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The password-based key derivation function Scrypt has been employed for many services and applications due to its protection ability. It has also been employed as a proof-of-work algorithm in blockchain implementations. Although this cryptographic hash function provides very high security, the processing speed and power consumption to generate a hashed block for the blockchain network are low-performance. In this paper, a high-speed and low-power hardware architecture of the Scrypt function is proposed to generate blocks for the Scrypt-based blockchain network. This architecture minimizes the number of main computational blocks to reduce the power consumption of the system. In addition, the proposed sharing resources and pipelined architectures make the calculation speed increase significantly while the hardware cost is reduced by half compared to the parallel non-pipelined architecture. The full hardware system is designed and implemented on Xilinx Virtex-7 and Aveo U280 FPGA platforms. The hash rate of the proposed system reaches 229.1 kHash/s. Its hash rate, hardware and energy efficiencies are much higher than those of the other works implemented on FPGA and GPU hardware platforms. The proposed hardware architecture is also successfully implemented in an ASIC design using ROHM 180 nm CMOS technology.

In this paper, a new four-dimensional chaotic system is constructed. Then, the dynamics of the phase diagram, Lyapunov exponent, bifurcation, and complexity of the system are investigated, and the simulation circuit of the system is designed and the trajectory simulation of the system is implemented using a field programmable gate array. National Institute of Standards and Technology tests have verified the randomness of the output of the chaotic sequence by the system. Finally, a new color image encryption algorithm is designed based on this system. In the proposed algorithm, the plaintext information is used to generate the initial value of the system through a hashing algorithm, and the plaintext information is applied to the algorithm, reflecting the idea of algorithmic adaption. The bit-plane decomposition row dislocation breaks the strong correlation between pixels, and finally, the DNA encoding is combined with the diffusion method to complete the complete encryption process. Multiple security analysis methods show that the scheme has a good encryption effect.

The main purpose of passwords is to prevent unauthorized people from accessing the system. The rise in internet users has led to an increase in password hacking, which has resulted in a variety of problems. These issues include opponents stealing a company's or nation's private information and harming the economy or the organization's security. Password hacking is a common tool used by hackers for illegal purposes. Password security against hackers is essential. There are several ways to hack passwords, including traffic interception, social engineering, credential stuffing, and password spraying. In an attempt to prevent hacking, hashing algorithms are therefore mostly employed to hash passwords, making password cracking more difficult. In the suggested work, several hashing techniques, including message digest (MD5), secure hash algorithms (SHA1, SHA2, and SHA3) have been used. They have become vulnerable as a result of being used to store passwords. A rainbow table attack is conceivable. Passwords produced with different hash algorithms can have their hash values attacked with the help of the Hashcat program. It is proven that the SHA3 algorithm can help with more secure password storage when compared to other algorithms.

Protecting digital images is crucial, and image encryption schemes based on chaotic systems have been extensively studied where image permutation is a critical process. The updating processes of particle swarm optimization algorithm have the ability to change the rules of particles motion, and it can be employed to permutate image. In this work, an image encryption scheme based on the updating processes of particle swarm optimization algorithm and hyperchaotic system is proposed. Specifically, a key generation mechanism combined with secure hash algorithm 256 hash is first introduced to generate the initial values of hyperchaotic complex Lü system. Then, the plain image is confused by the position and velocity updating processes of particle swarm optimization algorithm. In addition, an adaptive diffusion mechanism is designed and applied to the confused image to obtain the final cipher image. Simulation results and security analysis show that the proposed scheme exhibits good performance of sophisticated dynamic behavior, high sensitivity to key, and effectively resisting the typical cryptanalysis attacks, and provides an alternative to real-time image encryption application.

Current classification and retrieval methods are affected by the amount of data in the classification of multimedia learning resources, and there are problems such as low classification accuracy, low retrieval rate, and long retrieval time. To solve this problem, a new multimedia learning method is proposed. Combine decision tree and hash algorithm to design resource classification and retrieval method. The decision tree algorithm is used for the collection and classification of multimedia learning resources, the hash algorithm is introduced to solve and preprocess the resources, and the Lyapunov theorem is used to obtain features. By using two different deep convolutional networks as non-linear hash functions, joint training enables the corresponding hash codes of the network to interpret the similar relations contained in the semantic information. Use annotated propagation algorithm to realize multimedia classification and retrieval of learning resources. The experimental results show that the improved method can effectively improve the retrieval accuracy and efficiency of multimedia learning resources, and has certain practicability.

Currently, blockchain-based solutions for drug traceability encounter challenges related to counterfeit drug prevention, user identity verification, and scalability. This paper presents BE-AC, an enhanced blockchain-based drug traceability solution. To bolster the authenticity and integrity of drug information, we innovatively upgraded the EdDSA (Edwards-curve Digital Signature Algorithm) digital signature algorithm. Our enhancement incorporates the more advanced and efficient BLAKE3 hash function, replacing the conventional SHA-512 (Secure Hash Algorithm 512-bit). By employing larger hash windows and secure, efficient hash iteration modes, we expedite the generation and verification of digital signatures for drug information, thereby enhancing the overall performance and security of the system. Additionally, we have devised a decentralized identity authentication scheme. Through on-chain stored identity information, all participants can mutually verify each other’s identities, effectively preventing identity impersonation and fraudulent transactions. Furthermore, we have implemented smart contracts to record and store all transaction information on-chain during the drug distribution process, ensuring reliable and convenient drug transaction traceability. To address scalability and information security, we introduced a collaborative on-chain and off-chain drug information storage solution. Experimental results demonstrate a remarkable 78.65% improvement in signature verification efficiency compared to the original algorithm. The designed solution exhibits noteworthy enhancements in identity authentication, system throughput, and storage efficiency.

In the Quantum Key Distribution (QKD) network, authentication protocols play a critical role in safeguarding data interactions among users. To keep pace with the rapid advancement of QKD technology, authentication protocols must be capable of processing data at faster speeds. The Secure Hash Algorithm (SHA), which functions as a cryptographic hash function, is a key technology in digital authentication. Irreducible polynomials can serve as characteristic functions of the Linear Feedback Shift Register (LFSR) to rapidly generate pseudo-random sequences, which in turn form the foundation of the hash algorithm. Currently, the most prevalent approach to hardware implementation involves performing block computations and pipeline data processing of the Toeplitz matrix in the Field-Programmable Gate Array (FPGA) to reach a maximum computing rate of 1 Gbps. However, this approach employs a fixed irreducible polynomial as the characteristic polynomial of the LFSR, which results in computational inefficiency as the highest bit of the polynomial restricts the width of parallel processing. Moreover, an attacker could deduce the irreducible polynomials utilized by an algorithm based on the output results, creating a serious concealed security risk. This paper proposes a method to use FPGA to implement variational irreducible polynomials based on a hashing algorithm. Our method achieves an operational rate of 6.8 Gbps by computing equivalent polynomials and updating the Toeplitz matrix with pipeline operations in real-time, which accelerates the authentication protocol while also significantly enhancing its security. Moreover, the optimization of this algorithm can be extended to quantum randomness extraction, leading to a considerable increase in the generation rate of random numbers.

Attack detection in cyber security systems is one of the complex tasks which require domain specific knowledge and cognitive intelligence to detect novel and unknown attacks from large scale network data. This research explores how the network operations and network security affects the detection of unknown attacks in network systems. A hash based profile matching technique is presented in this paper for attack detection. The main objective of this work is to detect unknown attacks using a profile matching approach in Hypervisors. Hypervisors are characterized by their versatile nature since they allow the utilization of available system resources. The virtual machines (VMs) in the hypervisors are not dependent on the host hardware and as a result, hypervisors are considered advantageous. In addition, hypervisors have direct access to the hardware resources such as memory, storage and processors. However, hypervisors are more susceptible to the security threats which attack each and every VM. A SHA3-512 hashing algorithm used for generating hash values in hypervisor and the proposed model is used to verify whether the profile is malicious or benign. The performance of the hashbased profile matching technique is compared with traditional hash techniques namely SHA-256 and MD5 algorithm. Results show that the proposed SHA3-512 algorithm achieves a phenomenal performance in terms of phenomenal accuracy and zero false positive rates. Simulation results also show that the computation time required by Sha3-512 algorithm is lower compared to SHA-256 and MD5 algorithms. The performance analysis validates that the hash based approach achieves reliable performance for attack detection. The effectiveness of the hashing technique was determined using three different evaluation metrics namely attack DR, FPR, and computational time. Simulation results show that the existing SHA3- 512 algorithm detection rate of 97.24% with zero false positive rate and faster computational time compared to SHA 256 and MD5 algorithms.

Fragile digital watermarking is mainly used for digital content authentication, which is of great significance for protecting information security. A novel fragile spatial watermarking scheme based on prime number distribution theory is proposed in this paper. Firstly, 54 approximate pixel sets are constructed according to the prime number distribution in [0,255]. Secondly, the embedding of watermark information is achieved by pixel replacement in the approximate pixel set, while the MD5 hashing algorithm is used in the embedding process to ensure the security of the scheme. The experimental results show that the proposed watermarking scheme has better performance compared with the existing methods. It is not only robust to common image processing operations such as additive noise, rotation, sharpening and etc., but also has good invisibility, fragility, high capacity and low computational cost.

This paper introduces a lightweight cryptographic hash algorithm, LWH-128, developed using a sponge-based construction and specifically adapted for operation under constrained computational and energy conditions typical of embedded systems and Internet of Things devices. The algorithm employs a two-layer processing structure based on simple logical operations (XOR, cyclic shifts, and S-boxes) and incorporates a preliminary diffusion transformation function G, along with the Davis–Meyer compression scheme, to enhance irreversibility and improve cryptographic robustness. A comparative analysis of hardware implementation demonstrates that LWH-128 exhibits balanced characteristics in terms of circuit complexity, memory usage, and processing speed, making it competitive with existing lightweight hash algorithms. As part of the cryptanalytic evaluation, a Boolean SATisfiability (SAT) Problem-based model of the compression function is constructed in the form of a conjunctive normal form of Boolean variables. Experimental results using the Parkissat SAT solver show an exponential increase in computational time as the number of unknown input bits increased. These findings support the conclusion that the LWH-128 algorithm exhibits strong resistance to preimage attacks based on SAT-solving techniques.