A Formal Verification Based on Yu-Cao Delayed Chaotic Neural Network

Chosen plaintext attacks (CPA) pose a significant security risk to encryption algorithms. However, it can be difficult to perform such an attack without direct access to the encryption process. This paper introduces a new cryptoanalysis method that uses hidden CPA to analyze image encryption schemes based on substitution boxes (S-boxes) Unlike traditional CPA methods, the proposed algorithm does not require that they can directly into the encryption process. Instead, a hidden attack vector is embedded in the natural host image to reduce the risk of attack detection. By asking the owner of the encryption algorithm to encrypt this encryption image and provide a cipher image, the input vector can be compared with its encrypted counterpart This can have an effective S-box and break encryption the algorithm, which does not interact directly with the encryption process. Experimental results demonstrate that the proposed method can completely recover cipher images in cascading S-box encryption schemes, regardless of the number of S-boxes used. Additionally, it conceals the CPA vector within the host image imperceptibly, achieving a high PSNR of 49.47 dB, indicating minimal visual distortion. Furthermore, our CPA significantly outperforms existing techniques in speed, recovering a grayscale image in just 1.2 seconds. This method provides a simple yet effective cryptanalysis tool to evaluate the security of such image encryption schemes against CPAs.

S-boxes have been widely used as a base of new encryption strategies. Recently, the utilization of S-box becomes popular in image ciphers as a main approach to performing substitution. Based on a general model of S-box-only image ciphers, this paper performs a cryptanalysis on the performance of these kinds of ciphers against chosen plaintext attack. The cryptanalytic findings have been concluded that not only S-box-only image ciphers are practically insecure against chosen plaintext attack, but also the computational complexity of the attack is only O(128L), where L is the total number of pixels with respect to the image. Moreover, a real S-box-only chaotic image cipher is tested as an example analysis to demonstrate our assertion. Finally, we give four corresponding improvement ideas that help to design a secure cryptosystem based on S-boxes.

OFDM-PON physical layer encryption scheme based on chaotic Joseph ring and fractal system

Recently we have defined Staircase-Generator codes (St-Gen codes) and their variant with a random split of the generator matrix of the codes. One unique property of these codes is that they work with arbitrary error sets. In this paper we analyze the semantic security against chosen plaintext attack (IND-CPA) and key-privacy i.e. indistinguishability of public keys under chosen plaintext attack (IK-CPA) of the encryption scheme with random split of St-Gen codes. In a similar manner as it was done by Nojima et al. and later by Yamakawa et al. we show that padding the plaintext with a random bit-string provides IND-CPA and IK-CPA in the standard model. The difference with McEliece scheme is that with our scheme the length of the padded random string is significantly shorter.

Cloud Service Providers (CSPs) allow data owners to migrate their data to resource-rich and powerful cloud servers and provide access to this data by individual users. Some of this data may be highly sensitive and important and CSPs cannot always be trusted to provide secure access. It is also important for end users to protect their identities against malicious authorities and providers, when they access services and data. Attribute-Based Encryption (ABE) is an end-to-end public key encryption mechanism, which provides secure and reliable fine-grained access control over encrypted data using defined policies and constraints. Since, in ABE, users are identified by their attributes and not by their identities, collecting and analyzing attributes may reveal their identities and violate their anonymity. Towards this end, we define a new anonymity model in the context of ABE. We analyze several existing anonymous ABE schemes and identify their vulnerabilities in user authorization and user anonymity protection. Subsequently, we propose a Privacy-Preserving Access Control Scheme (PACS), which supports multi-authority, anonymizes user identity, and is immune against users collusion attacks, authorities collusion attacks and chosen plaintext attacks. We also propose an extension of PACS, called Statistical Privacy-Preserving Access Control Scheme (SPACS), which supports statistical anonymity even if malicious authorities and providers statistically analyze the attributes. Lastly, we show that the efficiency of our scheme is comparable to other existing schemes. Our analysis show that SPACS can successfully protect against Collision Attacks and Chosen Plaintext Attacks.

Hiding data with simplified diffractive imaging based hybrid method

Improvement of Rhouma's attacks on Gao algorithm

In previous work, security results of decorrelation theory was based on the infinity-associated matrix norm. This enables to prove that decorrelation provides security against non-adaptive iterated attacks. In this paper we define a new matrix norm dedicated to adaptive chosen plaintext attacks. Similarly, we construct another matrix norm dedicated to chosen plaintext and ciphertext attacks.The formalism from decorrelation enables to manipulate the notion of best advantage for distinguishers so easily that we prove as a trivial consequence a somewhat intuitive theorem which says that the best advantage for distinguishing a random product cipher from a truly random permutation decreases exponentially with the number of terms.We show that several of the previous results on decorrelation extend with these new norms. In particular, we show that the Peanut construction (for instance the DFC algorithm) provides security against adaptive iterated chosen plaintext attacks with unchanged bounds, and security against adapted iterated chosen plaintext and ciphertext attacks with other bounds, which shows that it is actually super-pseudorandom.We also generalize the Peanut construction to any scheme instead of the Feistel one. We show that one only requires an equivalent to Luby-Rackoff’s Lemma in order to get decorrelation upper bounds.

In this paper, we describe the Halvorsen circulant system (HCS) with a fractional-order Caputo derivative and its qualitative properties. The numerical solution of the fractional order Halvorsen circulant system (FO-HCS) is proposed based on the Adomian decomposition method (ADM). The ADM method is used to solve fractional-order systems. Then, dynamics is analyzed using different methods including Lyapunov exponents, bifurcation diagrams, complexity, and phase diagrams. This paper also investigates the stabilization and synchronization of identical FO-HCS, and stability theory proves adaptive feedback control and synchronization. In addition, using the fractional-order system’s remarkable properties to develop the image encryption technique using the extended fractional sequences. The proposed method uses a keystream generator for high security based on the enhanced fractional Halvorsen circulant chaotic behavior. The simulation results confirm that it can resist various attacks, including statistical analysis, differential attacks, brute-force attacks, known plaintext attacks, and chosen plaintext attacks, with high security, and low computational complexity. Finally, the results of the simulation and its performance prove that it's effective and secure in image data.

Healthcare data has risen as a top target for cyberattacks due to the rich amount of sensitive patient information. This negatively affects the potential of advanced analytics and collaborative research in healthcare. Homomorphic encryption (HE) has emerged as a promising technology for securing sensitive healthcare data while enabling computations on encrypted information. This paper conducts a background survey of HE and its various types. It discusses Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SHE), Fully Homomorphic Encryption (FHE) and Fully Leveled Homomorphic Encryption (FLHE). A critical analysis of these encryption paradigms’ theoretical foundations, implementation schemes, and practical applications in healthcare contexts is presented. The survey encompasses diverse healthcare domains. It demonstrates HE’s versatility in securing electronic health records (EHRs), enabling privacy-preserving genomic data analysis, protecting medical imaging, facilitating privacy-preserving machine learning (ML), supporting secure federated learning, ensuring confidentiality in clinical trials, and enhancing remote monitoring and telehealth services. A comprehensive examination of potential vulnerabilities in HE systems is conducted. The research systematically investigates various attack vectors, including side-channel attacks, key recovery attacks, chosen plaintext attacks (CPA), chosen ciphertext attacks (CCA), known plaintext attacks (KPA), fault injection attacks (FIA), and lattice attacks. A detailed analysis of potential defense mechanisms and mitigation strategies is provided for each identified threat. The analysis underscores the importance of HE for long-term security and sustainability in healthcare systems.

As a response to serious transmission security problems in wireless communications, physical layer encryption (PLE) provides an effective security measure which is very different from upper layer cryptography technologies. PLE can take advantage of the effects of channel and noise and the processing objects are complex vector signals, which are essentially different from Boolean algebra based traditional cryptography. This paper establishes mathematical models, design frameworks and cryptographic primitives for PLE. Two design frameworks are proposed: stream PLE and block PLE. For stream PLE, a new 3D security constellation mapping is derived. For block PLE, two types of sub-transforms are defined: isometry transformations and stochastic transformations. The proposed PLE framework has a large cipher signal space and key space; it provides more freedom in design and can resist known plaintext attacks and chosen-plaintext attacks.

Security is always an important issue in wireless communications. Physical layer encryption (PLE) is an effective way to enhance wireless communication security and prevent eavesdropping. Rather than replacing cryptography at higher layers, PLE's benefit is to enable using lightweight cryptosystems or provide enhanced security at the signal level. The upper cryptography is faced with a noise-free channel, and the processing object is bit data. In PLE, the effects of channel and noise can be exploited to enhance security and prevent deciphering. In addition, since the processing object is complex vector signals, there are more operational functions to select and design for PLE. The mathematical models, design frameworks, and cryptographic primitives of PLE are established. Two design frameworks are proposed: stream PLE and block PLE. For stream PLE, a new 3D security constellation mapping is derived. For block PLE, two types of sub-transforms are defined: isometry transformations and stochastic transformations. Furthermore, a practical system operation mode PLE-block chaining (PBC) is proposed to enhance the practical system security. The proposed PLE framework can resist known plaintext attacks and chosen-plaintext attacks. The simulation shows that the proposed isometry transformation method has good performances in terms of bit error ratio (BER) penalty and confusion degree.

In this paper, anti-synchronization problem of two identical chaotic neural networks with time-varying delays is proposed. By using time-delay feedback control technique, mean value theorem and the Leibniz-Newton formula, and by constructing appropriately Lyapunov-Krasovskii functional, sufficient condition is proposed to guarantee the asymptotically anti-synchronization of two identical chaotic neural networks. This condition, which is expressed in terms of linear matrix inequality, rely on the connection matrix in the drive and response networks as well as the suitable designed feedback gains in the response network. Finally, the anti-synchronization of two chaotic cellular neural network and Hopfield neural network with time-varying delays are considered to illustrate the effectiveness of the proposed control scheme, in which, when compared with the nonlinear feedback control method, the proposed method shows superior performance. Key words: Lyapunov-Krasovskii functional, chaotic neural networks, anti-synchronization, time-varying delay, linear matrix inequality.

We present a new Authenticated Encryption (AE) scheme based on finite automata using the method Encrypt-then-MAC. The scheme is constructed from two cryptographic primitives, a symmetric encryption scheme based on finite automata known as FASKC and a Message Authentication Code (MAC) constructed from a finite automaton. The paper shows how the scheme works and how to construct a MAC from a finite automaton using a boolean function with good cryptographic properties. Due to the construction method and the assumption that the symmetric encryption scheme is secure under Chosen Plaintext Attack (CPA), it is shown that the MAC is unforgeable under Chosen Message Attack (UF-CMA) making the scheme secure under Chosen Ciphertext Attack (CCA).

Chaos based image encryption cryptosystems have garnered much attraction in the recent past. In this regard, recently, two chaos-based image encryption algorithms have been proposed. Both the cryptosystems exhibit very good cryptographic metrics. The first cryptosystem utilizes cryptographic tweaks and other cryptographic primitives to encrypt digital images. This cryptosystem also relies on the idea that a tweak can make the cryptosystem secure. Our paper points out that merely using a tweak doesn’t make the cryptosystem secure and additionally, the structure and stages in the algorithm bear inability to preserve confidentiality of sensitive data. The second cryptosystem is an enhancement of another cryptosystem. Our work indicates that the enhancement in the second cryptosystem is also weak and allows an adversary to retrieve the exact key itself. Both the cryptosystems have similar weaknesses and don’t follow the guidelines laid down by National Institute of Standards and Technology (NIST). It is observed that both the cryptosystems can be broken, to reveal the exact chaotic sequence used for encryption, using a Chosen Plaintext Attack. From this work, it is realized that the weaknesses in the methods can be partially avoided by strictly following the rules laid down by the cryptographic community and NIST. Apart from this, it is expected that future cryptosystems follow all the suggestions mentioned in our work so that, before the cryptosystem is out for attack by cryptanalysts, it is scrutinized sufficiently.