Detecting Dynamic Security Threats in Multi-Component IoT Systems

Abstract

The rising ubiquity of the Internet of Things (IoT) has heralded a new era of increasingly prolific and damaging IoT-centric security threat vectors. Fastpaced market demand for multi-featured IoT products urge companies, and their software engineers, to bring products to market quickly, often at the cost of security. Lack of proper security threat analysis tooling during development, testing, and release cycles exacerbate security concerns. In this paper, we augment a security threat analysis tool to use audit hooks, open-source information capture components, and machine learning techniques to profile dynamic wearable and IoT operations spanning multiple components during execution. Our tool encourages data-drive threat identification and analysis approaches that can help software engineers perform dynamic testing and threat analysis to mitigate codelevel vulnerabilities that lead to attacks in IoT applications. Our approach is evaluated by means of a case study involving a system evaluation across several common attack vectors.

Bridging Internet of Things and Wireless Sensor Networks: Applications and Challenges

“…Due to ease of deployment, selfconfigurability, untended operation, and fault tolerance, sensor networks will play more important roles in future military C3I (Command, Control, Communications and Intelligence) systems and make future wars more intelligent with less human involvement. Sensors can be mounted on unmanned vehicles, tanks, fighter planes, submarines, missiles, or torpedoes to guide them around obstacles to their targets and lead them to coordinate with one another to accomplish more effective attacks or defences (Balaji et al, 2018;Shrestha & Hale, 2019).…”