Key Generation Research Articles

A New Tree Quantum Key Agreement Protocol for Secure Multiparty Communication

The Tree Multiparty Quantum Key Agreement Protocol (TMQKAP) is introduced as a novel solution for secure quantum key agreement among multiple participants, specifically tailored for tree topologies. Based on the BB84 protocol, TMQKAP employs hierarchical tree structures and XOR operations to facilitate efficient and secure key generation. Key elements are exchanged among participants in an equitable manner, ensuring that each participant contributes equally to the generation of the shared key. The protocol demonstrates robust security, effectively defending against both external and internal attacks, and achieves a quantum efficiency of 1/2 (N −1), where N is the number of participants. Thorough security analysis and simulations show TMQKAP’s robustness against various attacks while maintaining high efficiency. Additionally, the protocol is readily implementable with current quantum technologies, utilizing single-photon transmission to facilitate secure key distribution.

Implementation of an Image Tampering Detection System with a CMOS Image Sensor PUF and OP-TEE

Since image recognition systems use image data acquired by image sensors for analysis by AI technology, an important security issue is guaranteeing the authenticity of data transmitted from image sensors to successfully perform inference using AI. There have been reports of physical attacks on image sensor interfaces by tampering with images to cause misclassifications in AI classification results. As a countermeasure against these attacks, it is effective to add authenticity to image data with a message authentication code (MAC). For the implementation of this, it is important to have technologies for generating MAC keys on image sensors and to create an environment for secure MAC verification on the host device. For MAC key generation, we used the CIS-PUF technology, which generates MAC keys from PUF responses and random numbers from CMOS image sensor variations. For the secure MAC verification, we used TEE technology, which executes security-critical processes in an environment isolated from the normal operating system. In this study, we propose and demonstrate an image tampering detection system based on MAC verification with CIS-PUF and OP-TEE in an open portable TEE on an ARM processor. In the experiments, we demonstrated a system that computed and transmitted MAC for captured images using the CIS-PUF key and then performed MAC verification in the secure world of the OP-TEE.

Enhancing the SRAM PUF with an XOR Gate

This study focuses on designing enhanced Physically Unclonable Functions (PUFs) based on SRAM devices and improving the security of cryptographic systems. Most SRAM PUFs are limited in their number of CRPs, which makes them vulnerable to enrollment attacks. In this research, we present an SRAM-based PUF design that greatly increases the number of CRPs and the entropy of the generated bits by performing exclusive-or (XOR) on the responses of two SRAM devices. This was implemented using a readily available development board, SRAM devices, and a user-friendly custom circuit board for cryptographic key generation. The cryptographic protocol was implemented using both C++ and python3. The proposed SRAM PUF design was experimentally demonstrated and showed substantial improvements in the security of various cryptographic applications as a hardware authentication device. It also addresses the specific vulnerabilities of legacy designs.

Influence of tectonic evolution processes on burial, thermal maturation and gas generation histories of the Wufeng-Longmaxi shale in the Sichuan Basin and adjacent areas

The Wufeng-Longmaxi (WL) shale is widely distributed in the Sichuan Basin and adjacent areas in southwest China. The basin experienced multiple-stage complex tectonic movements, whose influences on burial, thermal maturation and gas generation histories in different areas are poorly understood. Based on a detailed study of the denudation stages, strata thickness, and thermal history of the basin, burial and thermal maturation histories of seven wells in different areas were modelled using PetroMod software. Due to the high maturity of the WL shale, a low-maturity Silurian Polish Llandovery shale was used for gold tube closed-system pyrolysis experiments to obtain kinetic parameters for evaluating methane generation history. The Polish shale was selected due to its depositional age, sedimentary environment and organic type, which are similar to the WL shale. The burial history of the WL shale can be divided into five stages: I. Early to Middle Silurian rapid burial; II. Caledonian uplift and denudation; III. Permian to Triassic sustained burial and denudation; IV. sustained burial since the Late Triassic; and V. Late Cretaceous to present sustained uplift and denudation. The thermal maturity of the WL shale in all wells increased with burial depth during stage IV. In addition, high calculated reflectance increments in wells JY1 and N201 during stage III occurred due to the relatively high basal heat flow and deep burial depth, resulting in higher current thermal maturities than in the other wells. The late Permian–Early Triassic and the Middle Jurassic–Early (or Late) Cretaceous were the key methane generation periods for wells JY1 and N201. In contrast, the other five wells had a single methane generation stage, mainly determined by burial and thermal maturation processes. The time of uplift and the amount of denudation during stage V, the current burial depth, the development of faults and fractures, high proportion of retention and the seal capacity of the overlying caprock are key factors for shale gas preservation. Hence, this study will help guide future shale gas development in the Sichuan Basin.

Heterogenous Analysis of KeyBERT, BERTopic, PyCaret and LDAs methods: P53 in Ovarian Cancer use case

In recent times, researchers with Computational background have found it easier to relate to Artificial Intelligence with the advancement of the transformer model, and unstructured medical data. This paper explores the heterogeneity of keyBERT, BERTopic, PyCaret and LDAs as key phrase generators and topic model extractors with P53 in ovarian cancer as a use case. PubMed abstract on mutant p53 was first extracted with the Entrez-global database and then preprocessed with Natural Toolkit (NLTK). keyBERT was then used for extracting keyphrases, and BERTopic modelling was used for extracting the related themes. PyCaret was further used for unigram topics and LDAs for examining the interaction among the topics in the word corpus. Lastly, Jaccard similarity index was used to check the similarity among the four methods. The results showed no relationship exists with KeyBERT, having a score of 0.0 while relationship exists among the three other topic models with score of 0.095, 0.235, 0.4 and 0.111. Based on the result, it was observed that keywords, keyphrases, similar topics, and entities embedded in the data use a closely related framework, which can give insights into medical data before modelling.

Improving the CSIDH Protocol for Multi-party Cryptography: Rigorous Mathematical Analysis, Efficiency, and Security Comparison

This paper introduces a novel Distributed Key Generation (DKG) protocol based on the Commutative Supersingular Isogeny Diffie-Hellman (CSIDH) framework for secure multi-party cryptography. Our proposed protocol is designed to address scalability and security concerns, particularly in post-quantum cryptographic systems. The main contributions include the introduction of Piecewise Verifiable Proofs (PVPs) for non-interactive zero-knowledge verification of secret shares, and the provision of rigorous security analysis, including resistance to quantum adversaries via Shor’s and Grover’s algorithms. We analyze the protocol’s efficiency, ensuring low computational overhead even in large-scale systems, and compare it with other distributed cryptographic protocols such as RSA-based and lattice-based schemes. Through mathematical proofs and complexity analysis, we demonstrate that our protocol offers enhanced security, efficiency, and scalability in a post-quantum environment. The results presented in this paper provide a strong foundation for implementing secure multi-party computations in quantum-resistant systems.

A novel method for generating public keys involving matrix operations.

With the rise of the Internet of things, the limitations of traditional PKI certificate authentication technology have progressively emerged. Hence, identity-based public key algorithms have been proposed. In this paper, we propose a new approach to generate an identity key, named identity public key (IPK). IPK identity key generation protocol is based on SM2 elliptic curve cryptography and random matrix theory. It builds upon the concept of combined public key (CPK) and resolves the linear collusion issue of CPK as well as the authenticity verification problem of the declared public key of the simplified TF-CPK by enhancing the identity mapping approach. Another main aim of this paper is to prove the security of the IPK identity key generation protocol. Roughly speaking, we verify the security of each part of the private key and the security of the composite private key. We also increase the function and performance comparison with other schemes, such as IBC(SM9) and TF-CPK. Our scheme has the lowest computation cost, which demonstrates its rationality.

Time-Based Cryptosystem

In this paper we introduce a Time-Based Cryptosystem (TBC) scheme. This scheme requires a Time-Based Key Generation Center (TBKGC) to broadcast a set of public keys based on the Multi-prime RSA (MPRSA) at every new interval. The sender encrypts the plaintext with a specified period of time and the corresponding public key broadcast by the TBKGC. And the receiver acquires the corresponding key from the TBKGC to decrypt the ciphertext. We discuss the difference between TBC and Time-Specific Encryption (TSE). Finally we suggest extension and directions of improvement of TBC.

Secure Data Aggregation and Transmission System for Wireless Body Area Networks Using Twofish Symmetric Key Generation

Nowadays, Wireless Body Area Networks (WBANs) are mostly used in the healthcare industry. They represent a portable, inexpensive network that exhibition adaptability. The data developed using WBAN devices is vulnerable to transmission-related internal and external attacks; nevertheless, this vulnerability arises due to resource restrictions; by employing data aggregation technologies to conduct statistical analyses of medical data while protecting patient privacy, medical professionals can enhance the precision of diagnoses and assist medical insurance firms in selecting optimal plans for their clients. Maintaining the confidentiality and integrity of sensitive health information becomes more stimulating at the stages of aggregation and transmission due to security issues. This study proposes a novel method, Twofish Symmetric Key Generation (TFSKG), combined into a Secure Data Aggregation (SDA) and transmission system intended for WBANs. The Twofish technique is animatedly employed to make the secure symmetric keys chosen for its robust encryption capabilities. These keys are used to encrypt and decrypt aggregated health data through transmission. The proposed TFSKG-SDA method implements effective algorithms for aggregating data to safeguard end-to-end privacy and preserve data accuracy while reducing bandwidth consumption. Thus, for improved performance, an innovative genetic algorithm for data security is presented in this study. This paper introduces TFSKG-SDA, a system that, by employing rigorous simulation testing, enhances security protocols, resistance against recognized threats, and data transmission efficacy in the context of resource-constrained WBANs. We assess the encryption strength, computational cost, and communication efficiency of the TFSKG- SDA method to prove its significance to real-world healthcare applications.

Implementation of Chaotic Neural Key Generation Algorithm For IoT Devices

This paper presents a new method for generating encryption keys for Internet of Things (IoT) devices. This method combines chaos theory with neural networks to create secure and efficient keys. We use the Lorenz chaotic system to generate complex patterns and a Convolutional Neural Network (CNN) to learn and predict these patterns. This approach is designed to address the unique security challenges of IoT devices, which often have limited computing power. We tested our method with different key sizes and evaluated its performance using accuracy, loss, entropy, and correlation metrics. The results show that key sizes between 256 and 512 bits offer the best balance between model performance and security for IoT devices. We also conducted Diehard statistical tests, which our key generation method passed successfully, demonstrating its ability to produce high-quality random keys.

Authenticated Key Exchange among IIoT Devices via Modified Blowfish with Optimal Key Generation

Authenticated Key Exchange among IIoT Devices via Modified Blowfish with Optimal Key Generation

Elliptic curves cryptography for lightweight devices in IoT system

The Internet of Things (IoT) is revolutionizing industries by connecting billions of devices, ranging from home appliances to industrial machines, to the internet. This transformation enables unprecedented automation, data collection, and process optimization. However, the widespread adoption of IoT also introduces significant security challenges, especially for lightweight devices with limited computational power and energy resources. Ensuring secure communication and data integrity in such constrained environments is critical. This paper explores and compares the performance of implemented algorithms within IoT devices. A comparison between Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) implementations is made to identify a lightweight, secure, and efficient solution for IoT environments. Our results indicate that ECC outperforms RSA in terms of memory requirements, overall energy consumption, key sizes, signature generation time, key generation and execution time, and decryption time in a resource-constrained environment. However, RSA performs better in signature verification and encryption.

A Review of Challenges and Developments in Wireless Channel Key Generation Technology

In recent years, physical layer security has become one of the core technologies for wireless communication system security. Physical layer encryption is based on the inherent reciprocity, time-varying, spatial uniqueness and unpredictability of wireless communication systems to generate keys, which are naturally unforgeable and steganography-proof. However, the research of physical layer key generation technology also faces many challenges, such as the problem of poor key generation performance due to signal interference, the problem of lower randomness and slower key generation rate in quasi-static channel environment, and the problem of lower key consistency between two legitimate communication parties due to the existence of channel estimation errors; this paper provides a systematic explanation of the traditional model of key generation for wireless channels and a typical solution for this series of problems. In this paper, the traditional model of wireless channel key generation is systematically explained, and the typical solutions to this series of problems are studied, analysed and compared in terms of performance.

Continuous-variable quantum passive optical network

To establish a scalable and secure quantum network, a critical milestone is advancing from basic point-to-point quantum key distribution (QKD) systems to the development of inherently multi-user protocols designed to maximize network capacity. Here, we propose a quantum passive optical network (QPON) protocol based on continuous-variable (CV) systems, particularly the quadrature of the coherent state, which enables deterministic, simultaneous, and high-rate secret key generation among all network users. We implement two protocols with different trust levels assigned to the network users and experimentally demonstrate key generation in a quantum access network with 8 users, each with an 11 km span of access link. Depending on the trust assumptions about the users, we reach 1.5 and 2.1 Mbits/s of total network key generation (or 0.4 and 1.0 Mbits/s with finite-size channels estimation). Demonstrating the potential to expand the network’s capacity to accommodate tens of users at a high rate, our CV-QPON protocols open up new possibilities in establishing low-cost, high-rate, and scalable secure quantum access networks serving as a stepping stone towards a quantum internet.

H²CT: Asynchronous Distributed Key Generation With High-Computational Efficiency and Threshold Security in Blockchain Network

H²CT: Asynchronous Distributed Key Generation With High-Computational Efficiency and Threshold Security in Blockchain Network

Scenarios for Optical Encryption Using Quantum Keys

Optical communications providing huge capacity and low latency remain vulnerable to a range of attacks. In consequence, encryption at the optical layer is needed to ensure secure data transmission. In our previous work, we proposed LightPath SECurity (LPSec), a secure cryptographic solution for optical transmission that leverages stream ciphers and Diffie–Hellman (DH) key exchange for high-speed optical encryption. Still, LPSec faces limitations related to key generation and key distribution. To address these limitations, in this paper, we rely on Quantum Random Number Generators (QRNG) and Quantum Key Distribution (QKD) networks. Specifically, we focus on three meaningful scenarios: In Scenario A, the two optical transponders (Tp) involved in the optical transmission are within the security perimeter of the QKD network. In Scenario B, only one Tp is within the QKD network, so keys are retrieved from a QRNG and distributed using LPSec. Finally, Scenario C extends Scenario B by employing Post-Quantum Cryptography (PQC) by implementing a Key Encapsulation Mechanism (KEM) to secure key exchanges. The scenarios are analyzed based on their security, efficiency, and applicability, demonstrating the potential of quantum-enhanced LPSec to provide secure, low-latency encryption for current optical communications. The experimental assessment, conducted on the Madrid Quantum Infrastructure, validates the feasibility of the proposed solutions.

Wireless Channel Key Generation Based on Multisubcarrier Phase Difference

Wireless Channel Key Generation Based on Multisubcarrier Phase Difference

EEG-based identification and cryptographic key generation system using extracted features from transformer-based models

EEG-based identification and cryptographic key generation system using extracted features from transformer-based models

MG+: Towards Efficient Context Inconsistency Detection by Minimized Link Generation

ABSTRACTSelf‐adaptive applications are becoming increasingly attractive, with the ability to smartly understand their runtime environments (or contexts) and deliver adaptive services, for example, location‐aware navigation or resource‐sensitive suggestions. However, due to inherent noises in the process of sensing and interpreting environmental information, there is a growing demand for guarding the consistency of collected contexts to avoid application misbehaviour and, at the same time, minimize extra costs. Existing work attempted to achieve this by speeding up the kernel constraint checking module inside the consistency guarding process. Most of these efforts were spent on reusing previous checking results or parallelizing the checking process, but they all leave one central step of constraint checking, that is, link generation, untouched. In this step, the checking engine provides reasons to explain the violation of constraints under check. It occupies a substantial part of the total time cost. Focusing on this key link generation step, we proposed MG, which deploys a rigourous analysis to automatically identify and avoid redundancy in the link generation without harming any correctness of the checking results. MG has been proven sound (always guaranteeing correctness) and complete (entirely removing redundancy). Moreover, based on our observation that MG's redundancy elimination also assists another core step of constraint checking to reduce unnecessary computation further, we additionally enhance MG with an escape‐condition optimization to escape unnecessary evaluation of truth values to further improve the efficiency of constraint checking in an aspect other than link generation. We call it MG+ for distinguishing. Our experiments with synthesized and real‐world consistency constraints reported that, compared with existing work, MG eliminates all link redundancy (83% to 0%), and based on it, MG+ further reduces significant truth value calculations (e.g., 49.74% reduction when combined with ECC and Con‐C). Generally, MG brought 14–500 speed‐ups in link generation, and MG+ further made 1.2–1.9 speed‐ups in truth value evaluation. Altogether, MG reduced the total constraint checking time up to 45.4%, and MG+ reduced it up to 61.0%.

Extreme learning with projection relational algebraic secured data transmission for big cloud data

SummaryCloud Computing (CC) and big data are growing technology in the business. Big data is demonstrated in terms of volume, variety, and velocity. CC is employed for storing, processing, and accessing data. Many cryptographic techniques have been developed to enhance big data security in cloud computing. However, security and privacy are the primary concerns in protecting data, as it is highly sensitive. Yet, it faces the major problems of inefficient performance, increased time consumption, and lack of data confidentiality and integrity. To address this issue, proposed Extreme Learning with Projection Relational Algebraic Secured Data Transmission (ELPRA‐SDT) is introduced to secure data transactions from cloud users to cloud servers with enhanced data confidentiality and reduced time consumption for big cloud data. The proposed ELPRA‐SDT consists of two major processes namely registration and key generation. At first, the user's IP address is registered employing a transitive advanced set relation theory graph model in a cloud server (CS) for retrieving the numerous services. The CS generates private and public keys for each registered user's IP address using the Transitive Operational and Time Synchronized Random Winternitz Key generation model. After, the user sends a request to the CS for acquiring data. The CS validates the requested user based on security policy attributes. Second, the Projection Relational Algebraic Signcryption and Unsigncryption algorithm performs signature verification to ensure secure data access for protecting the data. Results of experiments carried out by using Coburg Intrusion Detection Data Sets‐001 dataset in Java. ELPRA‐SDT method is more efficient and more suitable for providing security and privacy to network traces in the Cloud. The result shows maximum performance with data confidentiality by 10% and data integrity by 13%. In addition, delay is reduced by 32%, and data delivery time and communication complexity is decreased by 28% and 24% to other existing methods.