Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2020

Идентификатор DOI: 10.3103/S0146411620050077

Ключевые слова: binary classification, clonal selection, haar wavelet-transform, jpeg, negative selection, steganalysis

Аннотация: Abstract: This work aims to develop the heuristic steganalysis method of static JPEG images, based on the usage of artificial immune systems that allows detecting the presence of hidden information in them with good results on image processing time. A formal description of the artificial immune system’s primary nodes and an analysis of the obtained experimental results are presented. The proposed method allows detecting the presence of hidden information embedded by various popular steganography tools (like OutGuess, Steghide, and F5) in static JPEG images with sufficiently high accuracy. © 2020, Allerton Press, Inc.

Журнал: Automatic Control and Computer Sciences

Выпуск журнала: Vol. 54, Is. 5

Номера страниц: 423-431

ISSN журнала: 01464116

Издатель: Pleiades journals

• Shniperov A.N. (Siberian Fed Univ, Dept Appl Math & Comp Secur, Krasnoyarsk 660041, Russia)
• Prokofieva A.V. (Siberian Fed Univ, Dept Appl Math & Comp Secur, Krasnoyarsk 660041, Russia)

• Scopus
• Web of Science Core Collection
• Ядро РИНЦ (eLIBRARY.RU)