An Innovative Design of Substitution Box Using Trigonometric Transformation

As the number of hacking events and cyber threats keeps going up, it is getting harder and harder to communicate securely and keep personal information safe on the Internet. Cryptography is a very important way to deal with these problems because it can secure data by changing it from one form to another. In this study, we show a new, lightweight algorithm that is based on trigonometric ideas and offers a lot of security by making it less likely that cryptanalysis will work. The performance of our suggested algorithm is better than that of older methods like the Hill cipher, Blowfish, and DES. Even though traditional methods offer good security, they may have more work to do, which slows them down. The suggested algorithm tries to close this gap by offering a solution based on trigonometric ideas that are both fast and safe. The main goal of this study is to come up with a small but strong encryption algorithm that cannot be broken by cryptanalysis and keeps Internet communication safe. We want to speed up the coding process without making it less secure by using trigonometric principles. The suggested algorithm uses trigonometric functions and operations to create non-linearity and confusion, making it resistant to both differential and linear cryptanalysis. We show that the suggested algorithm is more secure and faster than traditional methods like the Hill cipher, Blowfish, and DES by doing a lot of research and testing. Combining trigonometric ideas with a simple design makes it workable for real world uses and offers a promising way to protect data on the Internet

Dynamic S-BOX using Chaotic Map for VPN Data Security

A dynamic SBox using a chaotic map is a cryptography technique that changes the SBox during encryption based on iterations of a chaotic map, adding an extra layer of confusion and security to symmetric encryption algorithms like AES. The chaotic map introduces unpredictability, non-linearity, and key dependency, enhancing the overall security of the encryption process. The existing work on dynamic SBox using chaotic maps lacks standardized guidelines and extensive security analysis, leaving potential vulnerabilities and performance concerns unaddressed. Key management and the sensitivity of chaotic maps to initial conditions are challenges that need careful consideration. The main objective of using a dynamic SBox with a chaotic map in cryptography systems is to enhance the security and robustness of symmetric encryption algorithms. The method of dynamic SBox using a chaotic map involves initializing the SBox, selecting a chaotic map, iterating the map to generate chaotic values, and updating the SBox based on these values during the encryption process to enhance security and resist cryptanalytic attacks. This article proposes a novel chaotic map that can be utilized to create a fresh, lively SBox. The performance assessment of the suggested S resilience Box against various attacks involves metrics such as nonlinearity (NL), strict avalanche criterion (SAC), bit independence criterion (BIC), linear approximation probability (LP), and differential approximation probability (DP). These metrics help gauge the Box ability to handle and respond to different attack scenarios. Assess the cryptography strength of the proposed S-Box for usage in practical security applications, it is compared to other recently developed SBoxes. The comparative research shows that the suggested SBox has the potential to be an important advancement in the field of data security.Comment: 11 Page

Designing substitution boxes based on chaotic map and globalized firefly algorithm

Cipher strength mainly depends on the robust structure and a well-designed interaction of the components in its framework. A significant component of a cipher system, which has a significant influence on the strength of the cipher system, is the substitution box or S-box. An S-box is a vital and most essential component of the cipher system due to its direct involvement in providing the system with resistance against certain known and potential cryptanalytic attacks. Hence, research in this area has increased since the late 1980s, but there are still several issues in the design and analysis of the S-boxes for cryptography purposes. Therefore, it is not surprising that the design of suitable S-boxes attracts a lot of attention in the cryptography community. Nonlinearity, bijectivity, strict avalanche criteria, bit independence criteria, differential probability, and linear probability are the major required cryptographic characteristics associated with a strong S-box. Different cryptographic systems requiring certain levels of these security properties. Being that S- boxes can exhibit a certain combination of cryptographic properties at differing rates, the design of a cryptographically strong S-box often requires the establishment of a trade-off between these properties when optimizing the property values. To date, many S-boxes designs have been proposed in the literature, researchers have advocated the adoption of metaheuristic based S-boxes design. Although helpful, no single metaheuristic claim dominance over their other countermeasure. For this reason, the research for a new metaheuristic based S-boxes generation is still a useful endeavour. This thesis aim to provide a new design for 8 × 8 S-boxes based on firefly algorithm (FA) optimization. The FA is a newly developed metaheuristic algorithm inspired by fireflies and their flash lighting process. In this context, the proposed algorithm utilizes a new design for retrieving strong S- boxes based on standard firefly algorithm (SFA). Three variations of FA have been proposed with an aim of improving the generated S-boxes based on the SFA. The first variation of FA is called chaotic firefly algorithm (CFA), which was initialized using discrete chaotic map to enhance the algorithm to start the search from good positions. The second variation is called globalized firefly algorithm (GFA), which employs random movement based on the best firefly using chaotic maps. If a firefly is brighter than its other counterparts, it will not conduct any search. The third variation is called globalized firefly algorithm with chaos (CGFA), which was designed as a combination of CFA initialization and GFA. The obtained result was compared with a previous S-boxes based on optimization algorithms. Overall, the experimental outcome and analysis of the generated S-boxes based on nonlinearity, bit independence criteria, strict avalanche criteria, and differential probability indicate that the proposed method has satisfied most of the required criteria for a robust S-box without compromising any of the required measure of a secure S-box

An External Parameter Independent Novel Cost Function for Evolving Bijective Substitution‐Boxes

The property of nonlinearity has high importance for the design of strong substitution boxes. Therefore, the development of new techniques to produce substitution boxes with high values of nonlinearity is essential. Many research papers have shown that optimization algorithms are an efficient technique to obtain good solutions. However, there is no reference in the public literature showing that a heuristic method obtains optimal nonlinearity unless seeded with optimal initial solutions. Moreover, the majority of papers with the best nonlinearity reported for pseudo-random seeding of the algorithm(s) often achieve their results with the help of some cost function(s) over the Walsh–Hadamard spectrum of the substitution. In the sense, we proposed to present, in this paper, a novel external parameter independent cost function for evolving bijective s-boxes of high nonlinearity, which is highly correlated to this property. Several heuristic approaches including GaT (genetic and tree), LSA (local search algorithm), and the Hill Climbing algorithm have been investigated to assess the performance of evolved s-boxes. A performance comparison has been done to show the advantages of our new cost function, with respect to cost functions for s-boxes like Clark’s and Picek’s cost functions

Construction of nonlinear component of block cipher using coset graph

In recent times, the research community has shown interest in information security due to the increasing usage of internet-based mobile and web applications. This research presents a novel approach to constructing the nonlinear component or Substitution Box (S-box) of block ciphers by employing coset graphs over the Galois field. Cryptographic techniques are employed to enhance data security and address current security concerns and obstacles with ease. Nonlinear component is a keystone of cryptography that hides the association between plaintext and cipher-text. Cryptographic strength of nonlinear component is directly proportional to the data security provided by the cipher. This research aims to develop a novel approach for construction of dynamic S-boxes or nonlinear components by employing special linear group $PSL(2, \mathbb{Z})$ over the Galois Field $GF\left({2}^{10}\right)$. The vertices of coset diagram belong to $GF\left({2}^{10}\right)$ and can be expressed as powers of α, where α represents the root of an irreducible polynomial $p\left(x\right) = {x}^{10}+{x}^{3}+1$. We constructed several nonlinear components by using ${GF}^{*}\left({2}^{10}\right)$. Furthermore, we have introduced an exceptionally effective algorithm for optimizing nonlinearity, which significantly enhances the cryptographic properties of the nonlinear component. This algorithm leverages advanced techniques to systematically search for and select optimal S-box designs that exhibit improved resistance against various cryptographic attacks

MODIFICATION ADVANCED ENCRYPTION STANDARD (AES) ALGORITHM WITH PERFECT STRICT AVALANCHE CRITERION S-BOX

The Advanced Encryption Standard or better known as the AES Algorithm is a standard algorithm and has been widely used as an application of cryptography. Currently, a lot of research is developing about attacks on the AES algorithm. Therefore, there have been many studies related to modifications to the AES algorithm with the aim of increasing the security of the algorithm and to produce alternatives to encryption algorithms that can be used to secure data. In this study, modifications were made to the AES algorithm by replacing the S-box using the perfect SAC S-box in the SubBytes process. The Perfect SAC S-box has an exact SAC average value of 0.5. The S-box that will be used must have good security strength, therefore the perfect SAC S-box is tested, namely the AC, SAC, BIC, XOR Table Distribution, and LAT Distribution tests. Based on the results of the study, it was found that the perfect SAC S-box had almost the same S-box test results as the AES S-box. Furthermore, after the perfect SAC S-box is applied to the AES algorithm, it is analyzed how the effect of these modifications on the AES algorithm uses randomness testing for the block cipher algorithm, namely the strict avalanche criterion (SAC) test. The results of the AES test with perfect SAC S-box can meet the SAC test since the second round with better results than the original AES algorithm with SAC values of 0.5003 and 0.5019

Hierarchical feature extraction from spatiotemporal data for cyber-physical system analytics

With the advent of ubiquitous sensing, robust communication and advanced computation, data-driven modeling is increasingly becoming popular for many engineering problems. Eliminating difficulties of physics-based modeling, avoiding simplifying assumptions and ad hoc empirical models are significant among many advantages of data-driven approaches, especially for large-scale complex systems. While classical statistics and signal processing algorithms have been widely used by the engineering community, advanced machine learning techniques have not been sufficiently explored in this regard. This study summarizes various categories of machine learning tools that have been applied or may be a candidate for addressing engineering problems. While there are increasing number of machine learning algorithms, the main steps involved in applying such techniques to the problems consist in: data collection and pre-processing, feature extraction, model training and inference for decision-making. To support decision-making processes in many applications, hierarchical feature extraction is key. Among various feature extraction principles, recent studies emphasize hierarchical approaches of extracting salient features that is carried out at multiple abstraction levels from data. In this context, the focus of the dissertation is towards developing hierarchical feature extraction algorithms within the framework of machine learning in order to solve challenging cyber-physical problems in various domains such as electromechanical systems and agricultural systems. Furthermore, the feature extraction techniques are described using the spatial, temporal and spatiotemporal data types collected from the systems. The wide applicability of such features in solving some selected real-life domain problems are demonstrated throughout this study

A new algorithm for minutiae extraction and matching in fingerprint

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A novel algorithm for fingerprint template formation and matching in automatic fingerprint recognition has been developed. At present, fingerprint is being considered as the dominant biometric trait among all other biometrics due to its wide range of applications in security and access control. Most of the commercially established systems use singularity point (SP) or ‘core’ point for fingerprint indexing and template formation. The efficiency of these systems heavily relies on the detection of the core and the quality of the image itself. The number of multiple SPs or absence of ‘core’ on the image can cause some anomalies in the formation of the template and may result in high False Acceptance Rate (FAR) or False Rejection Rate (FRR). Also the loss of actual minutiae or appearance of new or spurious minutiae in the scanned image can contribute to the error in the matching process. A more sophisticated algorithm is therefore necessary in the formation and matching of templates in order to achieve low FAR and FRR and to make the identification more accurate. The novel algorithm presented here does not rely on any ‘core’ or SP thus makes the structure invariant with respect to global rotation and translation. Moreover, it does not need orientation of the minutiae points on which most of the established algorithm are based. The matching methodology is based on the local features of each minutiae point such as distances to its nearest neighbours and their internal angle. Using a publicly available fingerprint database, the algorithm has been evaluated and compared with other benchmark algorithms. It has been found that the algorithm has performed better compared to others and has been able to achieve an error equal rate of 3.5%

Mathematical aspects of the design and security of block ciphers

Block ciphers constitute a major part of modern symmetric cryptography. A mathematical analysis is necessary to ensure the security of the cipher. In this thesis, I develop several new contributions for the analysis of block ciphers. I determine cryptographic properties of several special cryptographically interesting mappings like almost perfect nonlinear functions. I also give some new results both on the resistance of functions against differential-linear attacks as well as on the efficiency of implementation of certain block ciphers