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  • Open Access

    ARTICLE

    A Novel Post-Quantum Blind Signature for Log System in Blockchain

    Gang Xu1,2, Yibo Cao1, Shiyuan Xu1, Ke Xiao1, Xin Liu3, Xiubo Chen4,*, Mianxiong Dong5

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 945-958, 2022, DOI:10.32604/csse.2022.022100

    Abstract In recent decades, log system management has been widely studied for data security management. System abnormalities or illegal operations can be found in time by analyzing the log and provide evidence for intrusions. In order to ensure the integrity of the log in the current system, many researchers have designed it based on blockchain. However, the emerging blockchain is facing significant security challenges with the increment of quantum computers. An attacker equipped with a quantum computer can extract the user's private key from the public key to generate a forged signature, destroy the structure of the blockchain, and threaten the… More >

  • Open Access

    Fed-DFE: A Decentralized Function Encryption-Based Privacy-Preserving Scheme for Federated Learning

    Zhe Sun1, Jiyuan Feng1, Lihua Yin1,*, Zixu Zhang2, Ran Li1, Yu Hu1, Chongning Na3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1867-1886, 2022, DOI:10.32604/cmc.2022.022290

    Abstract Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data. However, the training mechanism for passing model parameters is still threatened by gradient inversion, inference attacks, etc. With a lightweight encryption overhead, function encryption is a viable secure aggregation technique in federation learning, which is often used in combination with differential privacy. The function encryption in federal learning still has the following problems: a) Traditional function encryption usually requires a trust third party (TTP) to assign the keys. If a TTP colludes with a server, the security aggregation mechanism can be… More >

  • Open Access

    ARTICLE

    Dynamic Automated Infrastructure for Efficient Cloud Data Centre

    R. Dhaya1,*, R. Kanthavel2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1625-1639, 2022, DOI:10.32604/cmc.2022.022213

    Abstract We propose a dynamic automated infrastructure model for the cloud data centre which is aimed as an efficient service stipulation for the enormous number of users. The data center and cloud computing technologies have been at the moment rendering attention to major research and development efforts by companies, governments, and academic and other research institutions. In that, the difficult task is to facilitate the infrastructure to construct the information available to application-driven services and make business-smart decisions. On the other hand, the challenges that remain are the provision of dynamic infrastructure for applications and information anywhere. Further, developing technologies to… More >

  • Open Access

    ARTICLE

    Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing

    A. S. Anakath1,*, R. Kannadasan2, Niju P. Joseph3, P. Boominathan4, G. R. Sreekanth5

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 479-492, 2022, DOI:10.32604/csse.2022.019940

    Abstract Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider in the network, they will… More >

  • Open Access

    ARTICLE

    Towards Securing Machine Learning Models Against Membership Inference Attacks

    Sana Ben Hamida1,2, Hichem Mrabet3,4, Sana Belguith5,*, Adeeb Alhomoud6, Abderrazak Jemai7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4897-4919, 2022, DOI:10.32604/cmc.2022.019709

    Abstract From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to different security and privacy attacks. Hence, these issues should be addressed while using ML models to preserve the security and privacy of the data used. There is a need to secure ML models, especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage. In this paper, we present an overview of ML threats and vulnerabilities, and we highlight current progress… More >

  • Open Access

    Preserving Privacy of User Identity Based on Pseudonym Variable in 5G

    Mamoon M. Saeed1, Mohammad Kamrul Hasan2,*, Rosilah Hassan2 , Rania Mokhtar3 , Rashid A. Saeed3,4, Elsadig Saeid1, Manoj Gupta5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5551-5568, 2022, DOI:10.32604/cmc.2022.017338

    Abstract

    The fifth generation (5G) system is the forthcoming generation of the mobile communication system. It has numerous additional features and offers an extensively high data rate, more capacity, and low latency. However, these features and applications have many problems and issues in terms of security, which has become a great challenge in the telecommunication industry. This paper aimed to propose a solution to preserve the user identity privacy in the 5G system that can identify permanent identity by using Variable Mobile Subscriber Identity, which randomly changes and does not use the permanent identity between the user equipment and home network.… More >

  • Open Access

    ARTICLE

    TAR-AFT: A Framework to Secure Shared Cloud Data with Group Management

    K. Ambika1,*, M. Balasingh Moses2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1809-1823, 2022, DOI:10.32604/iasc.2022.018580

    Abstract In addition to replacing desktop-based methods, cloud computing is playing a significant role in several areas of data management. The health care industry, where so much data is needed to be handled correctly, is another arena in which artificial intelligence has a big role to play. The upshot of this innovation led to the creation of multiple healthcare clouds. The challenge of data privacy and confidentiality is the same for different clouds. Many existing works has provided security framework to ensure the security of data in clouds but still the drawback on revocation, resisting collusion attack along with privacy of… More >

  • Open Access

    ARTICLE

    MIA-UNet: Multi-Scale Iterative Aggregation U-Network for Retinal Vessel Segmentation

    Linfang Yu, Zhen Qin*, Yi Ding, Zhiguang Qin

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 805-828, 2021, DOI:10.32604/cmes.2021.017332

    Abstract As an important part of the new generation of information technology, the Internet of Things (IoT) has been widely concerned and regarded as an enabling technology of the next generation of health care system. The fundus photography equipment is connected to the cloud platform through the IoT, so as to realize the real-time uploading of fundus images and the rapid issuance of diagnostic suggestions by artificial intelligence. At the same time, important security and privacy issues have emerged. The data uploaded to the cloud platform involves more personal attributes, health status and medical application data of patients. Once leaked, abused… More >

  • Open Access

    ARTICLE

    Cross-Layer Hidden Markov Analysis for Intrusion Detection

    K. Venkatachalam1, P. Prabu2, B. Saravana Balaji3, Byeong-Gwon Kang4, Yunyoung Nam4,*, Mohamed Abouhawwash5,6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502

    Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based on intrusion… More >

  • Open Access

    ARTICLE

    Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

    Jinsu Kim1, Sungwook Ryu2, Namje Park1,3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277

    Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, the file uploader list cannot… More >

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