The possibility of detection of steganography in digital images based on the classification of stegocontainers is investigated. The obtained results demonstrate the effectiveness of using deep neural networks for solving this problem. The LSB method can be detected using EfficientNet b3 architecture. The achieved classification accuracy is above 97%. Using of steganography methods in frequency domain can be effectively detected by classifying their representation in the form of a digital YCrBr model, with augmentation (vertical and horizontal rotations). The classification accuracy is above 77%.

Keywords: Steganography, stegocontainer, machine learning, classification, digital image, deep learning, CNN, EfficientNet b3, confidentiality, information protection

An approach for cosntruction of stream ciphers based on new type of cipher gamma generators with a non-linear (fuzzy) shift register selection function is proposed. The best configuration of generator is selected for generating a gamma whose properties are closest to white noise. It is shown that the proposed approach makes it possible to generate a gamma sequence with a quality that exceeds a number of other classical generators.

Keywords: cryptography, stream cipher, gamma, PNSG, random test, fuzzy logic,membership function, linguistic variable, defuzzification, linear feedback shift register

We describe the process and results of reverse analysis of malware Raccoon Stealer v.1.7.3. We describe instruments of analysis, the process of code analysis, unpacking, getting of original code. We describe the process of code analysis, construction of malware working algorithm. We describe recomendations for defense from Raccoon Stealer.

Keywords: Reverse analysis, reverse engineering, malware, code analysis, debuger, disassembler, hex redactor, database, browser, information security