Himanshu Thapliyal
Southern Methodist University, TX·Engineering·Early-career
Small Internet-of-Things (IoT) devices, such as wireless sensors and mobile gadgets, must run on very little power and still keep data secret. One threat is the side-channel attack.
- Fields
Engineering
Computer Science
- Topics
hardware security
energy recovery computing
adiabatic logic
- Grants
- 1 known grant, through Aug 2027
What they work on
- Investigate how secret information leaks through the power traces of energy recovery circuits, and propose design methods that reduce leakage against differential power analysis attacks.
- Develop a low-energy, DPA-resistant energy recovery standard cell library and a semi-custom design flow for building lightweight block-cipher encryption circuits.
- Design power clock generation and distribution for energy recovery circuits and fabricate silicon prototypes to measure the energy use and attack resistance of the encryption circuits.
More about the research
Here an attacker records how much power a chip draws while it encrypts data and uses those traces to work out secret keys. A common form is differential power analysis (DPA), which compares many power traces statistically. This project uses energy recovery (ER) computing to address both problems at once. ER circuits recycle electrical charge instead of discarding it, which lowers energy use. They may also produce power traces that reveal less about the computation.
Why it matters
The project could make IoT devices both lower-power and harder to hack through power-analysis attacks. This matters for battery-limited sensors and mobile devices that handle private data. The results are intended to make the case for chip designers in industry to adopt energy recovery circuits in secure, low-energy hardware.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Vanessa Chen
Carnegie Mellon University, PA·Engineering·Early-career
Design bio-inspired, time-domain analog classifiers that exploit transistor mismatch and nonlinearity to perform energy-efficient hierarchical classification at low supply voltages within a sensor.
Aatmesh Shrivastava
Northeastern University, MA·Engineering·Early-career
Develop a distributed beamforming technique that combines RF energy from multiple Wi-Fi or Bluetooth-type transmitters and directs it to a remote IoT receiver, using closed-loop optimization between transmitters and receiver.
Ruzica Piskac
Yale University, CT·Computer Science
Automatically locate power and electromagnetic side-channel vulnerabilities in low-level code by combining dynamic taint tracking and random testing with symbolic execution, satisfiability modulo theories solving and model counting.
The school
Southern Methodist University: 7 labs on PI Pages, $63M a year on research, 136 research doctorates a year.
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