Security Of Cryptosystem Research Articles

Single Trace Analysis of Visible vs. Invisible Leakage for Comparison-Operation-Based CDT Sampling

The emergence of quantum computers poses a significant threat to the security of conventional public-key cryptosystems, driving the demand for quantum-resistant cryptographic solutions. In response, the National Institute of Standards and Technology (NIST) conducted a multi-year competition, ultimately selecting four ciphers. Among these, Falcon employs cumulative distribution table (CDT) sampling, which produces arrays of random values derived from a discrete Gaussian distribution during the signature generation phase. This array is then used with secret key information, forming the core of Falcon. Enhanced variants of Falcon, such as Mitaka, SOLMAE, and Antrag, implemented CDT sampling using comparison operations. Previous research by Choi et al. proposed a single trace analysis and countermeasure for CDT sampling, which exploited a non-constant-time vulnerability in 8-bit AVR microcontrollers. However, this vulnerability is specific to certain environments, and a potential vulnerability in comparison-operation-based constant-time CDT sampling remains unstudied. This paper is an extension of that study. This paper investigates the constant-time operation of comparison-operation-based CDT sampling on Arm Cortex-M4-based chips and proposes a deep learning-based side-channel analysis to recover the sampling values using a novel vulnerability. The proposed model achieves an F1 score of 1.0 and a recovery success rate of 99.97%.

The Uber-Knowledge Assumption: A Bridge to the AGM

The generic-group model (GGM) and the algebraic-group model (AGM) have been exceptionally successful in proving the security of many classical and modern cryptosystems. These models, however, come with standard-model uninstantiability results, raising the question of whether the schemes analyzed under them can be based on firmer standard-model footing. We formulate the uber-knowledge (UK) assumption, a standard-model assumption that naturally extends the uber-assumption family to knowledge-type problems. We justify the soundness of UK in both the bilinear GGM and the bilinear AGM. Along the way we extend these models to account for hashing into groups, an adversarial capability that is available in many concrete groups—In contrast to standard assumptions, hashing may affect the validity of knowledge assumptions. These results, in turn, enable a modular approach to security in the GGM and the AGM. As example applications, we use the UK assumption to prove knowledge soundness of Groth's zero-knowledge SNARK (EUROCRYPT 2016) and of KZG polynomial commitments (ASIACRYPT 2010) in the standard model, where for the former we reuse the existing proof in the AGM without hashing.

Design of Protection Software Using Some Cryptosystems for Cloud Database Files

The security of cloud databases may be a basic concern for organizations as they store and manage expansive volumes of delicate information within the cloud. Cryptosystems played an essential part in securing information privacy and integrity in these situations. This paper gives an in-depth investigation of the utilization of cryptosystems for cloud database security. The paper starts by talking about the foundation and importance of cloud database security, highlighting the expanding requirement for strong information security measures. A comprehensive study reviewed and investigated the current state of research in this space, distinguishing key progressions and challenges. The paper at that point digs into the execution of cryptosystems in cloud databases, looking at their execution and trade-offs. Besides, rising patterns and advances for improving cloud database security, such as multi-factor confirmation, homomorphic encryption, and blockchain, are discussed. The paper moreover recognizes different inquiries about openings and future headings within the field, counting various encryption methods, execution optimization, key administration, convenience enhancements, compliance contemplations, and integration with rising advances. Furthermore, we proposed encryption software for file protection, the software designed based on symmetric and asymmetric cryptosystems. The proposed software can be adapted for file protection in cloud database security. In conclusion, the paper emphasizes the significance of cryptosystems for cloud database security and underscores the requirement for continuous inquiry about and collaboration to address challenges and drive development in this zone.

An efficient secure cryptosystem using improved identity based encryption with multimodal biometric authentication and authorization in cloud environments

An efficient secure cryptosystem using improved identity based encryption with multimodal biometric authentication and authorization in cloud environments

PSDCLS: Parallel simultaneous diffusion–confusion image cryptosystem based on Latin square

Today, due to the unparalleled growth of multimedia data sharing, especially digital images, between users over insecure channels in real-time applications, cryptography algorithms have gained increasing attention for the secure and efficient transmission. In classical chaos-based image cryptosystems, the confusion and diffusion operations are often applied as two separate and independent phases, which threatens the cryptosystem security. To address these problems, in this paper, a fast image cryptosystem based on parallel simultaneous diffusion–confusion strategy has been proposed using Latin squares, called PSDCLS. It consists of three main steps. First, the initial parameters of the Hénon-Sine chaotic map are produced from SHA256 of both the plain image content and the user’s secret key. Second, a chaos-based random Latin square is constructed by employing the chaotic sequence produced through the Hénon-Sine chaotic map. Third, a parallel simultaneous diffusion–confusion scheme is proposed by using Latin square and vectorization technique to overcome the problems of computational complexity and high risk of separable and iterative confusion–diffusion operations in the classical chaos-based image cryptosystems. To analyze and evaluate the security and performance of PSDCLS cryptosystem, we conducted extensive simulations and experiments on various benchmark images. Experimental results and analyses show that PSDCLS achieves excellent scores for information entropy (>7.99), correlation coefficients close to 0, key space (2512), NPCR (>99.60%), UACI (>33.46%). The encryption time for test images of size 512 × 512 and 512×512×3 was around 0.026 and 0.081 s, respectively. Therefore, PSDCLS is highly robust against common cryptographic attacks and serves as a swift cryptosystem for real-time encryption applications. The source code of PSDCLS is accessible at: https://github.com/EbrahimZarei64/PSDCLS.

Attack on optical cryptosystems by skip connection networks

Optical encryption methods, due to their efficient operation speed and parallel processing capabilities, hold significant importance in securing multidimensional and large-volume data. Enhancing the security of optical cryptosystems from the perspective of cryptanalysis holds significant importance currently. Presently, attack methods against optical encryption are complex, and the effectiveness of these attacks is insufficient. Security analysis solutions face limitations in both breadth and depth. Therefore, this paper proposes an attack on optical cryptosystems based on a skip connection network, demonstrating the susceptibility of optical cryptosystems to attacks based on neural network algorithms. The network model is trained on plaintext-ciphertext pairs, fitting equivalent keys without various additional conditions. It approximates plaintext information in high-dimensional space, directly obtaining corresponding plaintext through ciphertext information, expanding the applicability and enhancing the effectiveness of the attack scheme. Finally, the feasibility and effectiveness of the attack scheme were verified through computer simulations. The experiments indicate that the method proposed in this paper has low computational complexity, wide applicability, produces high-quality decrypted images, and high decipherment accuracy. This provides a universal approach for analyzing the security of various optical cryptosystems from the perspective of chosen plaintext attacks.

Integer syndrome decoding in the presence of noise

Code-based cryptography received attention after the NIST started the post-quantum cryptography standardization process in 2016. A central NP-hard problem is the binary syndrome decoding problem, on which the security of many code-based cryptosystems lies. The best known methods to solve this problem all stem from the information-set decoding strategy, first introduced by Prange in 1962. A recent line of work considers augmented versions of this strategy, with hints typically provided by side-channel information. In this work, we consider the integer syndrome decoding problem, where the integer syndrome is available but might be noisy. We study how the performance of the decoder is affected by the noise. First we identify the noise model as being close to a centered in zero binomial distribution. Second we model the probability of success of the ISD-score decoder in presence of a binomial noise. Third, we demonstrate that with high probability our algorithm finds the solution as long as the noise parameter d is linear in t (the Hamming weight of the solution) and t is sub-linear in the code-length. We provide experimental results on cryptographic parameters for the BIKE and Classic McEliece cryptosystems, which are both candidates for the fourth round of the NIST standardization process.

CryptoHHO: a bio-inspired cryptosystem for data security in Fog–Cloud architecture

CryptoHHO: a bio-inspired cryptosystem for data security in Fog–Cloud architecture

A Characterization of Generalized Boolean Functions Employed in CDMA Communications

In design of secure cryptosystems and CDMA communications, the negabent functions play a significant role. The generalized Boolean functions have been extensively studied by Schmidt and established several important results in this setup. In this paper, several characteristics of the generalized nega-Hadamard transform (GNT) of generalized Boolean functions like inverse of GNT, generalized nega-cross correlation, generalized nega-Parseval’s identity, relationship between GNT and generalized nega-cross correlation have analyzed. We studied the GNT for the derivative of this setup of functions and established the connection of generalized Walsh-Hadamard transform and GNT of derivatives of these functions. Also, the GNT of composition of vectorial Boolean function and generalized Boolean function is presented. Further, the generalized nega-convolution theorem for generalized Boolean function is obtained.

Toward Next Generation Quantum-Safe eIDs and eMRTDs: A Survey

Security mechanisms of Electronic Personal Documents (eCards) depend on (asymmetric) cryptography that is and always has been subject to the threat of compromise, be it from conventional attacks or quantum computers. With Post-Quantum Cryptography (PQC), we now have alternative building blocks at hand that can be leveraged to protect against both kind of attacks. Thus, PQC should be incorporated into eCard ecosystems, yet it is not clear how this is done best. In the work at hand, we review the state of currently used crypto-systems for eCard security, as well as their possible quantum-secure replacements. Further, we identify and categorize respective challenges that need to be addressed, present and assess existing approaches for their solution, and formulate research questions for open issues. By providing an overview of the situation, we help unraveling the issue and pave the way toward quantum-safe electronic Identity Documents and electronic Machine-Readable Travel Documents.

High-security learning-based optical encryption assisted by disordered metasurface

Artificial intelligence has gained significant attention for exploiting optical scattering for optical encryption. Conventional scattering media are inevitably influenced by instability or perturbations, and hence unsuitable for long-term scenarios. Additionally, the plaintext can be easily compromised due to the single channel within the medium and one-to-one mapping between input and output. To mitigate these issues, a stable spin-multiplexing disordered metasurface (DM) with numerous polarized transmission channels serves as the scattering medium, and a double-secure procedure with superposition of plaintext and security key achieves two-to-one mapping between input and output. In attack analysis, when the ciphertext, security key, and incident polarization are all correct, the plaintext can be decrypted. This system demonstrates excellent decryption efficiency over extended periods in noisy environments. The DM, functioning as an ultra-stable and active speckle generator, coupled with the double-secure approach, creates a highly secure speckle-based cryptosystem with immense potentials for practical applications.

The group factorization problem in finite groups of Lie type

With the development of Lie theory, Lie groups have profound significance in many branches of mathematics and physics. In Lie theory, matrix exponential plays a crucial role between Lie groups and Lie algebras. Meanwhile, as finite analogues of Lie groups, finite groups of Lie type also have wide application scenarios in mathematics and physics owning to their unique mathematical structures. In this context, it is meaningful to explore the potential applications of finite groups of Lie type in cryptography. In this paper, we firstly built the relationship between matrix exponential and discrete logarithmic problem (DLP) in finite groups of Lie type. Afterwards, we proved that the complexity of solving non-abelian factorization (NAF) problem is polynomial with the rank n of the finite group of Lie type. Furthermore, combining with the Algebraic Span, we proposed an efficient algorithm for solving group factorization problem (GFP) in finite groups of Lie type. Therefore, it's still an open problem to devise secure cryptosystems based on Lie theory.

VSDHS-CIEA: Color image encryption algorithm based on novel variable-structure discrete hyperchaotic system and cross-plane confusion strategy

Recently, the color image encryption algorithm based on chaos theory has become the focus of current research. When encrypting color images, the common practice is to treat color images as different gray components and process them severally, which results in more redundancy and low efficiency. The security of chaotic cryptosystems also depends on the performance of the chaotic systems adopted. The structures of many current chaotic systems are fixed, making their behaviors highly predictable. Additionally, the range of chaotic region parameters is limited and discontinuous. To solve the above-mentioned problems, a new color image encryption algorithm (CIEA) using fractal and chaos theory is presented, which fully considers the inherent connection among the RGB components of color images. First, we propose a variable-structure discrete hyperchaotic system (VSDHS) to solve the dilemma encountered by existing chaotic systems. The excellent dynamic properties of VSDHS are verified by rigorous mathematical proof and simulation performance analyses. Then, VSDHS-CIEA is designed using fractal theory and VSDHS. The algorithm makes full use of the inherent connection among the different components of color images and performs cross-plane confusion. Simulations and performance analyses prove that VSDHS-CIEA has higher security and better performance than some representative image encryption algorithms.

Algorithms of the Möbius function by random forests and neural networks

The Möbius function μ(n)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu (n)$$\\end{document} is known for containing limited information on the prime factorization of n. Its known algorithms, however, are all based on factorization and hence are exponentially slow on logn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\log n$$\\end{document}. Consequently, a faster algorithm of μ(n)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu (n)$$\\end{document} could potentially lead to a fast algorithm of prime factorization which in turn would throw doubt upon the security of most public-key cryptosystems. This research introduces novel approaches to compute μ(n)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu (n)$$\\end{document} using random forests and neural networks, harnessing the additive properties of μ(n)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu (n)$$\\end{document}. The machine learning models are trained on a substantial dataset with 317,284 observations (80%), comprising five feature variables, including values of n within the range of 4×109\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4\ imes 10^9$$\\end{document}. We implement the Random Forest with Random Inputs (RFRI) and Feedforward Neural Network (FNN) architectures. The RFRI model achieves a predictive accuracy of 0.9493, a recall of 0.5865, and a precision of 0.6626. On the other hand, the FNN model attains a predictive accuracy of 0.7871, a recall of 0.9477, and a precision of 0.2784. These results strongly support the effectiveness and validity of the proposed algorithms.

Two Indicators of Cross-Correlation for the Functions from Zqn to Z2q

Boolean functions play an important role in the design of secure cryptosystems and code division multiple access (CDMA) communication. Several possible generalizations of Boolean functions have been obtained in recent years. In this paper, we analyze the properties of functions from in terms of their Walsh-Hadamard transform (WHT). We provide a relationship between cross-correlation and the WHT of these functions. Also, we present a necessary and sufficient condition for the functions to have complementary autocorrelation. The Parseval’s identity for the current setup of these functions is obtained. Further, we obtained the modulus indicator (MI) and the sum-of-squares-modulus indicator (SSMI) of cross-correlation among two functions for the current setup.

A forensic framework to improve digital image evidence administration in IIoT✰

The extensive growth of Industrial Internet of Things (IIoT) has prompted cyber attackers to commence a variety of attacks which need to be identified to maintain the security of industrial data and services. Digital forensics is an extravagant need to detect cyber attacks and to identify cybercriminals. While conducting criminal investigation using digital forensics, there is high probability of leakage of collected digital evidence. Hence, the need for a secure and lightweight cryptosystem arises to protect it from cyber-attacks. In the present paper, authors aim to design a novel forensic framework for digital evidence administration using advanced encryption and preservation mechanisms. Authors focus to encrypt and preserve only digital image evidence but can be deployed on other types of multimedia data like video frames. Three types of Chaos-map algorithms namely 4D hyperchaotic map, 2D Arnold Cat map (ACM) and Henon Map have been utilized to encrypty and decrypt digital image evidence which enable high sensitivity and dependency on initial conditions, quasi-randomness, and ergodicity to digital content. The proposed approaches have been analyzed on different groups of images of different size and validated using various security parameters such as unified average changing intensity (UACI), correlation coefficient, and the number of pixels changing rate (NPCR). Image transformation and compression has been performed after encryption process using Fast Fourier Transformation (FFT). The proposed work has been analyzed using histogram and auto-correlation. Experimentations have provided the values of the correlation coefficient of plain images near 1 and the value of adjacent cipher images near zero which show a strong correlation. The evaluated results for UACI are more than 33 % for every considered images. The value for NPCR should be near 100 % and here the calculated results for each image are above 99 %. The complexity of the proposed encryption algorithm is O(n) due to key generation using a cryptographically secure pseudo-random number generator (CSPRNG). The compressed and transformed image evidence have been stored into decentralized blockchain to ensure the integrity and confidentiality. Decentralized blockchain has been used as a reliable and promising solution to preserve digital evidence due to its distinct features like secure peer to peer communication, improved trust and transparency among participants, integrity, confidentiality, immutability, without risk of single point-of-failure. The proposed digital forensic model is able to prevent various threats and security challenges which can contaminate or tamper off digital pieces of evidence and assures improved digital evidence administration and defensibility. In the proposed scheme, the encryption process takes only 2–3 s to perform the encryption of each size of image.

Continued Fractions Applied to the One Line Factoring Algorithm for Breaking RSA

The RSA (Rivest–Shamir–Adleman) cryptosystem is an asymmetric public key cryptosystem popular for its use in encryptions and digital signatures. However, the Wiener’s attack on the RSA cryptosystem utilizes continued fractions, which has generated much interest in developing competitive factoring algorithms. A general-purpose integer factorization method first proposed by Lehmer and Powers formed the basis of the well-known Continued Fraction Factorization (CFRAC) method. Recent work on the one line factoring algorithm by Hart and its connection with Lehman’s factoring method have motivated this paper. The emphasis of this paper is to explore the representations of PQ as continued fractions and the suitability of lower ordered convergences as representations of ab. These simpler convergences are then prescribed to Hart’s one line factoring algorithm. As an illustration, we demonstrate the working of our approach with two numbers: one smaller number and another larger number occupying 95 bits. Using our method, the fourth convergence finds the factors as the solution for the smaller number, while the eleventh convergence finds the factors for the larger number. The security of the RSA public key cryptosystem relies on the computational difficulty of factoring large integers. Among the challenges in breaking RSA semi-primes, RSA250, which is an 829-bit semi-prime, continues to hold a research record. In this paper, we apply our method to factorize RSA250 and present the practical implementation of our algorithm. Our approach’s theoretical and experimental findings demonstrate the reduction of the search space and a faster solution to the semi-prime factorization problem, resulting in key contributions and practical implications. We identify further research to extend our approach by exploring limitations and additional considerations such as the difference of squares method, paving the way for further research in this direction.

Key derivation function: key-hash based computational extractor and stream based pseudorandom expander.

The key derivation function is a specific cryptographic algorithm that transforms private string and public strings into one or more cryptographic keys. The cryptographic keys are essential for protecting electronic data during transmission on the internet. This function is designed based on a computational extractor and pseudorandom expander and is typically constructed using various cryptography ciphers such as stream ciphers, keyed-hash message authentication codes, and block ciphers. Having secure and efficient key derivation function designs is essential in the development of numerous security systems. A vulnerable key derivation function could potentially give attackers the ability to compromise an otherwise secure cryptosystem. This research proposes a different approach by combining two different cryptography ciphers to develop key derivation functions. The findings demonstrate that a computational extractor utilizing keyed-hash message authentication codes and a pseudorandom expander using stream ciphers maintain the highest level of security while also providing efficiency benefits in terms of execution time compared to existing key derivation function schemes.

Exploiting Substitution Box for Cryptanalyzing Image Encryption Schemes With DNA Coding and Nonlinear Dynamics

In recent years, a number of image encryption schemes based on DNA coding and nonlinear dynamics have been proposed. Generally, these DNA-based schemes first encode plaintext images into DNA sequences and then encrypt them with pseudorandom elements produced by chaotic systems or other nonlinear dynamics. Although ciphertexts can pass some security tests, many image encryption schemes are being shown to have intrinsic flaws and that they cannot guarantee a high level of security. In this paper, we cryptanalyze a family of image encryption schemes for which the encryption kernel is DNA coding or its variant. The complex DNA operation can be simplified as a substitution box (S-box). The whole cryptosystem's security level is thus significantly decreased and is vulnerable to the chosen-plaintext attack. Applications of this concept to break five ciphers are theoretically presented and experimentally verified. In addition, some suggestions for resisting similar attacks are also given in this paper.

Hybrid Intelligence and GPS: Design of a Location-Based Cryptosystem for Data Security in Computer Network

In mobile applications or the case of vehicles, the concept of Location-based Encryption is instrumental in increasing data security. Location-based encryption is one type of security algorithm where decryption or data access is bound to specified locations and times. This algorithm only provides an additional layer of security to the existing one. In this paper, we have tried to design a cryptosystem based on the longitude and latitude of a location. Here, we assume one object is moving (vehicle, mobile device, etc.) and another is fixed in an area. The encryption-decryption process can be done in a specific location using GPS information. We aim to protect the unauthorized access to confidential data based on the coordinate system (i.e., longitude & latitude) and cryptographic algorithm. We have generated a geo encryption key based on the longitude and latitude of two particular coordinates. Our cryptosystem has three modules: location and hybrid intelligence-based key generation, symmetric key-based authentication and bijective mapping-based encryption-decryption. The different types of experiments and their results and analysis confirm that our technique is very efficient for location-based data security.