Hardware Intrinsic Security Threats in Internet of Things (IoTs)
Project (3): Hardware Intrinsic Security Threats in Internet of Things (IoTs)
Every year, more than 10 billion microcontrollers are manufactured, many of which are used in the smart devices. In the near future, even more devices around us will be smarter and connected to each other through the IoT. It is expected that 20 billion connected devices will be used worldwide by 2020. Many of the IoT devices are small in size, low in computation capabilities and powered by low capacity batteries. The amount of the information exchanged among IoT devices is very attractive to attackers, making them a target for cyber-attacks. The small size and low computation capability of battery-powered IoT devices make the traditional public key cryptography too expensive to be implemented. Although some efforts have been made in applying lightweight cryptography on IoT devices, they are not enough to protect the IoT networks from internal hardware Trojan (HT) based attacks. Because of the unique nature of HT, most of the traditional digital communication network vulnerability detection techniques cannot be used for HT-based IoT attacks. Hence, in this research, an REU participant will explore potential hardware intrinsic (HI) attack scenarios and their mitigation techniques.
Leveraging Network Traffic Modeling to Secure Home Area Network against Hardware Attacks. The smart home appliance (SHA) has been extensively deployed in millions of houses around the globe and connected to the internet. The recent threats due to HT in the integrated circuit (IC) has become a serious concern. REU participants will investigate a new approach to detect hardware Trojan based SHA in HAN by utilizing Hurst exponent value to model the network data traffic in real time. Students will explore how the network behavior changes due to HT of some of the well-known attacks on the HAN, namely, ARQ, DoS, power depletion, and impersonation attacks. Experimental verification using our in-house testbed  will be conducted against different attack scenarios.
Qualifications: Matlab, c/c++, microcontroller programming, EE, CmpE or CmpSci major, knowledge of encryption.
Mentor: Dr. Hasan (email@example.com)