366 research outputs found
Cryptanalysis of an image encryption scheme based on the Hill cipher
This paper studies the security of an image encryption scheme based on the
Hill cipher and reports its following problems: 1) there is a simple necessary
and sufficient condition that makes a number of secret keys invalid; 2) it is
insensitive to the change of the secret key; 3) it is insensitive to the change
of the plain-image; 4) it can be broken with only one known/chosen-plaintext;
5) it has some other minor defects.Comment: 10 pages, three figure
Cryptanalysis of an Encryption Scheme Based on Blind Source Separation
Recently Lin et al. proposed a method of using the underdetermined BSS (blind
source separation) problem to realize image and speech encryption. In this
paper, we give a cryptanalysis of this BSS-based encryption and point out that
it is not secure against known/chosen-plaintext attack and chosen-ciphertext
attack. In addition, there exist some other security defects: low sensitivity
to part of the key and the plaintext, a ciphertext-only differential attack,
divide-and-conquer (DAC) attack on part of the key. We also discuss the role of
BSS in Lin et al.'s efforts towards cryptographically secure ciphers.Comment: 8 pages, 10 figures, IEEE forma
Distinguishing Lightweight Block Ciphers in Encrypted Images
Modern day lightweight block ciphers provide powerful encryption methods for securing IoT communication data. Tiny digital devices exchange private data which the individual users might not be willing to get disclosed. On the other hand, the adversaries try their level best to capture this private data. The first step towards this is to identify the encryption scheme. This work is an effort to construct a distinguisher to identify the cipher used in encrypting the traffic data. We try to establish a deep learning based method to identify the encryption scheme used from a set of three lightweight block ciphers viz. LBlock, PRESENT and SPECK. We make use of images from MNIST and fashion MNIST data sets for establishing the cryptographic distinguisher. Our results show that the overall classification accuracy depends firstly on the type of key used in encryption and secondly on how frequently the pixel values change in original input image
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