Cryptographic Techniques Research Articles

Blind Quantum Machine Learning with Quantum Bipartite Correlator.

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this Letter, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities for privacy-aware machine learning applications in the era of quantum technologies.

Efficient Lightweight Blockchain with Hybridized Consensus Algorithm for IoT Networks

Blockchain (BC) technology has attracted a lot of interest due to its excellent security and privacy features as well as its immutability. While BC can address security and privacy challenges in IoT, it is often computationally expensive, suffers from limited scalability, and introduces bandwidth overheads and delays, making it unsuitable for IoT applications. This paper proposes a novel lightweight and scalable blockchain (LIGHT-SB) designed specifically for IoT environments. In a smart IoT ecosystem, low-resource devices benefit from a centralized manager that handles communication keys and manages requests. LIGHT-SB enhances decentralization while maintaining robust privacy and security through a hybrid consensus algorithm combining permissionless proof-of-capacity and permissioned Byzantine fault tolerance (PoC-PBFT). Secure message delivery is achieved using SHA-256 and RSA cryptographic techniques. IoT device authentication, communication, and storage are safeguarded within the network. Distributed throughput management is implemented to monitor and adjust BC usage, ensuring it remains efficient. Qualitative evaluations demonstrate that LIGHT-SB effectively mitigates several security threats.

What is the Effectiveness of Salt and Pepper in Preventing Rainbow Table Attacks in Modern Password Hashing Algorithms?

Password security remains a critical concern in the digital age, as attackers continuously evolve their techniques to crack password databases. Among the most effective defenses against these threats are salt and pepper, two cryptographic techniques used to enhance password hashing security. Salt introduces unique, random values to each password, ensuring that even identical passwords result in different hashes, while pepper adds a hidden system-wide secret to further complicate attacks. This paper explores how salt and pepper work together to defend against rainbow table attacks, significantly increasing the complexity for attackers attempting to reverse-engineer password hashes. While these techniques provide strong protection, they are not foolproof and must be paired with additional security measures such as key-stretching algorithms and multi-factor authentication (MFA) to offer comprehensive defense. The paper also examines the limitations of salt and pepper and suggests future advancements, such as post-quantum cryptography and passwordless authentication, as potential pathways to further improve password security.

A designated private set based trapdoor authentication scheme for privacy preserving trust management in decentralized systems

Authentication is crucial for network system security, relying on methods such as passwords, ID cards, biometrics, and behavioral characteristics. The conventional centralized authentication may lead to potential performance bottlenecks and privacy risks such as key exposure, single point of failure. Decentralized authentication systems using cryptographic techniques aim to address these issues but often tradeoff between flexibility and communication efficiency. In this paper we propose a new cryptographic concept called designated private set-based trapdoor authentication (DPSBTA) for flexible and efficient trust management in decentralized systems. DPSBTA eliminates the need for a trusted authority, with users’ access privileges defined by their private sets. During the authentication process, each server can designate an element set and only if a user holds adequate elements which are contained in the designated set can he obtains a credential from the server. The key features of DPSBTA include: decentralized trapdoor authentication management, without a trusted authority, conducted in a double threshold manner; privacy preservation, as servers do not know users’ element holdings or credential generation; round-optimal communication, with only two rounds of interaction between users and servers. We present the generic construction, security models, and concrete algorithms with correctness proof. The theoretical proof and the performance evaluations demonstrate the tangible security and high efficacy of the proposed DPSBTA.

VISUAL CRYPTOGRAPHY WITH COLOR IMAGE ENCRYPTION VIA IMPROVED ELLIPTIC CURVE CRYPTOGRAPHY (ECC) AND OTP GENERATION: SELF-IMPROVED GOLD RUSH OPTIMIZATION ALGORITHM FOR OPTIMAL KEY GENERATION

Visual Cryptography is a cryptographic technique that involves encrypting images in such a way that decryption can be performed visually without the need for complex computations. This technique holds significant importance in secure image sharing, as it ensures that sensitive visual information remains confidential during transmission. Recognizing this significance, a novel approach named Self-Improved Gold Rush Optimization (SIGRO)-based Visual Cryptography has been proposed in this research. This approach encompasses two main phases: Embedding and Extraction. It involves encrypting three original images and two secret images using various encryption techniques such as Random grid-based secret image sharing, Extended Visual Cryptography Scheme (EVCS), and Kronecker product-based encryption, along with the integration of security measures like Modified HMAC-based One-Time Password generation technique (MHOTP) for Improved Elliptic Curve Cryptography (IECC)-based encryption and Baker's map-based encryption. In Kronecker product-based encryption stage, the SIGRO algorithm is utilized to generate optimal keys for encryption purposes. The SIGRO algorithm is proposed as a well-versed approach than the conventional Gold Rush Optimization (GRO) algorithm, incorporating three key enhancements. These enhancements significantly contribute to the efficacy and reliability of the SIGRO algorithm in generating optimal keys for Kronecker product-based encryption. Furthermore, the IECC-based encryption utilizes the MHOTP generation technique, where the OTPs generated by this technique serve as the keys for this encryption stage, enhancing the ECC algorithm into an IECC algorithm. The decryption process involves reversing the steps applied during various encryption stages. This proposed approach's significance lies in its ability to enhance security through a combination of encryption methods and security measures.

3D Lightweight Cryptosystem Design For IoT Applications Based On Composite S-Box

The security of the Internet of Things (IoT) depends on strong cryptographic functions that require extensive computation and resources. The security of Internet of Things (IoT) relies on the use of strong cryptographic functions that demand extensive computation and resources. Therefore, the selection of a cryptographic system is influenced by the computational and communicational capabilities of IoT devices, including their energy requirements, memory constraints, and execution time. This paper aims to develop a lightweight and secure encryption algorithm for IoT applications, focusing on advancing cryptanalysis techniques. We propose a new lightweight algorithm named enhanced 3D RECTANGLE, designed to deliver robust security for IoT applications and optimized for cell phones with minimal memory usage, low power consumption, and efficient performance. The RECTANGLE block cipher was chosen for this research due to its high efficiency and speed relative to other lightweight algorithms, despite some security issues. The proposed enhanced 3D RECTANGLE algorithm improves confusion and diffusion properties through a new 3D array block rotation method for 4x4 plaintext, based on a 128-bit key and 16 rounds. Additionally, we designed a 4x4 composite S-Box with a Galois field pipelining structure, offering a more advanced solution compared to the Look-Up Table method. The cryptanalysis, avalanche effect, and bit error rate tests were conducted to verify the security strength of the proposed algorithm. The proposed algorithm was evaluated against two existing algorithms, RECTANGLE and Extended 3D RECTANGLE. The enhanced 3D RECTANGLE algorithm provides better cryptanalysis, demonstrating a 40% avalanche effect and achieving a bit error rate (BER) of 31%, indicating its greater effectiveness compared to the other two lightweight algorithms.

SMedIR: secure medical image retrieval framework with ConvNeXt-based indexing and searchable encryption in the cloud

The security and privacy of medical images are crucial due to their sensitive nature and the potential for severe consequences from unauthorized modifications, including data breaches and inaccurate diagnoses. This paper introduces a method for lossless medical image retrieval from encrypted images stored on third-party clouds. The proposed approach employs a symmetric integrity-centric image encryption scheme, leveraging multiple chaotic maps and cryptographic hash techniques, to ensure lossless image reconstruction. Medical images are first encrypted by the image owners and converted into hashcodes encapsulating essential features using a deep hashing technique with the ConvNeXt network as the backbone in parallel. To ensure index privacy, these hashcodes are encrypted in a searchable manner. The encrypted medical images, along with a secure index, are subsequently uploaded to cloud storage. Authorized medical image users can request similar medical images for diagnostic purposes by submitting a query image, from which a search trapdoor is generated and sent to the cloud. The retrieval process involves a secure similar image search over the encrypted indexes, followed by decryption along with integrity verification of the retrieved images. The proposed method has been rigorously tested on three standard medical datasets, demonstrating an improvement of 5-20% in retrieval accuracy compared to standard baselines. Formal security analysis and experimental results indicate that the proposed scheme offers enhanced security and retrieval accuracy, making it an effective solution for the encrypted storage and secure retrieval of medical image data.

Securing Cloud Environments by Analyzing Cryptographic Techniques for Data Integrity and Confidentiality

With cloud computing, you'll effectively and rapidly reach a parcel of computer assets. Usually exceptionally valuable in this computerized age. But this alter within the way things work makes it much harder to keep data secure and private. There are numerous reasons why security is critical for cloud settings. This exposition centers on ways to keep information safe from individuals who shouldn't be able to see or alter it. We see at a few of the foremost vital thoughts in cryptography, such as hashing, advanced marks, symmetric and hilter kilter encryption, and how they can be utilized to security the cloud. A few sorts of encryption, like AES and others, keep information secure whereas it's being sent. Other sorts of encryption, like RSA and others, keep information secure whereas it's being put away. Hash calculations, like SHA-256, deliver each set of information a one of a kind advanced stamp that creates it simple to spot changes. This makes beyond any doubt that the information is rectify. Indeed more security is included by computerized marks, which check the data's clarity and reliability to create beyond any doubt it wasn't changed whereas it was being sent. There are more complicated secure strategies that we see at, such as secure multi-party computation and homomorphic encryption. There is solid protection indeed in places where no one can be trusted since these let forms be done on secured information without giving out the essential data. This paper examines how these safety measures can be utilized in cloud-based systems and talks about how well they perform and any speed issues they might lead to. There are case studies from real life that show how safe methods have been used successfully in the cloud. This shows that they can be used in real life. We also talk about the issues that come up when you need to manage encryption keys, which is a key part of keeping data safe. A lot of attention is paid to strong key management tools, such as Hardware Security Modules (HSMs) and key management services (KMS).

Security protocol for securing notifications about dangerous events in the agglomeration

Our everyday lives cannot function without intelligent devices, which create the so-called Internet of Things networks. Internet of Things devices have various sensors and software to manage the work environment and perform specific tasks without human intervention. Internet of Things networks require appropriate security at various levels of their operation. In this article, we present a new security protocol that protects communication in IoT networks and enables interconnected devices to communicate and exchange information to increase the security of people living in urban agglomerations. The Control Station device evaluates the collected data about events that may threaten the life or health of residents and then notifies the Emergency Notification Center about it. The protocol guarantees the security of devices and transmitted data. We verified this using automatic verification technology, formal verification using Burrows, Abadi and Needham logic and informal analysis. The proposed protocol ensures mutual authentication, anonymity and revocation. Also, it is resistant to Man-in-the-middle, modification, replay and impersonation attacks. Compared to other protocols, our solution uses simple cryptographic techniques that are lightweight, stable and do not cause problems related to high communication costs. It does not require specialist equipment, so we can implement it using typical hardware. At each stage of protocol execution, communication occurs between two entities, so it does not require interaction between different entities, which may limit its adaptability in the context of interoperability.

CryptoGenSec: A Hybrid Generative AI Algorithm for Dynamic Cryptographic Cyber Defence

As the world of cybersecurity constantly changes, traditional cryptographic techniques have faced limitations in the context of today's sophisticated and dynamic threats. Existing protections usually adopt static algorithms and key structures, making it difficult for them to resist the categories of modern attacks. This research paper, therefore, presents CryptoGenSec, a brand-new generative AI algorithm based on a hybrid consisting of generative adversarial networks (GANs) on reconnaissance learning (RL), for the purpose of increasing cryptographic cyber defences. CryptoGenSec applies a GAN to simulate various types of attack scenarios in cyberspace to perceive possible vulnerabilities. Then, RL refines the response strategies of our algorithm through recursive learning from the above simulations in real time and realizes the dynamic adaptation and evolution of defense mechanisms. By assessing the results of CryptoGenSec’s performance when traditional security methods are used as baselines, we can use several metrics for evaluation, such as detection accuracy, response time, resilience and evolution ability. According to these findings, the superiority of CryptoGenSec over conventional mechanisms becomes evident. To be more specific, it even shows an overwhelming edge in terms of threat detection, resulting in a 20% increase in speed of response, a 30% decrease in speed of response, and resisting power, making it 25% harder than the other methods. Moreover, it has a greater possibility of eliminating false-positive effects, which usually come from new and even dawned jeopardy: 50%. Moreover, to highlight the making-a-fortune frauds in the zero-day world, a comparison of the cohorts makes CryptoGenSec a 40% upper step. Stopping attackers from taking away all their data is also its plus point, which gains 95% achievement, whereas using mere methods only results in a 70% possibility. An enormous step in cybersecurity was taken with the combination of GANs and RL within the CryptoGenSec algorithm. Instead of being defenceless against all attacks, this approach changes and matches the threat level when necessary. The highly promising results presented here demonstrate its potential as a crucial technology for addressing the growing complexities of cyber challenges. This is a large step toward making defensive mechanisms more efficient and reliable.

Finding Complete Impossible Differential Attacks on AndRX Ciphers and Efficient Distinguishers for ARX Designs

The impossible differential (ID) attack is one of the most important cryptanalytic techniques for block ciphers. There are two phases to finding an ID attack: searching for the distinguisher and building a key recovery upon it. Previous works only focused on automated distinguisher discovery, leaving key recovery as a manual post-processing task, which may lead to a suboptimal final complexity. At EUROCRYPT 2023, Hadipour et al. introduced a unified constraint programming (CP) approach based on satisfiability for finding optimal complete ID attacks in strongly aligned ciphers. While this approach was extended to weakly-aligned designs like PRESENT at ToSC 2024, its application to ARX and AndRX ciphers remained as future work. Moreover, this method only exploited ID distinguishers with direct contradictions at the junction of two deterministic transitions. In contrast, some ID distinguishers, particularly for ARX and AndRX designs, may not be detectable by checking only the existence of direct contradictions.This paper fills these gaps by extending Hadipour et al.’s method to handle indirect contradictions and adapting it for ARX and AndRX designs. We also present a similar method for identifying zero-correlation (ZC) distinguishers. Moreover, we extend our new model for finding ID distinguishers to a unified optimization problem that includes both the distinguisher and the key recovery for AndRX designs. Our method improves ID attacks and introduces new distinguishers for several ciphers, such as SIMON, SPECK, Simeck, ChaCha, Chaskey, LEA, and SipHash. For example, we achieve a one-round improvement in ID attacks against SIMON-64-96, SIMON-64-128, SIMON-128-128, SIMON-128-256 and a two-round improvement against SIMON-128- 192. These results significantly contribute to our understanding of the effectiveness of automated tools in the cryptanalysis of different design paradigms.

Integrating Cryptographic Techniques with Machine Learning Algorithms for Enhanced Data Privacy and Information Security: A Mathematical Framework

Integrating Cryptographic Techniques with Machine Learning Algorithms for Enhanced Data Privacy and Information Security: A Mathematical Framework

Advanced Cybersecurity Enhancement through Mathematical Models: A Comprehensive Approach Using Statistical Methods, Cryptographic Techniques, and Machine Learning Algorithms (SVM, Random Forest, and Neural Networks) for Behavior-Based Malware Detection

Advanced Cybersecurity Enhancement through Mathematical Models: A Comprehensive Approach Using Statistical Methods, Cryptographic Techniques, and Machine Learning Algorithms (SVM, Random Forest, and Neural Networks) for Behavior-Based Malware Detection

Optimizing blockchain for healthcare IoT: a practical guide to navigating scalability, privacy, and efficiency trade-offs

The adoption of blockchain technology provides significant disruptive benefits to internet-of-things (IoT) applications in healthcare in vital aspects like security, integrity, transparency, and efficiency. Nevertheless, in order to fully realize the potential of blockchain-driven solutions, healthcare organizations have to address intricate compromises between essential factors including scalability, privacy and resource utilization considering that the data sensitivity alongside strict regulatory compliance requirements characterize this sector. This research discusses the fundamental aspects of these trade-offs, including the range of consensus protocols (e.g. proof-of-work, proof-of-stake) and cryptographic techniques (e.g. zero-knowledge proofs, homomorphic encryption). A systematic choice matrix is created, which relates specific use cases of the healthcare IoT to the optimal tailored blockchain structures on such critical metrics as transaction volume, frequency, privacy level and resource restrictions. The suggested framework provides solid, actionable recommendations to healthcare organizations in order to help them benefit from the enormous promise of the blockchain for connected IoT healthcare by finding a balance between decentralization advantages and performance, security and compliance requirements.

NFTs for 3D Models: Sustaining Ownership in Industry 4.0

Digital manufacturing (DM) is actively adopted to the production lifecycles of a variety of critical industries, and this rapid growth has resulted in exponential increase of 3D computer-aided design (CAD) models. Unfortunately, counterfeiting of intellectual property becomes a prominent threat as many 3D designs are accessible online, combined with the proliferation of cheap consumer 3D printers that enable malicious actors to produce non-authentic parts. State-of-the-art techniques to secure manufacturing processes mostly rely on watermarking, which embeds hidden information inside CAD models to prove ownership and authenticity. Nevertheless, such techniques tamper with the model itself, while existing attacks allow removing such watermarks altogether. To address these shortcomings, we integrate signal processing and cryptographic techniques and describe a tailored solution for CAD model ownership and supply chain management. Our approach generates unique identifiers for 3D designs using frequency-domain transforms and employs non-fungible tokens (NFTs) that persist on public distributed ledgers. Our NFTs are implemented on the Ethereum blockchain using smart contracts and their functionality is twofold: (a) authenticate the owner of a CAD model, and (b) enable ownership transfer. To validate our technique, we deployed our smart contract on Ethereum's proof-of-work Ropsten network and demonstrated the applicability of our methodology.

Elevating Data Entropy and Efficiency through Symmetric Cryptographic technique Based on Finite State Machine

Elevating Data Entropy and Efficiency through Symmetric Cryptographic technique Based on Finite State Machine

Anamoly based intrusion detection using ensemble machine learning and block-chain

<p>A major issue facing the quickly evolving technological world is the surge in security concerns, particularly for critical Internet-of-Things (IoT) applications like health care and the military. Early security attack detection is crucial for safeguarding important resources. Our research focuses on developing an anomaly-based intrusion detection system (IDS) using machine learning (ML) models. With the use of voting strategies, Bagging Ensemble, Boosting Ensemble, and Random Forest, we created a robust and long-lasting IDS. The F1 score is a crucial metric for measuring accurate predictions at the class level and serves as the focus of these ML systems. Maintaining a high F1 score in critical applications highlights the constant need for development. Make use of the latest CICIoT2023 data-set employ Hyper-ledger Fabric to create a private channel in order to bolster the security of our IDS through the usage of block-chain technology. We use block-chain's immutable record and cryptographic techniques to establish a decentralized, tamper-proof environment. Consequently, our proposed approach provides an efficient intrusion detection system that significantly enhances resource protection and alerting the user in prior with intruder information incritical regions for Internet of Things security applications.</p>

Enhancing cloud storage security through blockchain-integrated access control and optimized cryptographic techniques

Enhancing cloud storage security through blockchain-integrated access control and optimized cryptographic techniques

Hybrid Elephant Herding Optimization Approach for Cluster Head Selection And Secure Data Transmission In Wsn Using Hybrid Approach Cryptography Techniques

Introduction: The wireless nature of sensor networks makes safe transfer of data from one node to another a major challenge in communications. Sensing tasks connect these sensor nodes which have limitations of memories and energies. Cryptography techniques are utilised to handle critical issues of security in these networks. The performance of large-scale networks is enhanced in this case by optimisation algorithm mimicking natural behaviours.Methods: This work uses H-EHO (Hybrid Elephant Herding Optimisation technique based on Individual strategies to enhance cluster head selections in WSNs (Wireless Sensor Networks) and thus extend networks’ lifetime. WSNs complete cluster head selection processes, and proposed optimisation approach which selects cluster heads based on tracking of sensor nodes for enhancements. The clan operators of optimisation algorithms are adjusted to handle random walk scale factors of elephants. Clusters of WSNs elect updated sensor nodes in principle. Hybrid algorithm HSR19, a novel security symmetric technique offers greater security during data transfers. It offers integrity, confidentiality, and authentication for cryptographic primary keys. Results: The output of the simulation demonstrates the energy consumption, network longevity, end to end delay, and secure data transfer metrics. The results for choosing an effective and time-efficient cluster head selection process for WSNs are improved by contrasting the two approaches. Conclusion: This comparison also shows the efficiency of communication devices in terms of calculation times for encoding, decoding and energies consumed for various file sizes

A Review on Ancient Cryptographic, Modern Cryptographic and Quantum Cryptographic Techniques

Cryptography has a long and fascinating history, evolving from ancient techniques to modern methods and now exploring the potential of quantum mechanics. This review paper provides a comprehensive overview of cryptographic techniques from past to present. We begin by examining ancient cryptographic techniques, tracing their origins back to 2000 B.C. when the ancient Egyptians used "secret" hieroglyphics. We also discuss evidence from ancient Greece and Rome, such as secret writings and the famous Caesar cipher [1]. These early methods laid the foundation for the field of cryptography. Next, we delve into modern cryptographic techniques that have become increasingly complex and diverse in their applications. We explore how cryptography now makes extensive use of mathematical concepts from fields like information theory, computational complexity, statistics, combinatorics, abstract algebra, number theory, and finite mathematics. We also discuss how the development of digital computers and electronics has revolutionized cryptography, allowing for the encryption of any kind of binary data and the design of much more intricate ciphers [2]. Finally, we examine the emerging field of quantum cryptography, which aims to harness the principles of quantum mechanics to achieve new cryptographic functionalities beyond classical information alone. We survey some of the most remarkable theoretical uses of quantum information for cryptography, as well as the limitations and challenges faced by cryptographers in this new paradigm [3]. By tracing the evolution of cryptography from ancient times to the present day and beyond, this review paper provides valuable insights into the rich history and promising future of this critical field of study.