Visible to the public Biblio

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2020-07-16
Cronin, Patrick, Gouert, Charles, Mouris, Dimitris, Tsoutsos, Nektarios Georgios, Yang, Chengmo.  2019.  Covert Data Exfiltration Using Light and Power Channels. 2019 IEEE 37th International Conference on Computer Design (ICCD). :301—304.

As the Internet of Things (IoT) continues to expand into every facet of our daily lives, security researchers have warned of its myriad security risks. While denial-of-service attacks and privacy violations have been at the forefront of research, covert channel communications remain an important concern. Utilizing a Bluetooth controlled light bulb, we demonstrate three separate covert channels, consisting of current utilization, luminosity and hue. To study the effectiveness of these channels, we implement exfiltration attacks using standard off-the-shelf smart bulbs and RGB LEDs at ranges of up to 160 feet. We analyze the identified channels for throughput, generality and stealthiness, and report transmission speeds of up to 832 bps.

2017-12-12
Hosseini, Fateme S., Fotouhi, Pouya, Yang, Chengmo, Gao, Guang R..  2017.  Leveraging Compiler Optimizations to Reduce Runtime Fault Recovery Overhead. Proceedings of the 54th Annual Design Automation Conference 2017. :20:1–20:6.

Smaller feature size, lower supply voltage, and faster clock rates have made modern computer systems more susceptible to faults. Although previous fault tolerance techniques usually target a relatively low fault rate and consider error recovery less critical, with the advent of higher fault rates, recovery overhead is no longer negligible. In this paper, we propose a scheme that leverages and revises a set of compiler optimizations to design, for each application hotspot, a smart recovery plan that identifies the minimal set of instructions to be re-executed in different fault scenarios. Such fault scenario and recovery plan information is efficiently delivered to the processor for runtime fault recovery. The proposed optimizations are implemented in LLVM and GEM5. The results show that the proposed scheme can significantly reduce runtime recovery overhead by 72%.