Talk: Manideep Mamindlapally (July 07, 2022 at 1:00 PM, LNT Seminar room N2408)
Talks |
Unconditionally secure commitment over unreliable noisy channels
Manideep Mamindlapally
Indian Institute of Technology Kharagpur
Zoom Meeting:
Link: https://tum-conf.zoom.us/j/63632016037?pwd=WjJBczN2RSs5TnJJRThCYnEvaGhhZz09
Abstract:
Commitment is a classic two-phase cryptographic protocol. Here a committer encrypts a string and sends it to the receiver in the commit phase. The string is then revealed in the reveal phase to the receiver; such a verifier then accepts the string only if it matches the original one. It is well known that noisy channels offer a valuable resource to realise unconditionally-secure or information- theoretically secure commitment. The statistics of noisy channels, however, may be imprecisely characterised. Such unreliable noisy channels have been of active interest to the cryptographic community. In this work we study a wide range of unreliable channels; find out the regimes of parameters over which commitment is possible. We present new results for commitment throughput, i.e., commitment capacity for several channels. compoundness and elasticity. Over discrete alphabet, we complete the study on elastic channels, reverse elastic channels, compound channels and unfair noisy channels. The results bring to the fore an the interplay between two forms of unreliability compoundness and elasticity. Motivated by the interesting trends that have come to light, we propose and study an even more generalised “assymetric unfair noisy channels” for a wider perspective. We initiate a study over unreliable continuous channels too, by proposing and investigating commitment over “Gaussian unfair noisy channels.”
Biography:
Manideep Mamindlapally is currently pursuing (bachelor and master) dual degree with the Indian Institute of Technology Kharagpur, Kharagpur, India. His broad interest lies in theoretical computer science. He is currently interested in information theory, quantum information theory, quantum computation, and computational complexity.