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  • Open Access

    ARTICLE

    Securing Consumer Internet of Things for Botnet Attacks: Deep Learning Approach

    Tariq Ahamed Ahanger1,*, Abdulaziz Aldaej1, Mohammed Atiquzzaman2, Imdad Ullah1, Mohammed Yousuf Uddin1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3199-3217, 2022, DOI:10.32604/cmc.2022.027212

    Abstract DDoS attacks in the Internet of Things (IoT) technology have increased significantly due to its spread adoption in different industrial domains. The purpose of the current research is to propose a novel technique for detecting botnet attacks in user-oriented IoT environments. Conspicuously, an attack identification technique inspired by Recurrent Neural networks and Bidirectional Long Short Term Memory (BLRNN) is presented using a unique Deep Learning (DL) technique. For text identification and translation of attack data segments into tokenized form, word embedding is employed. The performance analysis of the presented technique is performed in comparison to More >

  • Open Access

    ARTICLE

    Iterative Dichotomiser Posteriori Method Based Service Attack Detection in Cloud Computing

    B. Dhiyanesh1,*, K. Karthick2, R. Radha3, Anita Venaik4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1099-1107, 2023, DOI:10.32604/csse.2023.024691

    Abstract Cloud computing (CC) is an advanced technology that provides access to predictive resources and data sharing. The cloud environment represents the right type regarding cloud usage model ownership, size, and rights to access. It introduces the scope and nature of cloud computing. In recent times, all processes are fed into the system for which consumer data and cache size are required. One of the most security issues in the cloud environment is Distributed Denial of Service (DDoS) attacks, responsible for cloud server overloading. This proposed system ID3 (Iterative Dichotomiser 3) Maximum Multifactor Dimensionality Posteriori Method… More >

  • Open Access

    ARTICLE

    Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm

    R. S. Aashmi1, T. Jaya2,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 79-95, 2023, DOI:10.32604/iasc.2023.024291

    Abstract

    Cloud computing is the technology that is currently used to provide users with infrastructure, platform, and software services effectively. Under this system, Platform as a Service (PaaS) offers a medium headed for a web development platform that uniformly distributes the requests and resources. Hackers using Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks abruptly interrupt these requests. Even though several existing methods like signature-based, statistical anomaly-based, and stateful protocol analysis are available, they are not sufficient enough to get rid of Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks

    More >

  • Open Access

    ARTICLE

    Detection of DDoS Attack in IoT Networks Using Sample Selected RNN-ELM

    S. Hariprasad1,*, T. Deepa1, N. Bharathiraja2

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1425-1440, 2022, DOI:10.32604/iasc.2022.022856

    Abstract The Internet of Things (IoT) is a global information and communication technology which aims to connect any type of device to the internet at any time and in any location. Nowadays billions of IoT devices are connected to the world, this leads to easily cause vulnerability to IoT devices. The increasing of users in different IoT-related applications leads to more data attacks is happening in the IoT networks after the fog layer. To detect and reduce the attacks the deep learning model is used. In this article, a hybrid sample selected recurrent neural network-extreme learning… More >

  • Open Access

    ARTICLE

    Dynamic Threshold-Based Approach to Detect Low-Rate DDoS Attacks on Software-Defined Networking Controller

    Mohammad Adnan Aladaileh, Mohammed Anbar*, Iznan H. Hasbullah, Abdullah Ahmed Bahashwan, Shadi Al-Sarawn

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1403-1416, 2022, DOI:10.32604/cmc.2022.029369

    Abstract The emergence of a new network architecture, known as Software Defined Networking (SDN), in the last two decades has overcome some drawbacks of traditional networks in terms of performance, scalability, reliability, security, and network management. However, the SDN is vulnerable to security threats that target its controller, such as low-rate Distributed Denial of Service (DDoS) attacks, The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component. Therefore, there is an urgent need to propose a detection approach… More >

  • Open Access

    ARTICLE

    Comprehensive DDoS Attack Classification Using Machine Learning Algorithms

    Olga Ussatova1,2, Aidana Zhumabekova1,*, Yenlik Begimbayeva2,3, Eric T. Matson4, Nikita Ussatov5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 577-594, 2022, DOI:10.32604/cmc.2022.026552

    Abstract The fast development of Internet technologies ignited the growth of techniques for information security that protect data, networks, systems, and applications from various threats. There are many types of threats. The dedicated denial of service attack (DDoS) is one of the most serious and widespread attacks on Internet resources. This attack is intended to paralyze the victim's system and cause the service to fail. This work is devoted to the classification of DDoS attacks in the special network environment called Software-Defined Networking (SDN) using machine learning algorithms. The analyzed dataset included instances of two classes:… More >

  • Open Access

    ARTICLE

    Adaptive Polling Rate for SNMP for Detecting Elusive DDOS

    Yichiet Aun*, Yen-Min Jasmina Khaw, Ming-Lee Gan, Vasaki Ponnusamy

    Journal of Cyber Security, Vol.4, No.1, pp. 17-28, 2022, DOI:10.32604/jcs.2022.027524

    Abstract Resilient network infrastructure is pivotal for business entities that are growing reliance on the Internet. Distributed Denial-of-Service (DDOS) is a common network threat that collectively overwhelms and exhausts network resources using coordinated botnets to interrupt access to network services, devices, and resources. IDS is typically deployed to detect DDOS based on Snort rules. Although being fairly accurate, IDS operates on a compute-intensive packet inspection technique and lacks rapid DDOS detection. Meanwhile, SNMP is a comparably lightweight countermeasure for fast detection. However, this SNMP trigger is often circumvented if the DDOS burst rate is coordinated to… More >

  • Open Access

    ARTICLE

    Early DDoS Detection and Prevention with Traced-Back Blocking in SDN Environment

    Sriramulu Bojjagani1, D. R. Denslin Brabin2,*, K. Saravanan2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 805-819, 2022, DOI:10.32604/iasc.2022.023771

    Abstract The flow of information is a valuable asset for every company and its consumers, and Distributed Denial-of-Service (DDoS) assaults pose a substantial danger to this flow. If we do not secure security, hackers may steal information flowing across a network, posing a danger to a business and society. As a result, the most effective ways are necessary to deal with the dangers. A DDoS attack is a well-known network infrastructure assault that prevents servers from servicing genuine customers. It is necessary to identify and block a DDoS assault before it reaches the server in order… More >

  • Open Access

    ARTICLE

    Machine Learning with Dimensionality Reduction for DDoS Attack Detection

    Shaveta Gupta1, Dinesh Grover2, Ahmad Ali AlZubi3,*, Nimit Sachdeva4, Mirza Waqar Baig5, Jimmy Singla6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2665-2682, 2022, DOI:10.32604/cmc.2022.025048

    Abstract With the advancement of internet, there is also a rise in cybercrimes and digital attacks. DDoS (Distributed Denial of Service) attack is the most dominant weapon to breach the vulnerabilities of internet and pose a significant threat in the digital environment. These cyber-attacks are generated deliberately and consciously by the hacker to overwhelm the target with heavy traffic that genuine users are unable to use the target resources. As a result, targeted services are inaccessible by the legitimate user. To prevent these attacks, researchers are making use of advanced Machine Learning classifiers which can accurately… More >

  • Open Access

    ARTICLE

    Cooperative Detection Method for DDoS Attacks Based on Blockchain

    Jieren Cheng1,2, Xinzhi Yao1,2,*, Hui Li3, Hao Lu4, Naixue Xiong5, Ping Luo1,2, Le Liu1,2, Hao Guo1,2, Wen Feng1,2

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 103-117, 2022, DOI:10.32604/csse.2022.025668

    Abstract Distributed Denial of Service (DDoS) attacks is always one of the major problems for service providers. Using blockchain to detect DDoS attacks is one of the current popular methods. However, the problems of high time overhead and cost exist in the most of the blockchain methods for detecting DDoS attacks. This paper proposes a blockchain-based collaborative detection method for DDoS attacks. First, the trained DDoS attack detection model is encrypted by the Intel Software Guard Extensions (SGX), which provides high security for uploading the DDoS attack detection model to the blockchain. Secondly, the service provider… More >

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