoT) devices. Advancements in Internet of Things (IoT), wireless, advanced robotics, intelligent agents, cloud computing and other technologies, as well as reliance on 3rd party commercial-off-the-shelf software, will also increase the cyber-attack surface in systems and networks.
Given the ability of the human immune system to detect all infections and how the human body can be related to the complex network of interconnected systems that exist today, our proposal takes a biological approach to solving the network intrusion detection problem. Our proposed bio-inspired system for network intrusion detection makes use of the models that exist in immunology which has been abstracted to an area under artificial intelligence known as artificial immune system (AIS). The proposed system will be a combination of the immunology-developed theory of self-nonself (SNS), and danger theory (DT). The proposed system stems from our successful application of SNS and DT respectively to the detection of cyber attacks that originate from external networks. Our proposed system will be detecting cyber-attacks that originate from both inside and outside a communication network.