Research On A Fast Chaos Encryption Algorithm Based On The Ambiguities Of Blind Source Separation For EEG Signal

With the development of ubiquitous computing and biomedical signal technology, ubiquitous applications based on bio-electrical signal analysis have been grown rapidly. This highlighted the importance of performing privacy protection on bio-electrical signal data. Since minis ize, wireless and pervasive are the main principles of ubiquitous computing, it requires the algorithms to be fast and low cost, while traditional cryptography techniques require massive computation to ensure their security, causing low computation speed and high memory cost, with is very against the requirement of ubiquitous computing. In this paper, by sacrificing the generality of the algorithm, using the unique feature of electroencephalograph (EEG) signal, we proposed and fast chaos masking method for EEG based on the ambiguous of Blind Source Separation, a hard problem in signal processing field. Secure analysis and simulation shows that the proposed algorithm is secure against all4classic attacks against block cipher, attacks against pseudorandom number generator, and attacks using signal processing methods. Further simulation to compare algorithm efficiency of the proposed method and3classic block ciphers, DES, AES and IDEA, shows the proposed method runs significantly faster than both of these algorithms. This paper shows that, by strictly limit the algorithm to work on a specific data type, there is a possibility of gaining both security and efficiency in designing cryptography. This can be a new thinking of how to design security applications for ubiquitous computing.