An enhanced Blowfish Algorithm based on cylindrical coordinate system and dynamic permutation box

The Blowfish Algorithm (BA) is a symmetric block cipher that uses Feistel network to iterate simple encryption and decryption functions. BA key varies from 32 to 448 bits to ensure a high level of security. However, the substitution box (S-Box) in BA occupies a high percentage of memory and has problems in security, specifically in randomness of output with text and image files that have large strings of identical bytes. Thus, the objective of this research is to enhance the BA to overcome these problems. The research involved three phases, algorithm design, implementation, and evaluation. In the design phase, a dynamic 3D S-Box, a dynamic permutation box (P-Box), and a Feistal Function (F-Function) were improved. The improvement involved integrating Cylindrical Coordinate System (CCS) and dynamic P-Box. The enhanced BA is known as Ramlan Ashwak Faudziah (RAF) algorithm. The implementation phase involved performing key expansion, data encryption, and data decryption. The evaluation phase involved measuring the algorithm in terms of memory and security. In terms of memory, the results showed that the RAF occupied 256 bytes, which is less than the BA (4096 bytes). In terms of randomness of text and image files that have large strings of identical bytes, the average rate of randomness for 188 statistical tests obtained values of more than 96%. This means that the RAF has high randomness indicating that it is more secured. Thus, the results showed that the RAF algorithm that integrates the CCS and dynamic P-Box serves as an effective approach that can consume less memory and strengthen security

Memory Carving in Embedded Devices: Separate the Wheat from the Chaff

International audienceThis paper investigates memory carving techniques for embedded devices. Given that cryptographic material in memory dumps makes carving techniques inefficient, we introduce a methodology to distinguish meaningful information from cryptographic material in smallsized memory dumps. The proposed methodology uses an adaptive boosting technique with statistical tests. Experimented on EMV cards, the methodology recognized 92% of meaningful information and 98% of cryptographic material

New Statistical Randomness Tests Based on Length of Runs

Random sequences and random numbers constitute a necessary part of cryptography. Many cryptographic protocols depend on random values. Randomness is measured by statistical tests and hence security evaluation of a cryptographic algorithm deeply depends on statistical randomness tests. In this work we focus on statistical distributions of runs of lengths one, two, and three. Using these distributions we state three new statistical randomness tests. New tests use χ2 distribution and, therefore, exact values of probabilities are needed. Probabilities associated runs of lengths one, two, and three are stated. Corresponding probabilities are divided into five subintervals of equal probabilities. Accordingly, three new statistical tests are defined and pseudocodes for these new statistical tests are given. New statistical tests are designed to detect the deviations in the number of runs of various lengths from a random sequence. Together with some other statistical tests, we analyse our tests’ results on outputs of well-known encryption algorithms and on binary expansions of e, π, and 2. Experimental results show the performance and sensitivity of our tests

Evaluation of Randomness Test Results for Short Sequences

Randomness testing of cryptographic algorithms are of crucial importance to both designer and the attacker. When block ciphers and hash functions are considered, the sequences subject to randomness testing are of at most 512-bit length, "short sequences". As it is widely known, NIST has a statistical test suite to analyze the randomness properties of sequences and generators. However, some tests in this suite can not be applied to short sequences and most of the remaining ones do not produce reliable test values for the sequences in question. Consequently, the analysis method which is proposed in this suite is not suitable for evaluation of generators which produce relatively short sequences. In this work, we propose an alternative approach to analyze short sequences without tweaking the tests