Artificial intelligence in the cyber domain: Offense and defense

Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Lymph node inspired computing: towards immune system inspired human-engineered complex systems

The immune system is a distributed decentralized system that functions without any centralized control. The immune system has millions of cells that function somewhat independently and can detect and respond to pathogens with considerable speed and efficiency. Lymph nodes are physical anatomical structures that allow the immune system to rapidly detect pathogens and mobilize cells to respond to it. Lymph nodes function as: 1) information processing centres, and 2) a distributed detection and response network. We introduce biologically inspired computing that uses lymph nodes as inspiration. We outline applications to diverse domains like mobile robots, distributed computing clusters, peer-to-peer networks and online social networks. We argue that lymph node inspired computing systems provide powerful metaphors for distributed computing and complement existing artificial immune systems. We view our work as a first step towards holistic simulations of the immune system that would capture all the complexities and the power of a complex adaptive system like the immune system. Ultimately this would lead to immune system inspired computing that captures all the complexities and power of the immune system in human-engineered complex systems