Biblio

As recently studied, network-on-chip (NoC) suffers growing threats from hardware trojans (HTs), leading to performance degradation or information leakage when it provides communication service in many/multi-core systems. Therefore, defense techniques against NoC HTs experience rapid development in recent years. However, to the best of our knowledge, there are few standard benchmarks developed for the defense techniques evaluation. To address this issue, in this paper, we design a suite of benchmarks which involves multiple NoCs with different HTs, so that researchers can compare various HT defense methods fairly by making use of them. We first briefly introduce the features of target NoC and its infected modules in our benchmarks, and then, detail the design of our NoC HTs in a one-by-one manner. Finally, we evaluate our benchmarks through extensive simulations and report the circuit cost of NoC HTs in terms of area and power consumption, as well as their effects on NoC performance. Besides, comprehensive experiments, including functional testing and side channel analysis are performed to assess the stealthiness of our HTs.

The Internet of Things (IoT) era envisions billions of interconnected devices capable of providing new interactions between the physical and digital worlds, offering new range of content and services. At the fundamental level, IoT nodes are physical devices that exist in the real world, consisting of networking, sensor, and processing components. Some application examples include mobile and pervasive computing or sensor nets, and require distributed device deployment that feed information into databases for exploitation. While the data can be centralized, there are advantages, such as system resiliency and security to adopting a decentralized architecture that pushes the computation and storage to the network edge and onto IoT devices. However, these devices tend to be much more limited in computation power than traditional racked servers. This research explores using the Cassandra distributed database on IoT-representative device specifications. Experiments conducted on both virtual machines and Raspberry Pi's to simulate IoT devices, examined latency issues with network compression, processing workloads, and various memory and node configurations in laboratory settings. We demonstrate that distributed databases are feasible on Raspberry Pi's as IoT representative devices and show findings that may help in application design.