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K, S. K., Sahoo, S., Mahapatra, A., Swain, A. K., Mahapatra, K. K..  2017.  Analysis of Side-Channel Attack AES Hardware Trojan Benchmarks against Countermeasures. 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). :574–579.

Hardware Trojan (HT) is one of the well known hardware security issue in research community in last one decade. HT research is mainly focused on HT detection, HT defense and designing novel HT's. HT's are inserted by an adversary for leaking secret data, denial of service attacks etc. Trojan benchmark circuits for processors, cryptography and communication protocols from Trust-hub are widely used in HT research. And power analysis based side channel attacks and designing countermeasures against side channel attacks is a well established research area. Trust-Hub provides a power based side-channel attack promoting Advanced Encryption Standard (AES) HT benchmarks for research. In this work, we analyze the strength of AES HT benchmarks in the presence well known side-channel attack countermeasures. Masking, Random delay insertion and tweaking the operating frequency of clock used in sensitive operations are applied on AES benchmarks. Simulation and power profiling studies confirm that side-channel promoting HT benchmarks are resilient against these selected countermeasures and even in the presence of these countermeasures; an adversary can get the sensitive data by triggering the HT.

Kumar, K. S., Rao, G. H., Sahoo, S., Mahapatra, K. K..  2015.  A Novel PUF Based SST to Prevent Distribution of Rejected ICs from Untrusted Assembly. 2015 IEEE International Symposium on Nanoelectronic and Information Systems. :314–319.

Globalization of semiconductor design, manufacturing, packaging and testing has led to several security issues like over production of chips, shipping of faulty or partially functional chips, intellectual property infringement, cloning, counterfeit chips and insertion of hardware trojans in design house or at foundry etc. Adversaries will extract chips from obsolete PCB's and release used parts as new chips into the supply chain. The faulty chips or partially functioning chips can enter supply chain from untrusted Assembly Packaging and Test (APT) centers. These counterfeit parts are not reliable and cause catastrophic consequences in critical applications. To mitigate the counterfeits entering supply chain, to protect the Intellectual Property (IP) rights of owners and to meter the chip, Secure Split Test (SST) is a promising solution. CSST (Connecticut SST) is an improvement to SST, which simplifies the communication required between ATP center and design house. CSST addresses the scan tests, but it does not address the functional testing of chips. The functional testing of chips during production testing is critical in weeding out faulty chips in recent times. In this paper, we present a method called PUF-SST (Physical Unclonable Function – SST) to perform both scan tests and functional tests without compromising on security features described in CSST.

Majhi, D., Rao, M., Sahoo, S., Dash, S. P., Mohapatra, D. P..  2020.  Modified Grey Wolf Optimization(GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry. 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA). :1–4.
The occurrences of accidents in mining industries owing to the fragile health conditions of mine workers are reportedly increasing. Health conditions measured as heart rate or pulse, glycemic index, and blood pressure are often crucial parameters that lead to failure in proper reasoning when not within acceptable ranges. These parameters, such as heartbeat rate can be measured continuously using sensors. The data can be monitored remotely and, when found to be of concern, can send necessary alarms to the mine manager. The early alarm notification enables the mine manager with better preparedness for managing the reach of first aid to the accident spot and thereby reduce mine fatalities drastically. This paper presents a framework for deterring accidents in mines with the help of the Grey Wolf Optimization approach.