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  • Open Access

    ARTICLE

    An Enhanced Privacy Preserving, Secure and Efficient Authentication Protocol for VANET

    Safiullah Khan1, Ali Raza2,3, Seong Oun Hwang4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3703-3719, 2022, DOI:10.32604/cmc.2022.023476 - 07 December 2021

    Abstract Vehicular ad hoc networks (VANETs) have attracted growing interest in both academia and industry because they can provide a viable solution that improves road safety and comfort for travelers on roads. However, wireless communications over open-access environments face many security and privacy issues that may affect deployment of large-scale VANETs. Researchers have proposed different protocols to address security and privacy issues in a VANET, and in this study we cryptanalyze some of the privacy preserving protocols to show that all existing protocols are vulnerable to the Sybil attack. The Sybil attack can be used by… More >

  • Open Access

    ARTICLE

    Robust Reversible Audio Watermarking Scheme for Telemedicine and Privacy Protection

    Xiaorui Zhang1,2,*, Xun Sun1, Xingming Sun1, Wei Sun3, Sunil Kumar Jha4

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3035-3050, 2022, DOI:10.32604/cmc.2022.022304 - 07 December 2021

    Abstract The leakage of medical audio data in telemedicine seriously violates the privacy of patients. In order to avoid the leakage of patient information in telemedicine, a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data. The scheme decomposes the medical audio into two independent embedding domains, embeds the robust watermark and the reversible watermark into the two domains respectively. In order to ensure the audio quality, the Hurst exponent is used to find a suitable position for watermark embedding. Due to the independence of the two embedding domains, the embedding of… More >

  • 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 - 10 November 2021

    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… 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 - 03 November 2021

    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… 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 - 03 November 2021

    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 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 - 25 October 2021

    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… 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 - 11 October 2021

    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,… 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 - 11 October 2021

    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

    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 - 09 October 2021

    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… 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 - 27 September 2021

    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… More >

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