Quarterly journal published in SPbPU
and edited by prof. Peter Zegzhda
Peter the Great St. Petersburg Polytechnic University
Institute of computer sciences and technologies
information security of computer systems
Information Security Problems. Computer Systems
Published since 1999.
ISSN 2071-8217

A. V. Kozachok, V. I. Kozachok, A. A. Spirin
Russian Federation Security Guard Service Federal Academy

Annotation: Since 2010 there is an increase in leaks of confidential information due to the fault of an internal violator, despite the availability of a wide range of means for detecting and preventing information leaks. One of the possible channels leakage is transmission of information in encrypted form, since existing leak detection tools use signature methods of data classification. The article presents an algorithm for detecting encrypted data based on a statistical model of pseudorandom sequences. The proposed algorithm allows classifying encrypted and compressed data with an accuracy of 0.97.
Keywords: Data Analysis, Classification of Encrypted and Compressed Data, Machine Learning, Binary Data Analysis, Pseudorandom Sequences
Pages 16-26