95 research outputs found
A New Cryptanalytic Method Using the Distribution Characteristics of Substitution Distances
In this paper, we suggest a new method for cryptanalysis of the basic structures of the block ciphers having SP network structure. The concept of the substitution difference is introduced and the distribution characteristics of substitution distances in an S-box is developed. This gives clues for cryptanalysis of the cipher. We then examine if this method is applicable to cryptanalysis of Rijndael. We present the method for cryptanalysis of the first round of Rijndael including the initial Round-Key addition part in order to illustrate our new method
Genetic algorithms in cryptography
Genetic algorithms (GAs) are a class of optimization algorithms. GAs attempt to solve problems through modeling a simplified version of genetic processes. There are many problems for which a GA approach is useful. It is, however, undetermined if cryptanalysis is such a problem. Therefore, this work explores the use of GAs in cryptography. Both traditional cryptanalysis and GA-based methods are implemented in software. The results are then compared using the metrics of elapsed time and percentage of successful decryptions. A determination is made for each cipher under consideration as to the validity of the GA-based approaches found in the literature. In general, these GA-based approaches are typical of the field. Of the genetic algorithm attacks found in the literature, totaling twelve, seven were re-implemented. Of these seven, only three achieved any success. The successful attacks were those on the transposition and permutation ciphers by Matthews [20], Clark [4], and Griindlingh and Van Vuuren [13], respectively. These attacks were further investigated in an attempt to improve or extend their success. Unfortunately, this attempt was unsuccessful, as was the attempt to apply the Clark [4] attack to the monoalphabetic substitution cipher and achieve the same or indeed any level of success. Overall, the standard fitness equation genetic algorithm approach, and the scoreboard variant thereof, are not worth the extra effort involved. Traditional cryptanalysis methods are more successful, and easier to implement. While a traditional method takes more time, a faster unsuccessful attack is worthless. The failure of the genetic algorithm approach indicates that supplementary research into traditional cryptanalysis methods may be more useful and valuable than additional modification of GA-based approaches
Cryptography: Against AI and QAI Odds
Artificial Intelligence (AI) presents prodigious technological prospects for
development, however, all that glitters is not gold! The cyber-world faces the
worst nightmare with the advent of AI and quantum computers. Together with
Quantum Artificial Intelligence (QAI), they pose a catastrophic threat to
modern cryptography. It would also increase the capability of cryptanalysts
manifold, with its built-in persistent and extensive predictive intelligence.
This prediction ability incapacitates the constrained message space in device
cryptography. With the comparison of these assumptions and the intercepted
ciphertext, the code-cracking process will considerably accelerate. Before the
vigorous and robust developments in AI, we have never faced and never had to
prepare for such a plaintext-originating attack. The supremacy of AI can be
challenged by creating ciphertexts that would give the AI attacker erroneous
responses stymied by randomness and misdirect them. AI threat is deterred by
deviating from the conventional use of small, known-size keys and
pattern-loaded ciphers. The strategy is vested in implementing larger secret
size keys, supplemented by ad-hoc unilateral randomness of unbound limitations
and a pattern-devoid technique. The very large key size can be handled with low
processing and computational burden to achieve desired unicity distances. The
strategy against AI odds is feasible by implementing non-algorithmic
randomness, large and inexpensive memory chips, and wide-area communication
networks. The strength of AI, i.e., randomness and pattern detection can be
used to generate highly optimized ciphers and algorithms. These pattern-devoid,
randomness-rich ciphers also provide a timely and plausible solution for NIST's
proactive approach toward the quantum challenge
Algorithm 959: VBF: A Library of C plus plus Classes for Vector Boolean Functions in Cryptography
VBF is a collection of C++ classes designed for analyzing vector Boolean functions (functions that map a Boolean vector to another Boolean vector) from a cryptographic perspective. This implementation uses the NTL library from Victor Shoup, adding new modules that call NTL functions and complement the existing ones, making it better suited to cryptography. The class representing a vector Boolean function can be initialized by several alternative types of data structures such as Truth Table, Trace Representation, and Algebraic Normal Form (ANF), among others. The most relevant cryptographic criteria for both block and stream ciphers as well as for hash functions can be evaluated with VBF: it obtains the nonlinearity, linearity distance, algebraic degree, linear structures, and frequency distribution of the absolute values of the Walsh Spectrum or the Autocorrelation Spectrum, among others. In addition, operations such as equality testing, composition, inversion, sum, direct sum, bricklayering (parallel application of vector Boolean functions as employed in Rijndael cipher), and adding coordinate functions of two vector Boolean functions are presented. Finally, three real applications of the library are described: the first one analyzes the KASUMI block cipher, the second one analyzes the Mini-AES cipher, and the third one finds Boolean functions with very high nonlinearity, a key property for robustness against linear attacks
FM 11-35, Signal Corps Intelligence, 1942
This manual describes the intelligence activities of the Signal Corps. At that time, the Signal Corps was a bureau within the Headquarters, Department of the Army, as well as a branch of the Army to which soldiers were commissioned and assigned. The Signal Corps developed and supplied the army with signal and photographic equipment, trained personnel and units for service with the forces in the field, provided the army with communications and photographic services, and provided communications, signal, and technical intelligence. This manual describes the intelligence responsibilities and functions of the Signal Corps and the role of signal intelligence units with forces in the field.
Chapter 2 (Pages 4-25) describes the activities of the Signal Intelligence Service, the predecessor of the post-war Army Security Agency and the National Security Agency
Evolution of an Emerging Symmetric Quantum Cryptographic Algorithm
With the rapid evolution of data exchange in network environments,
information security has been the most important process for data storage and
communication. In order to provide such information security, the
confidentiality, data integrity, and data origin authentication must be
verified based on cryptographic encryption algorithms. This paper presents a
new emerging trend of modern symmetric encryption algorithm by development of
the advanced encryption standard (AES) algorithm. The new development focuses
on the integration between Quantum Key Distribution (QKD) and an enhanced
version of AES. A new quantum symmetric encryption algorithm, which is
abbreviated as Quantum-AES (QAES), is the output of such integration. QAES
depends on generation of dynamic quantum S-Boxes (DQS-Boxes) based quantum
cipher key, instead of the ordinary used static S-Boxes. Furthermore, QAES
exploits the specific selected secret key generated from the QKD cipher using
two different modes (online and off-line)
Systematically Quantifying Cryptanalytic Non-Linearities in Strong PUFs
Physically Unclonable Functions~(PUFs) with large challenge space~(also called Strong PUFs) are promoted for usage in authentications and various other cryptographic and security applications. In order to qualify for these cryptographic applications, the Boolean functions realized by PUFs need to possess a high non-linearity~(NL). However, with a large challenge space~(usually bits), measuring NL by classical techniques like Walsh transformation is computationally infeasible. In this paper, we propose the usage of a heuristic-based measure called non-homomorphicity test which estimates the NL of Boolean functions with high accuracy in spite of not needing access to the entire challenge-response set. We also combine our analysis with a technique used in linear cryptanalysis, called Piling-up lemma, to measure the NL of popular PUF compositions. As a demonstration to justify the soundness of the metric, we perform extensive experimentation by first estimating the NL of constituent Arbiter/Bistable Ring PUFs using the non-homomorphicity test, and then applying them to quantify the same for their XOR compositions namely XOR Arbiter PUFs and XOR Bistable Ring PUF. Our findings show that the metric explains the impact of various parameter choices of these PUF compositions on the NL obtained and thus promises to be used as an important objective criterion for future efforts to evaluate PUF designs. While the framework is not representative of the machine learning robustness of PUFs, it can be a useful complementary tool to analyze the cryptanalytic strengths of PUF primitives
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