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  • Open Access

    ARTICLE

    FFRA: A Fine-Grained Function-Level Framework to Reduce the Attack Surface

    Xingxing Zhang1, Liang Liu1,*, Yu Fan1, Qian Zhou2

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 969-987, 2024, DOI:10.32604/csse.2024.046615 - 17 July 2024

    Abstract System calls are essential interfaces that enable applications to access and utilize the operating system’s services and resources. Attackers frequently exploit application’s vulnerabilities and misuse system calls to execute malicious code, aiming to elevate privileges and so on. Consequently, restricting the misuse of system calls becomes a crucial measure in ensuring system security. It is an effective method known as reducing the attack surface. Existing attack surface reduction techniques construct a global whitelist of system calls for the entire lifetime of the application, which is coarse-grained. In this paper, we propose a Fine-grained Function-level framework… More >

  • Open Access

    ARTICLE

    Covalent Bond Based Android Malware Detection Using Permission and System Call Pairs

    Rahul Gupta1, Kapil Sharma1,*, R. K. Garg2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4283-4301, 2024, DOI:10.32604/cmc.2024.046890 - 26 March 2024

    Abstract The prevalence of smartphones is deeply embedded in modern society, impacting various aspects of our lives. Their versatility and functionalities have fundamentally changed how we communicate, work, seek entertainment, and access information. Among the many smartphones available, those operating on the Android platform dominate, being the most widely used type. This widespread adoption of the Android OS has significantly contributed to increased malware attacks targeting the Android ecosystem in recent years. Therefore, there is an urgent need to develop new methods for detecting Android malware. The literature contains numerous works related to Android malware detection.… More >

  • Open Access

    ARTICLE

    An Asset-Based Approach to Mitigate Zero-Day Ransomware Attacks

    Farag Azzedin*, Husam Suwad, Md Mahfuzur Rahman

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3003-3020, 2022, DOI:10.32604/cmc.2022.028646 - 16 June 2022

    Abstract This article presents an asset-based security system where security practitioners build their systems based on information they own and not solicited by observing attackers’ behavior. Current security solutions rely on information coming from attackers. Examples are current monitoring and detection security solutions such as intrusion prevention/detection systems and firewalls. This article envisions creating an imbalance between attackers and defenders in favor of defenders. As such, we are proposing to flip the security game such that it will be led by defenders and not attackers. We are proposing a security system that does not observe the… More >

  • Open Access

    ARTICLE

    Malware Detection Based on Multidimensional Time Distribution Features

    Huizhong Sun1, Guosheng Xu1,*, Hewei Yu2, Minyan Ma3, Yanhui Guo1, Ruijie Quan4

    Journal of Quantum Computing, Vol.3, No.2, pp. 55-63, 2021, DOI:10.32604/jqc.2021.017365 - 22 June 2021

    Abstract Language detection models based on system calls suffer from certain false negatives and detection blind spots. Hence, the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window. To detect such behaviors, we extract a multidimensional time distribution feature matrix on the basis of statistical analysis. This matrix mainly includes multidimensional time distribution features, multidimensional word pair correlation features, and multidimensional word frequency distribution features. A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given More >

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