The application of $σ$-LFSR in Key-Dependent Feedback Configuration for Word-Oriented Stream Ciphers
This work addresses security enhancements for stream ciphers, but it is incremental as it builds on existing σ-LFSR and SNOW 2.0 frameworks.
The paper tackles the problem of generating key-dependent feedback configurations for σ-LFSRs in word-oriented stream ciphers, proposing a method that uses the secret key and initialization vector to create configurations, with analysis showing improved resistance to attacks when applied to SNOW 2.0.
In this paper, we propose and evaluate a method for generating key-dependent feedback configurations (KDFC) for $σ$-LFSRs. $σ$-LFSRs with such configurations can be applied to any stream cipher that uses a word-based LFSR. Here, a configuration generation algorithm uses the secret key(K) and the initialization vector (IV) to generate a feedback configuration. We have mathematically analysed the feedback configurations generated by this method. As a test case, we have applied this method on SNOW 2.0 and have studied its impact on resistance to various attacks. Further, we have also tested the generated keystream for randomness and have briefly described its implementation and the challenges involved in the same.