Symmetric Cryptanalysis Via Higher Order Vectorial Derivatives.
Funded by SERB (INR 6.6 Lakhs)
Dhiman Saha | Project Investigator |
Sahiba Suryawanshi | PhD Student, IIT Bhilai |
Shibam Ghosh | PhD Student, University of Haifa |
Prathamesh Ram | Dual Degree Student, IIT Bhilai |
Theoretical cryptanalysis has always leveraged non-randomness as one of the primary indicators of underlying weakness of a cryptographic primitive. In this regard symmetry has always been a cheap source of non-randomness and a property that is foremost on the list of properties to be eliminated by any cryptosystem designer. In \fse 2017~\cite{DBLP:journals/tosc/SahaKC17} and later in \afc 2020~\cite{DBLP:conf/africacrypt/SuryawanshiSS20}, it was shown how internal symmetry (alternatively, the \emph{translation invariance} property) of some sub-functions of \sha~\cite{sha3} (the latest cryptographic hash function standard) can be linked to its algebraic degree. And the same property was used to devise the \emph{most effective} distinguishers on \sha. The primary idea was to compute higher order vectorial derivatives (Refer Definition~
This project attempts to investigate new properties of higher order boolean derivatives to detect non-randomness in cryptographic hash functions. The primary targets are international hash standard \sha and \nist Lightweight Cryptography competition finalist \xood~\cite{DBLP:journals/tosc/DaemenHPAK20}. The basic idea is to improve the limitations of \sym distinguisher.