Abstract:
Symmetric key block ciphers are employed for data encryption widely in everyday applications. Block ciphers are considered robust and secure even if their structure is known globally and immune to several cryptanalysis attacks including linear and differential cryptanalysis. Data retrieval should only be possible with the help of data encryption key. However, there may exist block ciphers whose structure is transparent, but may contain an inherent algebraic backdoor helping the designer to retrieve the data encryption key. Undiscoverable algebraic backdoors are hard to design because of the hidden mathematical structure employed to retrieve the key. Moreover, it is also interesting to explore statistical methods in order to determine an inherent mathematical backdoor. In this thesis, we explored various backdoor embedding methodologies previously, and have employed the recent LowMC-M framework to design a backdoored cipher. Furthermore, we applied the standard NIST statistical suite tests against the backdoored cipher and the standard AES to explore which statistical methods might help to determine the underlying backdoor cipher .
