Traditional Encryption Methods Research Articles

QHopNN: investigating quantum advantage in cryptanalysis using a quantum hopfield neural network

Cryptanalysis is crucial for securing cryptographic systems, particularly with the advent of quantum computing, which threatens traditional encryption methods. Advanced cryptanalytic techniques are essential for developing robust systems that can withstand quantum attacks, ensuring encrypted data remains secure and accessible only to authorized parties. This paper introduces the Quantum Hopfield Neural Network (QHopNN) as a novel approach to enhance key recovery in symmetric ciphers. This research provides valuable insights into integrating quantum principles with neural network architectures, paving the way for more secure and efficient cryptographic systems. By leveraging quantum principles like superposition and entanglement, along with Hopfield networks’ pattern recognition and optimization capabilities, QHopNN achieves superior accuracy and efficiency in deciphering encrypted data. Additionally, integrating unitary quantum evolution with dissipative dynamics further enhances the cryptographic robustness and efficiency of QHopNN. The proposed framework is rigorously evaluated using prominent symmetric ciphers, including S-AES and S-DES, and benchmarked against existing state-of-the-art techniques. Experimental results compellingly demonstrate the superiority of QHopNN in key recovery, with a mean Bit Accuracy Probability (BAP) of 0.9706 for S-AES and 0.9815 for S-DES, significantly outperforming current methods. This breakthrough opens new avenues for advancing cryptanalysis and sets the stage for pioneering future research in quantum-inspired cryptographic techniques.

FTPE-BC: Fast thumbnail-preserving image encryption using block-churning

With the boom in personal images, cloud services are beginning to take on a significant role in image storage. However, images uploaded to the cloud will face new privacy threats. Image privacy can be effectively protected using traditional encryption methods, but the encrypted images are snowflake-like noisy images, which makes the images unusable. Lately, Thumbnail Preserving Encryption (TPE) is proposed, which relieves this conflict between image availability and privacy in cloud platforms by retaining thumbnails unchanged after encryption. Existing TPE schemes for intra-block grouping usually utilize a lot of pseudo-random functions with high computational complexity, which makes encryption and decryption time too long. We propose a new model, block-churning, and propose a new TPE scheme based on this model. In this scheme, all pixels in the block are churned as a whole. This fundamentally solves the problem of low encryption efficiency caused by intra-block grouping, and greatly improves the encryption speed, while being able to change pixel values more significantly in blocks. The experiment shows that the encrypted image achieves a good balance between availability and privacy.

Cryptographic Protocols Resilient to Quantum Attacks: Advancements in Post-Quantum Cryptography

New developments in quantum computing have made people worry that current security methods could be broken by quantum attacks. Some mathematical problems are hard to solve, which is how traditional encryption methods like RSA and ECC keep their secrets safe. However, quantum computers might be able to solve these issues a lot faster than regular computers, which makes these methods less safe. Because of this threat, experts have been working hard to make post-quantum cryptography methods that quantum computers can't break. These methods are made to stand up to the strength of quantum algorithms and protect the privacy, integrity, and validity of private data even when quantum attackers are present. Lattice-based cryptography is a potential method for post-quantum encryption. Its security comes from the difficulty of certain lattice problems. Lattice-based methods are thought to be safe from threats from both traditional and quantum computers because they offer good security promises. Lattice-based cryptography is a flexible way to build different types of cryptographic primitives, like encryption, digital signatures, and key sharing protocols. The study of code-based cryptography, which is based on how hard it is to decode some error-correcting codes, is another important advance. Code-based methods have been around for a long time and have been studied a lot, which makes them a good choice for security after quantum computing. Code-based cryptography is also easy to use and has strong security features, which makes it a good choice for real-world situations. Multivariate polynomial cryptography is another possible choice for cryptography after quantum computing. The safety of this method depends on how hard it is to solve systems of multivariate polynomial problems. Multivariate polynomial methods might not be as secure as lattice-based or code-based cryptography, but they are interesting options for some situations and places with limited resources.

Enhancing Cyber Security Using Quantum Computing and Artificial Intelligence: A Review

This article examines the transformative potential of quantum computing in addressing the growing challenge of cyber threats. With traditional encryption methods becoming increasingly ineffective against sophisticated cyber attacks, quantum computing emerges as a promising solution, offering unparalleled computational capabilities for enhancing cyber security. This technology is poised to revolutionize how we protect sensitive data by developing quantum-resistant encryption algorithms and quantum-based machine learning modules to safeguard critical infrastructures. By exploring the intersection between quantum computing and cyber security, this article highlights the opportunities, challenges, and prospects of leveraging quantum advancements to strengthen our defenses against the evolving landscape of cyber threats

Anonymous lattice-based authentication protocol for vehicular communications

Quantum-proof authentication is essential for vehicular communications as the threat of quantum computing attacks on traditional encryption methods grows. Several lattice-based authentication protocols have recently been developed to help with this issue, but they come with hefty storage and communication overheads. Most of them also fail to provide strong anonymity for vehicles and edge nodes and can not support authentication for vehicles from multiple domains. This study presents a new lattice-based authentication protocol for vehicular communications that addresses limitations of previous methods and offers advanced security features such as anonymity, and unlinkability. The protocol utilizes a distributed ledger to store public keys, making the system more secure, tamper-proof, and efficient for key revocation in large networks. Additionally, it allows for a multi-domain authentication system for vehicular communication with improved security and flexibility. The proposed protocol's security is evaluated both formally and informally to demonstrate its resistance against the well-known attacks. Additionally, the performance analysis indicates that the proposed protocol surpasses current protocols and is suitable for vehicular communications.

Chaos key enhanced physical layer secure transmission method based on the convolutional long short-term memory neural network

In this paper, we propose a method for training a key-enhanced chaotic sequence using the convolutional long short term memory neural network (CLSTM-NN) for secure transmission. This method can cope with the potential security risk posed by the degradation of chaotic dynamics when using chaotic model encryption in traditional secure transmissions. The simulation results show that the proposed method improves the key space by 1036 compared to traditional chaotic models, reaching 10241. The method was applied to orthogonal chirp division multiplexing (OCDM). To demonstrate the feasibility of the proposed scheme, we conducted transmission experiments of encrypted 16 quadrature amplitude modulation (QAM) OCDM signals at a speed of 53.25 Gb/s over a 2 km length of 7-core optical fiber and test different encryption schemes. After key enhancements, the overall number of keys in the system can increase from 18 to 105.The results show that there is no significant difference between the bit error rate (BER) performance of the encryption method proposed in this paper and the traditional encryption method. The maximum performance difference between the different systems does not exceed 1 dBm. This fact proves the feasibility of the proposed scheme and provides new ideas for the next generation of secure transmission.

Multi-dimension-precision chaotic encryption mechanism for Internet of Things

The massive amount of information processed in the Internet of Things(IoT) environment requires effective encryption schemes to ensure secure transmission. However, traditional encryption methods such as Elliptic Curve Cryptography (ECC) or Data Encryption Standard (DES) are not suitable for IoT environments where large amounts of data need to be quickly encrypted. In this paper, a multi-precision encryption mechanism based on multi-dimensional chaotic system is proposed. Firstly, the proposed scheme uses floating-point, 32-bit, 24-bit, and 16-bit data accuracy respectively, which can effectively reduce the complexity through fixed-point calculation. Secondly, aiming at the problem that traditional chaotic dynamic analysis methods such as the Lyapunov index cannot be applied, an analysis scheme based on complexity measure is proposed. Finally, a free dimension encryption mechanism based on Logistic, Tent, and PWLCM is proposed. By adding random disturbance to a one-dimensional chaotic map, the weak randomness of the single chaotic sequence is overcome effectively. Finally, the security analysis of the encryption scheme is carried out, and the result proves that the scheme can effectively resist the common attack means. In the 3D chaotic system, the encryption effect of 24-bit data accuracy is close to floating point accuracy, which is suitable for the IoT environment with large data volume, high encryption efficiency, and vulnerability.

Local bit-level image encryption algorithm based on one dimensional zero excluded chaotic map

The exchange of digital images on the internet has become more convenient, but it has also led to increasing security concerns. Image encryption differs from text encryption, as inherent features such as massive data volume and high pixel correlation make it challenging to apply traditional AES and DES methods to images. This paper introduces a novel local bit-level image encryption algorithm based on chaos. Firstly, a new one-dimensional chaos system named the One-Dimensional Zero Excluded Chaotic Map (1D-ZECM) is designed, possessing features such as approximate global chaos, a broad chaos range, and high Lyapunov exponents, making it well-suited for cryptography. To resist brute force attacks, a hash function is employed to generate the encryption system’s key, further enhanced by using the 1D-ZECM to derive the key stream for the cryptographic system. Unlike traditional encryption methods that encrypt all 8 bits of a pixel, this algorithm focuses on the first six bits of each pixel during the encryption process, as the lower two bits contain less image information. In the diffusion process, the key stream generated by the 1D-ZECM is combined with mod and XOR operations to diffuse the rearranged image. Experimental results demonstrate that the proposed encryption algorithm exhibits high security and can resist common attacks. Moreover, when compared to representative algorithms, the proposed algorithm demonstrates better security and efficiency. The encryption algorithm presented in this paper provides a high-quality encrypted output.

Attribute-Based Searchable Encryption: A Survey

With the advent of the big data era, the size and complexity of data continue to increase, which makes the requirement for data privacy and security increasingly urgent. However, traditional encryption methods cannot meet the demand for efficient searching in large-scale datasets. To solve this problem and enable users to search within encryped data and without decrypting the entire dataset, trapdoor functions and other cryptograhic techniques are introduced in searchable encryption. However, searchable encryption still cannot meet the needs in the real world. Therefore, researchers have introduced the concept of attribute-based encryption into searchable encryption, resulting in attribute-based searchable encryption (ABSE). This approach aims to achieve efficient search by attributes in encrypted datasets. ABSE has a wide range of applications in the fields of privacy protection, data sharing, and cloud computing. In this paper, we describe the trends in development, focusing on enhancing security, improving computational efficiency, and increasing flexibility. We also present the related schemes. In addition, several common application areas are introduced and the relevant schemes proposed by researchers are summarized. Moreover, the challenges and future directions of ABSE are discussed in this paper.

Image cryptosystem with image key using integral disproportion

The subject matter of this article is the process of securing visual data through encryption. The goal of this study is to develop a new approach for image encryption and decryption using an image as a key, where security and performance are comparable or superior to alternatives. The tasks to be solved are as follows: developing a symmetric image cryptosystem for both greyscale and colored images in any format that can use an arbitrary image as a security key; adapting the capabilities of integral disproportionality for image encryption. The encryption method applies an integral disproportion formula for each pair of pixels’ components for both the input image and the key image starting from the first one. The output is a ciphered object represented as an array of real numbers, with decryption being the inverse process. The result is a novel approach to image encryption, proposing a new cryptosystem in which an arbitrary image of varying size, format, or content serves as the encryption key. The proposed symmetric full-encryption cryptosystem is applicable to both greyscale and colored images in any format. The method employs a frequency-based approach that influences the values of pixels rather than their positions. In contrast to mainstream approaches in this area, the representation of a cipher is not an image but a binary array. The proposed algorithm is simple to implement. The proposed method appears to meet the required requirements in both security and performance. Conclusions. The scientific novelty of the results obtained is as follows: This research introduces a new image encryption method, which is unique in its application of integral disproportionality to alter pixel values, differing from traditional encryption methods. This provides a practical yet secure option to the existing encryption techniques.

Image security using steganography and cryptography with sweeping computational ghost imaging

A sweeping computational ghost imaging (SCGI)-based encryption system is intended for increased data security and speedier data transport. SCGI is combined with steganography and cryptography processes in this system. SCGI requires fewer shots, resulting in faster image capture, transmission, encryption, and decryption. This strategy also results in smaller, more compact data packages and higher bitrates. Least significant bit (LSB) uses steganography to conceal the hidden picture. In the case of Rivest–Shamir–Adleman (RSA) encryption, public and private keys are generated via a one-way function based on bucket values. Encryption is performed on two levels, with an asymmetric approach divided into three sub-items that significantly increase encryption. Surprisingly, the method uses fewer pictures for image reconstruction, resulting in faster image reconstruction. SCGI promises applications in an extensive number of data encryption sectors since this technology leads to smaller data packages and higher bitrates. The presented approach is examined using the number of pixel change rate (NPCR), normalized root mean square (NRMS), peak signal-to-noise ratio (PSNR), and correlation coefficient (CC), which indicates constant encryption improvement. We experimentally and situationally demonstrate our findings under eavesdropping, which prove the resistance and robustness of our methods. In optimal settings, this innovation enhances encryption by up to 90% when compared to traditional encryption methods.

Enhanced Secure Communication Protocol with Pipelined Advanced Encryption for Mobile Networks

In today's increasingly connected world, the demand for secure mobile communications is paramount. The security protocols are specifically tailored for mobile communication systems, ensuring the confidentiality and integrity of sensitive data transmitted over wireless networks. It can be seamlessly integrated into various mobile applications such as messaging platforms, VoIP services, and mobile banking apps, providing end-to-end encryption for user privacy. Current encryption protocols used in mobile communications often face challenges related to performance and security. Traditional encryption methods may not adequately address the evolving threats posed by sophisticated attackers. Moreover, the computational overhead associated with encryption and decryption processes can impact the overall efficiency of mobile communication systems. This work presents a novel approach to enhancing the security of mobile communications through the design of a Pipelined Advanced Encryption Based Cryptography Protocol (PAEBCP). The proposed protocol aims to address the vulnerabilities present in existing encryption methods by leveraging a pipelined architecture for efficient encryption and decryption processes. The proposed PAEBCP protocol introduces a pipelined architecture that optimizes the encryption and decryption processes for mobile communication systems. By dividing the encryption process into multiple stages and parallelizing key operations, the protocol enhances both security and performance.

Quantum computing and its potential impact on U.S. cybersecurity: A review: Scrutinizing the challenges and opportunities presented by quantum technologies in safeguarding digital assets

This study explores the dual impact of quantum computing on cybersecurity, focusing on the challenges it poses to existing cryptographic standards and the opportunities it presents for enhancing secure communication. Through a comprehensive review of current literature and analysis of emerging quantum-resistant technologies such as Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC), the research identifies key vulnerabilities in traditional encryption methods and outlines the potential of quantum technologies to revolutionize cybersecurity practices. The study emphasizes the urgent need for the development and standardization of quantum-resistant cryptographic solutions to safeguard digital assets against the computational capabilities of quantum technologies. Policy recommendations are psroposed to accelerate the adoption of quantum-safe standards and to foster collaboration among stakeholders in the cybersecurity ecosystem. Furthermore, the study highlights areas for future research, including the scalability of quantum-resilient solutions and the ethical implications of quantum computing on privacy and security. Conclusively, the findings suggest that a proactive and collaborative approach is essential for navigating the quantum computing era, underscoring the importance of preparing a quantum-resilient cybersecurity infrastructure to ensure the long-term security of digital communications and assets.

Exploring and reviewing the potential of quantum computing in enhancing cybersecurity encryption methods

As the landscape of cybersecurity continually evolves, traditional encryption methods face unprecedented challenges from the impending era of quantum computing. This paper undertakes a comprehensive exploration of the potential transformative impact that quantum computing could have on enhancing cybersecurity encryption methods. Commencing with an overview of quantum computing fundamentals, including the principles of quantum mechanics and key quantum properties, the paper delves into the disruptive power of Shor's algorithm. This algorithm, capable of exponentially faster factorization than classical counterparts, poses a significant threat to prevalent cryptographic techniques such as RSA and ECC. In response to the vulnerabilities exposed by quantum algorithms, the paper investigates the field of post-quantum cryptography, examining cryptographic algorithms designed to resist quantum attacks. Additionally, the study scrutinizes Quantum Key Distribution (QKD) as a potential solution for secure communication in a quantum environment, analyzing its strengths and limitations. The paper provides an updated survey of the current state of quantum computing, highlighting achievements, milestones, and a comparative analysis of existing quantum computing platforms. Subsequently, it assesses the potential impact of quantum computing on cybersecurity, addressing both its ability to fortify encryption and potential risks and vulnerabilities. Striking a balance between benefits and challenges, the research offers insights into the coexistence of quantum and classical cryptographic methods. Looking toward the future, the paper explores ongoing research and development in quantum computing, identifying challenges and ethical considerations. In conclusion, it synthesizes key findings, emphasizing the implications for the future of cybersecurity and advocating for continued research to ensure the development of resilient encryption methods in the quantum era.

Analyzing the Impact of Quantum Computing on Current Encryption Techniques

As the field of quantum computing progresses, the disruption to traditional encryption methods, which secure vast amounts of sensitive data, becomes an imminent threat, and conventional encryption techniques, primarily based on mathematical complexity, may no longer suffice in the era of quantum supremacy. This research systematically analyzes the vulnerabilities of current encryption standards in the face of advanced quantum computing capabilities, focusing specifically on widely-used cryptographic protocols such as RSA and AES, which are foundational to modern cybersecurity. Employing the SmartPLS method, the study models the interaction between quantum computing power and the robustness of existing encryption techniques, involving simulating quantum attacks on sample cryptographic algorithms to evaluate their quantum resistance. The findings reveal that quantum computing possesses the capacity to significantly compromise traditional encryption methods within the next few decades, with RSA encryption showing substantial vulnerabilities while AES requires considerably larger key sizes to maintain security. This study underscores the urgency for the development of quantum-resistant encryption techniques, critical to safeguarding future digital communication and data integrity, and advocates for a paradigm shift in cryptographic research and practice, emphasizing the need for 'quantum-proof' algorithms. It also contributes to the strategic planning for cybersecurity in the quantum age and provides a methodological framework using SmartPLS for further exploration into the impact of emerging technologies on existing security protocols.

Securing large-scale data processing: Integrating lightweight cryptography in MapReduce

<p>In today’s rapidly evolving digital landscape, the imperative of data security stands paramount. With the proliferation of sensitive information being stored and transmitted online, the necessity for robust encryption algorithms has grown exponentially. However, the suitability of traditional encryption methods in resource-constrained settings, like mobile devices and cloud computing, remains a concern due to their computational intensity. To address this, researchers have introduced a novel category of encryption algorithms known as lightweight cryptography algorithms. These cryptographic solutions are designed to offer robust security while minimizing computational demands, thus striking a harmonious balance between security and efficiency. While lightweight cryptography algorithms present a promising solution, their adequacy for applications demanding exceptionally high security, particularly within Big Data environments, warrants careful consideration. In this study, we presented a novel approach involving the utilization of lightweight cryptography algorithms within the MapReduce framework. By subjecting these algorithms to rigorous experimentation, we assessed their performance using software-oriented metrics from various dimensions.</p>

Using GAN-Based Encryption to Secure Digital Images With Reconstruction Through Customized Super Resolution Network

Unlike traditional encryption methods, Generative Adversarial Network (GAN)-based methods possess a high level of security for digital images. Many existing simple encryption methods may be less secure than expected and have high storage costs. This paper proposes a GAN-based encryption method to secure digital images, solving these problems. First, a random sequence generator using a GAN with cross-coupled logistics and a Henon map is generated to encrypt an image. Next, the encrypted image is downsampled into one-fourth of the original size and sent to the receiver. Finally, image reconstruction uses a Customized Super Resolution Network (CSRNet) rather than decompressing the image at the receiver side. Our extensive experimental results demonstrate that the proposed method achieves NPCR, UACI, entropy, PSNR and SSIM up to 0.99604, 0.33460, 7.9993, 37.0462 dB and 0.94561, respectively. Further, our encryption method achieves up to 75% faster than the recent methods when evaluated on two standard datasets. Therefore, the proposed GAN-Based solution can possess a high level of security and save sufficient storage space for any practical application.

A novel compression-based 2D-chaotic sine map for enhancing privacy and security of biometric identification systems

Human biometric images are utilized for cell phone authentication, airport security, and biometric passports. To improve the biometric identification process, this should be protected from cyber attackers because it is sensitive to any minor changes. Thus, security is a major concern in biometric images. Traditional encryption and compression methods are ineffective for encrypting biometric images due to their high execution time and algorithm complexity. In this paper, a novel 2D chaotic sine map is proposed for generating encryption keys and improving security for biometric identification systems. The proposed scheme uses the 2D chaotic map to generate the private key and diffusion process. Here, the Hénon-Sine Map (HSM-512), Secure Hash Algorithm (SHA-256), and DNA computing are also used in the key generation process. The pixel values of the original images in the proposed schemes are shuffled using Mersenne Twister (MT) to improve the security of biometric images. Moreover, the Differential Huffman Compression (DHC) method is used for lossless compression while performing the XOR-based encryption process. The proposed model has been tested on different RGB biometric images, namely the SOCOFing dataset and the COVID-19 chest X-ray dataset. The experiment results have been evaluated using many performance metrics, such as entropy, key space, histogram analysis, key sensitivity, robustness analysis, correlation, and similarity analysis. The outcomes demonstrate that the proposed scheme is more effective than the state-of-the-art schemes.

Cryptographic security for IoT : Leveraging Feistel-permutation network for enhanced encryption

The emergence of the Internet of Things (IoT) has initiated an era where numerous devices are interconnected, resulting in the generation of significant volumes of data. Data security is an issue raised by this increase in communication, especially when it comes to picture encryption. Traditional encryption methods create considerable challenges in resource-constrained IoT environments. In this paper, a novel encryption-based framework known as the Feistel-Permutation Network Hybrid is proposed. It effectively safeguards IoT image data. A comprehensive performance evaluation by utilizing MATLAB that shows the effectiveness of the algorithm used. The findings offer valuable insights into the efficacy of the algorithm. Also, the areas for further investigation within the ever-evolving field of IoT image encryption are discussed.

A Hybrid Chaotic Encryption ASIC With Dynamic Precision for Internet of Things

With the rapid development of the Internet of Things (IoT), device and data security has attracted huge academic attention in recent years since conventional security methods are barely feasible in IoT circumstances. Traditional encryption methods require extensive computation complexity, which requires several hardware resources and power consumption. Meanwhile, due to the low power requirement, most IoT devices are lightweight with limited computing and storage capabilities. The dilemma leads to the need for a lightweight encryption method with decent data protection strength. Chaotic encryption can be applied in the IoT because of the characteristics of determinacy and strong randomness. However, its safety and hardware overhead are positively correlated with implementation precision. Therefore, this paper performs a quantitative analysis of the system under different precision conditions. Then, a hybrid chaotic encryption scheme with dynamic precision is proposed, which balances power consumption and security protection level. Finally, the proposed design is implemented by Verilog and synthesized using SMIC 65nm CMOS technology. The evaluation results proved that the proposed ASIC provides decent encryption strength under diverse precision, effectively overcoming the influence of limited precision with low hardware resources and power consumption.