Azar Abid Salih^1,*, Maiwan Bahjat Abdulrazaq²

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1275-1295, 2024, DOI:10.32604/cmc.2023.046101

Abstract Cyberspace is extremely dynamic, with new attacks arising daily. Protecting cybersecurity controls is vital for network security. Deep Learning (DL) models find widespread use across various fields, with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and hosts. The capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic patterns. This study presents novel lightweight DL models, known as Cybernet models, for the detection and recognition of various cyber Distributed Denial of Service (DDoS) attacks. These models were constructed to have a reasonable number… More >

Gul Nawaz¹, Muhammad Junaid¹, Adnan Akhunzada², Abdullah Gani^2,*, Shamyla Nawazish³, Asim Yaqub³, Adeel Ahmed¹, Huma Ajab⁴

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2157-2178, 2023, DOI:10.32604/cmc.2023.026952

Abstract Distributed denial of service (DDoS) attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user. We proposed a deep neural network (DNN) model for the detection of DDoS attacks in the Software-Defined Networking (SDN) paradigm. SDN centralizes the control plane and separates it from the data plane. It simplifies a network and eliminates vendor specification of a device. Because of this open nature and centralized control, SDN can easily become a victim of DDoS attacks. We proposed a supervised Developed Deep Neural Network (DDNN) model that can classify the DDoS attack traffic… More >

Abdelwahed Berguiga^1,2,*, Ahlem Harchay^1,2, Ayman Massaoudi^1,2, Mossaad Ben Ayed³, Hafedh Belmabrouk⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 379-402, 2023, DOI:10.32604/cmc.2023.041667

Abstract Smart Agriculture, also known as Agricultural 5.0, is expected to be an integral part of our human lives to reduce the cost of agricultural inputs, increasing productivity and improving the quality of the final product. Indeed, the safety and ongoing maintenance of Smart Agriculture from cyber-attacks are vitally important. To provide more comprehensive protection against potential cyber-attacks, this paper proposes a new deep learning-based intrusion detection system for securing Smart Agriculture. The proposed Intrusion Detection System IDS, namely GMLP-IDS, combines the feedforward neural network Multilayer Perceptron (MLP) and the Gaussian Mixture Model (GMM) that can better protect the Smart Agriculture… More >

Adnan Hasan Bdair Aighuraibawi^1,2, Selvakumar Manickam^1,*, Rosni Abdullah³, Zaid Abdi Alkareem Alyasseri^4,5, Ayman Khallel⁶, Dilovan Asaad Zebari⁹, Hussam Mohammed Jasim⁷, Mazin Mohammed Abed⁸, Zainb Hussein Arif⁷

Computer Systems Science and Engineering, Vol.47, No.1, pp. 553-574, 2023, DOI:10.32604/csse.2023.037948

Abstract Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system… More >

Anitha Thangasamy^*, Bose Sundan, Logeswari Govindaraj

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2553-2567, 2023, DOI:10.32604/csse.2023.032078

Abstract The recent development of cloud computing offers various services on demand for organization and individual users, such as storage, shared computing space, networking, etc. Although Cloud Computing provides various advantages for users, it remains vulnerable to many types of attacks that attract cyber criminals. Distributed Denial of Service (DDoS) is the most common type of attack on cloud computing. Consequently, Cloud computing professionals and security experts have focused on the growth of preventive processes towards DDoS attacks. Since DDoS attacks have become increasingly widespread, it becomes difficult for some DDoS attack methods based on individual network flow features to distinguish… More >

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 for this type of attack… More >

Jieren Cheng^1,2, Xinzhi Yao^1,2,*, Hui Li³, Hao Lu⁴, Naixue Xiong⁵, Ping Luo^1,2, Le Liu^1,2, Hao Guo^1,2, Wen Feng^1,2

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 uploads the encrypted model to… More >

Isha Sood^*, Varsha Sharma

Journal of Cyber Security, Vol.3, No.2, pp. 89-106, 2021, DOI:10.32604/jcs.2021.018623

Abstract The Internet is often targeted by the Distributed Denial of Service (DDOS) Attacks that deliberately utilize resources and bandwidth to prohibit access to potential users. The attack possibility is that the packets are filled massively. A DOS attack is launched by a single source, while a DDOS attack is originated from numerous resources. DDoS attacks are not capable of stealing website user’s information. The prime motive of the DDoS attacks is to devastate the website resources. Distributed Denial of Service (DDoS) attacks are disruptive to internet access on the Network. The attitude of the customer to get fast and reliable… More >

Mohammad Aladaileh¹, Mohammed Anbar^1,*, Iznan H. Hasbullah¹, Yousef K. Sanjalawe^1,2, Yung-Wey Chong¹

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 373-391, 2021, DOI:10.32604/cmc.2021.017972

Abstract The Software-Defined Networking (SDN) technology improves network management over existing technology via centralized network control. The SDN provides a perfect platform for researchers to solve traditional network’s outstanding issues. However, despite the advantages of centralized control, concern about its security is rising. The more traditional network switched to SDN technology, the more attractive it becomes to malicious actors, especially the controller, because it is the network’s brain. A Distributed Denial of Service (DDoS) attack on the controller could cripple the entire network. For that reason, researchers are always looking for ways to detect DDoS attacks against the controller with higher… More >

Muhammad Reazul Haque¹, Saw Chin Tan¹, Zulfadzli Yusoff^2,*, Kashif Nisar^3,5,6, Lee Ching Kwang^2,7, Rizaludin Kaspin⁴, Bhawani Shankar Chowdhry⁵, Rajkumar Buyya⁸, Satya Prasad Majumder⁹, Manoj Gupta¹⁰, Shuaib Memon¹¹

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3147-3165, 2021, DOI:10.32604/cmc.2021.016591

Abstract In software-defined networks (SDNs), controller placement is a critical factor in the design and planning for the future Internet of Things (IoT), telecommunication, and satellite communication systems. Existing research has concentrated largely on factors such as reliability, latency, controller capacity, propagation delay, and energy consumption. However, SDNs are vulnerable to distributed denial of service (DDoS) attacks that interfere with legitimate use of the network. The ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design, especially in critical applications such as military, health care, and financial services networks requiring high availability. We propose a mathematical… More >