Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (302)
  • Open Access


    Machine Learning Empowered Security and Privacy Architecture for IoT Networks with the Integration of Blockchain

    Sohaib Latif1,*, M. Saad Bin Ilyas1, Azhar Imran2, Hamad Ali Abosaq3, Abdulaziz Alzubaidi4, Vincent Karovič Jr.5

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 353-379, 2024, DOI:10.32604/iasc.2024.047080

    Abstract The Internet of Things (IoT) is growing rapidly and impacting almost every aspect of our lives, from wearables and healthcare to security, traffic management, and fleet management systems. This has generated massive volumes of data and security, and data privacy risks are increasing with the advancement of technology and network connections. Traditional access control solutions are inadequate for establishing access control in IoT systems to provide data protection owing to their vulnerability to single-point OF failure. Additionally, conventional privacy preservation methods have high latency costs and overhead for resource-constrained devices. Previous machine learning approaches were… More >

  • Open Access


    Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

    Zhenxiang He*, Zhenyu Zhao, Ke Chen, Yanlin Liu

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3023-3045, 2024, DOI:10.32604/cmc.2024.050281

    Abstract The fast-paced development of blockchain technology is evident. Yet, the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem. Conventional smart contract vulnerability detection primarily relies on static analysis tools, which are less efficient and accurate. Although deep learning methods have improved detection efficiency, they are unable to fully utilize the static relationships within contracts. Therefore, we have adopted the advantages of the above two methods, combining feature extraction mode of tools with deep learning techniques. Firstly, we have constructed corresponding feature extraction mode for… More >

  • Open Access


    Towards Blockchain-Based Secure BGP Routing, Challenges and Future Research Directions

    Qiong Yang1, Li Ma1,2,*, Shanshan Tu1, Sami Ullah3, Muhammad Waqas4,5, Hisham Alasmary6

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2035-2062, 2024, DOI:10.32604/cmc.2024.049970

    Abstract Border Gateway Protocol (BGP) is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different destinations. The BGP protocol exhibits security design defects, such as an unconditional trust mechanism and the default acceptance of BGP route announcements from peers by BGP neighboring nodes, easily triggering prefix hijacking, path forgery, route leakage, and other BGP security threats. Meanwhile, the traditional BGP security mechanism, relying on a public key infrastructure, faces issues like a single point of failure and a single point of trust. The decentralization, anti-tampering, and More >

  • Open Access


    Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

    Muhammad Ahmad Nawaz Ul Ghani1, Kun She1,*, Muhammad Arslan Rauf1, Shumaila Khan2, Javed Ali Khan3, Eman Abdullah Aldakheel4, Doaa Sami Khafaga4

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2609-2623, 2024, DOI:10.32604/cmc.2024.049611

    Abstract The use of privacy-enhanced facial recognition has increased in response to growing concerns about data security and privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a variety of industries, including access control, law enforcement, surveillance, and internet communication. However, the growing usage of face recognition technology has created serious concerns about data monitoring and user privacy preferences, especially in context-aware systems. In response to these problems, this study provides a novel framework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain, and distributed computing… More >

  • Open Access


    Blockchain-Based Key Management Scheme Using Rational Secret Sharing

    Xingfan Zhao1, Changgen Peng1,2,*, Weijie Tan2, Kun Niu1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 307-328, 2024, DOI:10.32604/cmc.2024.047975

    Abstract Traditional blockchain key management schemes store private keys in the same location, which can easily lead to security issues such as a single point of failure. Therefore, decentralized threshold key management schemes have become a research focus for blockchain private key protection. The security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset security. The threshold blockchain private key management schemes based on verifiable secret sharing have made some progress, but these schemes do not consider participants’ self-interested behavior, and require trusted nodes to keep private key… More >

  • Open Access


    Cervical Cancer Prediction Empowered with Federated Machine Learning

    Muhammad Umar Nasir1, Omar Kassem Khalil2, Karamath Ateeq3, Bassam SaleemAllah Almogadwy4, M. A. Khan5, Khan Muhammad Adnan6,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 963-981, 2024, DOI:10.32604/cmc.2024.047874

    Abstract Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in the fourth position because of the leading death cause in its premature stages. The cervix which is the lower end of the vagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumor in the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approach uses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer to train… More >

  • Open Access


    A Lightweight, Searchable, and Controllable EMR Sharing Scheme

    Xiaohui Yang, Peiyin Zhao*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1521-1538, 2024, DOI:10.32604/cmc.2024.047666

    Abstract Electronic medical records (EMR) facilitate the sharing of medical data, but existing sharing schemes suffer from privacy leakage and inefficiency. This article proposes a lightweight, searchable, and controllable EMR sharing scheme, which employs a large attribute domain and a linear secret sharing structure (LSSS), the computational overhead of encryption and decryption reaches a lightweight constant level, and supports keyword search and policy hiding, which improves the high efficiency of medical data sharing. The dynamic accumulator technology is utilized to enable data owners to flexibly authorize or revoke the access rights of data visitors to the More >

  • Open Access


    An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve Data Availability in the Context of Big Data

    Linlin Yuan1,2, Tiantian Zhang1,3, Yuling Chen1,*, Yuxiang Yang1, Huang Li1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1561-1579, 2024, DOI:10.32604/cmc.2023.046907

    Abstract The development of technologies such as big data and blockchain has brought convenience to life, but at the same time, privacy and security issues are becoming more and more prominent. The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’ privacy by anonymizing big data. However, the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability. In addition, ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced. Based… More >

  • Open Access


    Computing Resource Allocation for Blockchain-Based Mobile Edge Computing

    Wanbo Zhang1, Yuqi Fan1, Jun Zhang1, Xu Ding2,*, Jung Yoon Kim3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 863-885, 2024, DOI:10.32604/cmes.2024.047295

    Abstract Users and edge servers are not fully mutually trusted in mobile edge computing (MEC), and hence blockchain can be introduced to provide trustable MEC. In blockchain-based MEC, each edge server functions as a node in both MEC and blockchain, processing users’ tasks and then uploading the task related information to the blockchain. That is, each edge server runs both users’ offloaded tasks and blockchain tasks simultaneously. Note that there is a trade-off between the resource allocation for MEC and blockchain tasks. Therefore, the allocation of the resources of edge servers to the blockchain and the… More >

  • Open Access


    Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

    Umer Nauman1, Yuhong Zhang2, Zhihui Li3, Tong Zhen1,3,*

    Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 15-34, 2024, DOI:10.32604/jimh.2024.048784

    Abstract The convergence of handheld devices and cloud-based computing has transformed how Electronic Health Records (EHRs) are stored in mobile cloud paradigms, offering benefits such as affordability, adaptability, and portability. However, it also introduces challenges regarding network security and data confidentiality, as it aims to exchange EHRs among mobile users while maintaining high levels of security. This study proposes an innovative blockchain-based solution to these issues and presents secure cloud storage for healthcare data. To provide enhanced cryptography, the proposed method combines an enhanced Blowfish encryption method with a new key generation technique called Elephant Herding… More >

Displaying 1-10 on page 1 of 302. Per Page