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  • Open Access


    Optimal Deep Learning Based Ransomware Detection and Classification in the Internet of Things Environment

    Manal Abdullah Alohali1, Muna Elsadig1, Fahd N. Al-Wesabi2, Mesfer Al Duhayyim3, Anwer Mustafa Hilal4,*, Abdelwahed Motwakel4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3087-3102, 2023, DOI:10.32604/csse.2023.036802

    Abstract With the advent of the Internet of Things (IoT), several devices like sensors nowadays can interact and easily share information. But the IoT model is prone to security concerns as several attackers try to hit the network and make it vulnerable. In such scenarios, security concern is the most prominent. Different models were intended to address these security problems; still, several emergent variants of botnet attacks like Bashlite, Mirai, and Persirai use security breaches. The malware classification and detection in the IoT model is still a problem, as the adversary reliably generates a new variant of IoT malware and actively… More >

  • Open Access


    Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection

    Khaled M. Alalayah1, Fatma S. Alrayes2, Mohamed K. Nour3, Khadija M. Alaidarous1, Ibrahim M. Alwayle1, Heba Mohsen4, Ibrahim Abdulrab Ahmed5, Mesfer Al Duhayyim6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3103-3119, 2023, DOI:10.32604/csse.2023.034034

    Abstract Malware is a ‘malicious software program that performs multiple cyberattacks on the Internet, involving fraud, scams, nation-state cyberwar, and cybercrime. Such malicious software programs come under different classifications, namely Trojans, viruses, spyware, worms, ransomware, Rootkit, botnet malware, etc. Ransomware is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it; then, the user pays a ransom procedure of a sum of money. To prevent detection, various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine… More >

  • Open Access


    Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

    Mesfer Al Duhayyim1,*, Heba G. Mohamed2, Fadwa Alrowais3, Fahd N. Al-Wesabi4, Anwer Mustafa Hilal5, Abdelwahed Motwakel5

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1293-1310, 2023, DOI:10.32604/csse.2023.035589

    Abstract The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations.… More >

  • Open Access


    A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

    R. T. Pavendan1,*, K. Sankar1, K. A. Varun Kumar2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3331-3348, 2023, DOI:10.32604/iasc.2023.028029

    Abstract Attacks on the cyber space is getting exponential in recent times. Illegal penetrations and breaches are real threats to the individuals and organizations. Conventional security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats (APTs) they fails. These APTs are targeted, more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing defenses. Hence, there is a need for an effective defense system that can achieve a complete reliance of security. To address the above-mentioned issues, this paper proposes a novel honeypot system that tracks the anonymous behavior… More >

  • Open Access


    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

    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 behavior of the attack. On… More >

  • Open Access


    Ransomware Classification Framework Using the Behavioral Performance Visualization of Execution Objects

    Jun-Seob Kim, Ki-Woong Park*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3401-3424, 2022, DOI:10.32604/cmc.2022.026621

    Abstract A ransomware attack that interrupted the operation of Colonial Pipeline (a large U.S. oil pipeline company), showed that security threats by malware have become serious enough to affect industries and social infrastructure rather than individuals alone. The agents and characteristics of attacks should be identified, and appropriate strategies should be established accordingly in order to respond to such attacks. For this purpose, the first task that must be performed is malware classification. Malware creators are well aware of this and apply various concealment and avoidance techniques, making it difficult to classify malware. This study focuses on new features and classification… More >

  • Open Access


    Novel Ransomware Hiding Model Using HEVC Steganography Approach

    Iman Almomani1,2,*, Aala AlKhayer1, Walid El-Shafai1,3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1209-1228, 2022, DOI:10.32604/cmc.2022.018631

    Abstract Ransomware is considered one of the most threatening cyberattacks. Existing solutions have focused mainly on discriminating ransomware by analyzing the apps themselves, but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then analyzed. Therefore, this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding (HEVC) steganography approach. The main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different blocks. After that, the Least Significant Bit (LSB) based Hamming Distance (HD) calculation is performed amongst the… More >

  • Open Access


    A User-friendly Model for Ransomware Analysis Using Sandboxing

    Akhtar Kamal1, Morched Derbali2, Sadeeq Jan1,*, Javed Iqbal Bangash3, Fazal Qudus Khan2, Houssem Jerbi4, Rabeh Abbassi4, Gulzar Ahmad5

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3833-3846, 2021, DOI:10.32604/cmc.2021.015941

    Abstract Ransomware is a type of malicious software that blocks access to a computer by encrypting user’s files until a ransom is paid to the attacker. There have been several reported high-profile ransomware attacks including WannaCry, Petya, and Bad Rabbit resulting in losses of over a billion dollars to various individuals and businesses in the world. The analysis of ransomware is often carried out via sandbox environments; however, the initial setup and configuration of such environments is a challenging task. Also, it is difficult for an ordinary computer user to correctly interpret the complex results presented in the reports generated by… More >

  • Open Access


    An Immunization Scheme for Ransomware

    Jingping Song1, Qingyu Meng1, Chenke Luo2, Nitin Naik3, Jian Xu1, *

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1051-1061, 2020, DOI:10.32604/cmc.2020.010592

    Abstract In recent years, as the popularity of anonymous currencies such as Bitcoin has made the tracking of ransomware attackers more difficult, the amount of ransomware attacks against personal computers and enterprise production servers is increasing rapidly. The ransomware has a wide range of influence and spreads all over the world. It is affecting many industries including internet, education, medical care, traditional industry, etc. This paper uses the idea of virus immunity to design an immunization solution for ransomware viruses to solve the problems of traditional ransomware defense methods (such as anti-virus software, firewalls, etc.), which cannot meet the requirements of… More >

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