Review
Chemistry, Analytical
Tejal Rathod, Nilesh Kumar Jadav, Mohammad Dahman Alshehri, Sudeep Tanwar, Ravi Sharma, Raluca-Andreea Felseghi, Maria Simona Raboaca
Summary: This paper presents a survey of wireless networks (WNs) in the context of security and privacy issues with blockchain-based solutions. The existing research works, security requirements, and security issues in different generations of WNs are analyzed. The influence of blockchain technology and a taxonomy for blockchain-enabled security solutions in WN are showcased. Furthermore, a blockchain and 6G-based WN architecture is proposed and evaluated against performance metrics. Various open issues and research challenges for blockchain-based WNs solutions are discussed.
Article
Computer Science, Information Systems
Fariba Ghaffari, Emmanuel Bertin, Noel Crespi, Julien Hatin
Summary: The accelerated growth of networking technologies emphasizes the significance of Authentication and Access Control (AAC) in protecting against associated attacks. The use of Distributed Ledger Technology (DLT) has gained interest in the AAA community due to its distributed nature and immutability, which offer potential solutions to challenges faced by conventional systems. This paper explores the deployment of authentication and access control approaches via DLT for various networking use cases, and proposes future directions to address existing limitations and meet future needs.
COMPUTER SCIENCE REVIEW
(2023)
Article
Computer Science, Information Systems
Ajay Kumar, Kumar Abhishek, Bharat Bhushan, Chinmay Chakraborty
Summary: The study focused on using Ethereum-based Distributed Ledger Technology and unified advancements to address issues faced by Cloud-Based Manufacturers. By utilizing smart contracts based on controlled Ethereum with ERC20 interface, a comprehensive structure was created to secure Cloud-Based Manufacturing operations. The effectiveness of the prototype was demonstrated in the study, showing that critical loopholes in blockchain can be overcome. Suggestions for future research directions were also outlined.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Review
Computer Science, Interdisciplinary Applications
Anshuman Kalla, Chamitha de Alwis, Pawani Porambage, Gurkan Gur, Madhusanka Liyanage
Summary: 6G will be highly softwarized and open networks, but will also face issues such as security and privacy, blockchain technology will be deeply integrated into 6G networks to address these challenges.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Computer Science, Theory & Methods
Rafael Belchior, Andre Vasconcelos, Miguel Correia, Thomas Hardjono
Summary: Blockchain interoperability is crucial in reducing investment risks, enabling the development of the digital economy, providing migration capabilities, and supporting seamless interoperability among enterprises. Organizations can connect to each blockchain via gateways to achieve interoperability, but these gateways must be resilient to avoid crashes.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Sujit Biswas, Zigang Yao, Lin Yan, Abdulmajeed Alqhatani, Anupam Kumar Bairagi, Fatima Asiri, Mehedi Masud
Summary: The widespread use of smart devices and city-centric services improves civic life, but also raises concerns about privacy and security. To address security issues, city-centric services are shifting towards blockchain-based systems, which is a time-consuming and challenging process. This paper proposes an interoperability framework for blockchain-based smart city services and explores how independent service providers can continue local transactions without overloading the blockchain network. A simulated interoperability network demonstrates the effectiveness of the framework, showcasing the scalability and memory optimization of the blockchain network.
Article
Computer Science, Information Systems
Soumyashree S. Panda, Debasish Jena, Bhabendu Kumar Mohanta, Somula Ramasubbareddy, Mahmoud Daneshmand, Amir H. Gandomi
Summary: This article proposes a Blockchain-based distributed IoT architecture using hash chains for secure key management to ensure data privacy and provide a secure communication environment. It also introduces a secure and efficient key generation and management scheme for mutual authentication between communication entities, utilizing a one-way hash chain technique to provide a set of public and private key pairs to IoT devices. The experimental analysis confirms the superior performance of the proposed scheme compared to conventional mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Sumit Kumar Rana, Arun Kumar Rana, Sanjeev Kumar Rana, Vishnu Sharma, Umesh Kumar Lilhore, Osamah Ibrahim Khalaf, Antonino Galletta
Summary: Modern legal proceedings heavily rely on digital evidence, but threats to its security and integrity exist due to factors like data alteration and unauthorised access. To overcome these issues, we propose a decentralised methodology using smart contracts and blockchain technology. This approach ensures the integrity and transparency of digital evidence without the need for a centralised authority. Multiple parties can build confidence and accountability through programmable rules and automated enforcement mechanisms. Our study demonstrates the architecture and advantages of this decentralised model, as well as potential difficulties and constraints.
Article
Chemistry, Multidisciplinary
Quan Zou, Wenyang Yu, Ziwei Bao, Vincent A. Cicirello
Summary: A large number of raw data collected by satellites need to be processed to obtain product data, and the secure exchange and storage of these data is of interest to researchers in the field of remote sensing information science. Distributed ledger technology can ensure information security and traceability, and can be applied to the field of remote sensing to improve data security and management efficiency.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Saima Zafar, Syed Faseeh Ul Hassan, AlSharef Mohammad, Ahmad Aziz Al-Ahmadi, Nasim Ullah
Summary: This study applies advanced blockchain technology to automotive supply chain management, addressing the issues of inaccessible automobile records and used vehicle maintenance data. Experimental results demonstrate that blockchain can provide system security with minimal impact on storage and monetary costs.
Article
Computer Science, Information Systems
Rafael Torres Moreno, Jesus Garcia-Rodriguez, Jorge Bernal Bernabe, Antonio Skarmeta
Summary: Traditional Identity Management systems face privacy, trust, and security issues, with the European OLYMPUS project proposing a distributed approach based on enhanced Attribute-Based Credentials (ABC). However, trust relationships between service providers, users, and identity providers remain a gap in this privacy-preserving ABC system.
Article
Management
Evrim Tan, A. Paula Rodriguez Mueller
Summary: This study analyzes how blockchain technology affects the design choices and process of coproduction using the case of Barcelona. The findings suggest that blockchain-based coproduction has the potential to lead to new forms and roles in digital coproduction, but institutional, social, and organizational factors can influence the design choices and the implications of such processes.
PUBLIC MANAGEMENT REVIEW
(2023)
Article
Business
Michal Kowalski, Zach W. Y. Lee, Tommy K. H. Chan
Summary: The research findings suggest that blockchain technology enhances trust relationships among trading partners by improving the security of transactions and data exchanges, facilitating the expression of benevolence, enhancing the efficiency and quality of communication, and increasing the predictability of trading partners.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Review
Multidisciplinary Sciences
Damilare Peter Oyinloye, Je Sen Teh, Norziana Jamil, Moatsum Alawida
Summary: Blockchain networks are built on cryptographic notions, with mainstream protocols having drawbacks while alternative consensus protocols remain relatively unknown. These protocols offer unique merits for development of future consensus protocols.
Review
Computer Science, Information Systems
Bahareh Lashkari, Petr Musilek
Summary: This article provides a comprehensive review of the fundamentals of distributed ledger and its variants, with a comparative analysis of 130 consensus algorithms in different application domains. It also analyzes the evolution of consensus mechanisms and envisions future prospects for consensus as a crucial part of distributed ledger technology.
Article
Computer Science, Artificial Intelligence
O. S. Albahri, H. A. AlSattar, Salem Garfan, Sarah Qahtan, A. A. Zaidan, Ibraheem Y. Y. Ahmaro, A. H. Alamoodi, B. B. Zaidan, A. S. Albahri, Mohammed S. Al-Samarraay, Ali Najm Jasim, M. J. Baqer
Summary: In this study, the fuzzy multicriteria decision-making approach is utilized to address flexibility and uncertainty issues in the decision-making process by employing the Pythagorean fuzzy set (PFS) and m-polar fuzzy set. Two MCDM methods, namely Pm-PFWZIC and Pm-PFDOSM, are extended to weight the evaluation criteria and rank the alternatives. The empirical results show that the Pm-PFWZIC method effectively considers the importance of each evaluation criterion when evaluating sign language recognition systems.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Review
Computer Science, Artificial Intelligence
Amneh Alamleh, O. S. Albahri, A. A. Zaidan, A. H. Alamoodi, A. S. Albahri, B. B. Zaidan, Sarah Qahtan, Amelia Ritahani Binti Ismail, R. Q. Malik, M. J. Baqer, Ali Najm Jasim, Mohammed S. Al-Samarraay
Summary: Intrusion detection systems (IDSs) utilize advanced security techniques to detect malicious activities on hosts and/or networks. Multi-attribute decision-making (MADM) is a commonly used decision support approach for selecting the most optimal solution from available alternatives. This study conducts a systematic review to organize the research landscape of IDS and MADM, providing valuable reference for researchers.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Alhamzah Alnoor, A. A. Zaidan, Sarah Qahtan, Hassan A. Alsattar, R. T. Mohammed, K. W. Khaw, M. Alazab, Teh S. Yin, A. S. Albahri
Summary: This article proposes a novel benchmarking method for evaluating and comparing the sustainability of international oil companies using the linear Diophantine fuzzy rough sets (LDFRS) extension method. The results show that this method can effectively weigh the evaluation criteria and successfully benchmark the IOCs.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Z. T. Al-Qaysi, M. A. Ahmed, Nayif Mohammed Hammash, Ahmed Faeq Hussein, A. S. Albahri, M. S. Suzani, Baidaa Al-Bander
Summary: Brain-Computer Interface (BCI) research is an important interdisciplinary field that aids people with severe motor disabilities in recovering and improving motor actions through Motor Imagery (MI) based BCI systems. Smart Training Environments (STEs) based on virtual reality play a significant role in training users for motor recovery. However, there is a lack of comparisons of STE applications based on smart and effective criteria. This study develops a methodology for evaluating and benchmarking STE applications using Multi-Criteria Decision Making (MCDM) and provides important insights for the MI-BCI community and market.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
M. A. Ahmed, Z. T. Al-Qaysi, A. S. Albahri, M. E. Alqaysi, Gang Kou, O. S. Albahri, A. H. Alamoodi, Suad A. Albahri, Alhamzah Alnoor, Mohammed S. Al-Samarraay, Rula A. Hamid, Salem Garfan, Fahd S. Alotaibi
Summary: In this study, a new multi-criteria decision-making framework is developed to evaluate and benchmark hybrid multi-deep transfer learning models in radiography X-ray coronavirus disease (COVID-19) images. The framework includes data collection, pre-processing, feature extraction, hybrid model generation, and evaluation using performance metrics. The MCDM approach is used to develop a dynamic decision matrix, determine weight coefficients, and rank the hybrid models. The experimental results show the importance of different evaluation metrics and identify the top-performing hybrid models.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Physics, Applied
W. Al Saidi, R. Sbiaa, S. Bhatti, S. N. Piramanayagam, S. Al Risi
Summary: Controlling multiple skyrmions in nanowires is crucial for their use in racetrack memory or neuromorphic computing. This study examines the dynamic behavior of two interacting skyrmions in confined devices and compares it to the behavior of a single skyrmion. The two skyrmions shrink near the edges and follow a helical path, but their behavior differs. The leading skyrmion, positioned between the edge and the trailing one, shrinks further and collapses at a lower current density compared to the case of a single skyrmion. At higher current density, both skyrmions are annihilated through a core-collapse mechanism for the leading one and a bubble-collapse mechanism for the trailing one.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2023)
Article
Computer Science, Artificial Intelligence
Noorulden Basil, M. E. Alqaysi, Muhammet Deveci, A. S. Albahri, O. S. Albahri, A. H. Alamoodi
Summary: This research proposes a novel selection-integrated approach for optimizing AUV algorithms in different motions using two MCDM methods: FWZIC for criteria weighting and FDOSM for algorithm selection. The approach comprises three main phases: PID development, FWZIC-based criteria weighting, and FDOSM-based algorithm selection. The evaluation results indicate that AOA is the best alternative for depth motion, while black hole optimization is the worst alternative for yaw motion, and AOA is also the best alternative for theta motion.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Chemistry, Analytical
A. H. Alamoodi, O. S. Albahri, A. A. Zaidan, H. A. Alsattar, B. B. Zaidan, A. S. Albahri, Amelia Ritahani Ismail, Gang Kou, Laith Alzubaidi, Mohammed Talal
Summary: An intelligent remote prioritization method is proposed in this research for patients with high-risk multiple chronic diseases, based on emotion and sensory measurements and multi-criteria decision making. The methodology consists of a case study using a multi-criteria decision matrix and a modified technique for reorganizing opinion order. The results highlight the importance of chronic heart disease and emotion-based criteria, as well as the significance of Peaks as a sensor-based criterion and chest pain as an emotion criterion. Low blood pressure disease is identified as the most important criterion for patient prioritization, with severe cases being prioritized. The results are evaluated through systematic ranking and sensitivity analysis.
Review
Health Care Sciences & Services
A. S. Albahri, Z. T. Al-qaysi, Laith Alzubaidi, Alhamzah Alnoor, O. S. Albahri, A. H. Alamoodi, Anizah Abu Bakar
Summary: The significance of deep learning techniques in SSVEP-based BCI applications is assessed through a systematic review. Relevant articles were gathered from three reliable databases and classified into five categories based on their deep learning methods. The study examines the findings and challenges in existing applications, and provides recommendations for researchers and developers.
INTERNATIONAL JOURNAL OF TELEMEDICINE AND APPLICATIONS
(2023)
Article
Computer Science, Theory & Methods
Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, Jose Santamaria, A. S. Albahri, Bashar Sami Nayyef Al-dabbagh, Mohammed. A. A. Fadhel, Mohamed Manoufali, Jinglan Zhang, Ali. H. H. Al-Timemy, Ye Duan, Amjed Abdullah, Laith Farhan, Yi Lu, Ashish Gupta, Felix Albu, Amin Abbosh, Yuantong Gu
Summary: Data scarcity is a major challenge in training deep learning models due to the need for a large amount of labeled data. Manual labeling is costly and time-consuming, and many applications lack sufficient data for training. This paper presents a comprehensive overview of state-of-the-art techniques to address the issue of data scarcity in deep learning and provides recommendations for data acquisition and ensuring the trustworthiness of training datasets.
JOURNAL OF BIG DATA
(2023)
Article
Computer Science, Artificial Intelligence
O. S. Albahri, Mohammed S. Al-Samarraay, H. A. AlSattar, A. H. Alamoodi, A. A. Zaidan, A. S. Albahri, B. B. Zaidan, Ali Najm Jasim
Summary: Intrusion detection systems (IDSs) are commonly used in the Internet of Medical Things (IoMT) to address network security threats. However, IDSs face challenges in handling large network traffic, high-dimensional datasets, and real-time detection. This study integrates robust multi-criteria decision-making (MCDM) methodologies to overcome these challenges and proposes a precise solution using rough Fermatean fuzzy sets (RFFSs). The evaluations reveal the optimal IDS classifier and confirm the robustness of the results through systematic modeling and comparative studies.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
Article
Computer Science, Artificial Intelligence
Mohammed Al-Samarraay, Omar Al-Zuhairi, A. H. Alamoodi, O. S. Albahri, Muhammet Deveci, O. R. Alobaidi, A. S. Albahri, Gang Kou
Summary: Semiconductor materials are crucial for optoelectronics and power devices, but evaluating and selecting them is a multi-attribute decision-making problem. This study proposes an integrated fuzzy multi-measurement decision-making model (IFMMDMM) for evaluating and selecting optimization techniques for semi-polar III-V semiconductor materials.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Iman Mohamad Sharaf, A. H. Alamoodi, O. S. Albahri, Muhammet Deveci, Mohammed Talal, A. S. Albahri, Dursun Delen, Witold Pedrycz
Summary: This study proposes a novel multi-criteria decision-making solution to address the challenges in evaluating and selecting 5G-RAN architectures. By integrating fuzzy sets and Type-2 neutrosophic fuzzy environment, a more robust evaluation and decision platform is established. The weighting and selection methods determine the most important evaluation criteria and the optimal RAN architecture.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Mengqi Feng, Chao Lin, Wei Wu, Debiao He
Summary: Digital signature provides resistance against information tampering and identity impersonation, but lacks specific anonymity requirement for scenarios such as voting and whistle-blowing. Ring signature was introduced for achieving anonymity, but existing schemes face size limitations. In this paper, a novel construction paradigm called DualRing is proposed for logarithmic-sized ring signature. The SM2 digital signature is transformed into Type-T and integrated with DualRing technology, proving unforgeability and anonymity. Optimized and linkable schemes are proposed, and the performance in communication and computation costs are demonstrated.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
B. Meenakshi, D. Karunkuzhali
Summary: Wireless Sensor Network (WSN) is a crucial component of the cyber physical system, consisting of fixed or moving sensors that collectively sense, gather, analyze, and transfer data of detected objects. Intrusion detection schemes in WSNs often suffer from poor identification rate, high computation overhead, and higher false alarm rate. This study proposes an innovative approach that combines advanced techniques such as self-attention, provisional learning, and generative adversarial networks to improve security and adaptability in WSNs.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Jose Luis de la Vara, Hector Bahamonde, Clara Ayora
Summary: Most safety-critical systems undergo rigorous assurance processes to ensure dependability, often in compliance with standards like DO-178C for aerospace software. However, following these standards can be challenging due to issues in their text, such as imprecision and ambiguity. This study introduces an approach using RQA - Quality Studio for evaluating the text quality of safety standards, identifying common issues like passive voice and imprecise modal verbs in DO-178C.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Ruben Grande, Aurora Vizcaino, Felix O. Garcia
Summary: The adoption of DevOps in global and distributed settings can bring several advantages to software companies, but it also presents challenges that need to be overcome.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Haibo Tian, Yanchuan Wen, Fangguo Zhang, Yunfeng Shao, Bingshuai Li
Summary: In this paper, a lattice-based distributed threshold additive homomorphic encryption (DTAHE) scheme is proposed and its applications in federated learning are demonstrated. The DTAHE scheme saves communication bandwidth compared to other lattice-based DTAHE schemes. Two secure aggregation protocols are obtained when embedding the scheme into federated learning, one against semi-honest adversary and the other against active adversary using a smart contract in a ledger.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Abderrahmane Nitaj, Willy Susilo, Joseph Tonien
Summary: This paper investigates a specific family of enhanced substitution boxes for the Advanced Encryption Standard. These modified S-boxes have the maximal periodicity property, with each input having the maximum orbit length of 256. The parameters for achieving this maximal periodicity property are completely determined. The new enhanced S-boxes also exhibit improved bit avalanche property.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Lifei Wei, Jihai Liu, Lei Zhang, Qin Wang, Wuji Zhang, Xiansong Qian
Summary: Private set intersection (PSI) is widely studied for preserving privacy in collaborative data analytics. However, existing multi-party PSI (MP-PSI) protocols often face performance and scalability issues when the number of participants increases. To address this, we propose two efficient MP-PSI protocols for scenarios with a large number of participants and small set size.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
A. Noorian
Summary: This paper proposes a novel personalized sequential recommendation model, BERTSeqHybrid, which utilizes Bidirectional Encoder Representations from Transformers (BERT) to improve user-user similarity model. The model also employs asymmetric schemas and topic modeling to enhance contextual data from Points of Interest (POIs). Furthermore, a novel method for evaluating user preferences utilizing explicit demographic data is proposed to solve the cold start problem. Experimental evaluation demonstrates the superiority of the developed methodology in terms of RMSE, F-Score, MAP, and NDCG indexes on two different datasets (Yelp and Flickr).
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Amjad Rehman, Ibrahim Abunadi, Khalid Haseeb, Tanzila Saba, Jaime Lloret
Summary: Artificial intelligence (AI) is experiencing significant growth in the areas of smart cities, agriculture, food management, and weather forecasting, primarily due to the limitations of computing power on sensing devices. The integration of AI with IoT and ubiquitous sensors has led to improvements in the agricultural sector and reduced management costs. However, optimizing resource management and data load for forwarding nodes near edge boundaries remains a challenging issue due to limited wireless technology resources.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Leixiao Cheng, Jing Qin, Fei Meng
Summary: This paper analyzes the vulnerability of existing CLPASE schemes to frequency analysis, which compromises user's search privacy. A concrete CLPASE scheme against frequency analysis is proposed, which provides higher guarantee for user's search privacy with comparable efficiency compared to previous schemes.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Yanmei Cao, Jianghong Wei, Yang Xiang, Willy Susilo, Xiaofeng Chen
Summary: Deniable encryption (DE) allows private communication even when adversaries force participants to reveal their secret keys. However, existing DE systems do not consider potential abuse by malicious users. This paper proposes an abuse-resistant DE scheme and provides formal definitions and security analysis. The proposed scheme outperforms existing work in terms of functionality and ciphertext rate.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Xiaoyi Yang, Yanqi Zhao, Sufang Zhou, Lianhai Wang
Summary: This paper proposes a lightweight delegated PSI-CA protocol based on multi-point oblivious pseudorandom function and collision-resistant hash function, and utilizes it to build a privacy-preserving contact tracing system. Experimental results show that our system is more practical and advantageous for densely populated areas.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Kaifeng Xiao, Xinjian Chen, Jianye Huang, Hongbo Li, Qiong Huang
Summary: Ordinary encryption techniques cannot meet the needs of comparing, sharing, and classifying data hidden in ciphertexts in the face of growing threats to data security. The advent of the quantum computing era has brought unprecedented challenges to traditional cryptography. Fortunately, a lattice-based PKEET scheme can solve these problems by providing satisfying anti-quantum computing security and resisting OMRA attacks. This paper presents a lattice-based PKE-DET scheme that supports delegated tester function and demonstrates security under the LWE hardness assumption in the standard model. The scheme offers advantages such as high security, delegated tester authorization, and small storage space compared to existing schemes.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Jingwei Lu, Hongbo Li, Jianye Huang, Sha Ma, Man Ho Allen Au, Qiong Huang
Summary: This paper introduces public key encryption with equality test (PKEET) and identity-based encryption with equality test (IBEET) to address the problem of determining whether two ciphertexts contain the same message encrypted with different public keys, without decryption. The proposed IBEET scheme resists offline message recovery attacks (OMRA) and does not require the dual-tester setting or group mechanism. Security is demonstrated through mathematical assumptions, and experiment results show the efficiency of the scheme. From a usability perspective, the paper explains why the scheme is more suitable for healthcare social Apps compared to other OMRA-resistant schemes.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Dun Li, Dezhi Han, Tien-Hsiung Weng, Zibin Zheng, Hongzhi Li, Kuan-Ching Li
Summary: Stablecoins have facilitated the growth of decentralized payments and the emergence of a new generation of payment systems using cryptocurrencies and Blockchain technology. However, the existing research lacks a comprehensive overview of Stablecoins that focuses on their full context, stabilization mechanisms, and payment applicability. This paper provides a thorough summary of the definition, current state, and ecosystem of Stablecoins. It discusses the system structure, stability mechanisms, and their applicability in payment scenarios. The study identifies asset-backed Stablecoins as the most efficient and widely used, while cryptocurrency-backed Stablecoins are more balanced in relation to the original concept. Algorithm-backed Stablecoins show significant potential for development but are hesitant due to the lack of collateral or deposit reserves, making them prone to collapse. The paper concludes by presenting possible future trends for Stablecoins.
COMPUTER STANDARDS & INTERFACES
(2024)
