Yousef Sanjalawe^1,2,*, Turke Althobaiti^3,4

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3571-3588, 2023, DOI:10.32604/cmc.2023.037386

Abstract Intrusion Detection System (IDS) in the cloud Computing (CC) environment has received paramount interest over the last few years. Among the latest approaches, Deep Learning (DL)-based IDS methods allow the discovery of attacks with the highest performance. In the CC environment, Distributed Denial of Service (DDoS) attacks are widespread. The cloud services will be rendered unavailable to legitimate end-users as a consequence of the overwhelming network traffic, resulting in financial losses. Although various researchers have proposed many detection techniques, there are possible obstacles in terms of detection performance due to the use of insignificant traffic features. Therefore, in this paper,… More >

Emad Alsuwat^1,*, Suhare Solaiman¹, Hatim Alsuwat²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3743-3759, 2023, DOI:10.32604/cmc.2023.035126

Abstract Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning (ML) models. Due to attackers’ (and/or benign equivalents’) dynamic behavior changes, testing data distribution frequently diverges from original training data over time, resulting in substantial model failures. Due to their dispersed and dynamic nature, distributed denial-of-service attacks pose a danger to cybersecurity, resulting in attacks with serious consequences for users and businesses. This paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of Service (DDOS) in the network.… 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 >

M. Revathi, V. V. Ramalingam^*, B. Amutha

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3023-3036, 2023, DOI:10.32604/csse.2023.033600

Abstract The impact of a Distributed Denial of Service (DDoS) attack on Software Defined Networks (SDN) is briefly analyzed. Many approaches to detecting DDoS attacks exist, varying on the feature being considered and the method used. Still, the methods have a deficiency in the performance of detecting DDoS attacks and mitigating them. To improve the performance of SDN, an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model (RMCARTAM) is sketched in this article. The RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming packets. The model is designed with multiple controllers to handle network traffic… More >

S. Rameshkumar^1,*, R. Ganesan², A. Merline¹

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2379-2394, 2023, DOI:10.32604/csse.2023.027910

Abstract In The Wireless Multimedia Sensor Network (WNSMs) have achieved popularity among diverse communities as a result of technological breakthroughs in sensor and current gadgets. By utilising portable technologies, it achieves solid and significant results in wireless communication, media transfer, and digital transmission. Sensor nodes have been used in agriculture and industry to detect characteristics such as temperature, moisture content, and other environmental conditions in recent decades. WNSMs have also made apps easier to use by giving devices self-governing access to send and process data connected with appropriate audio and video information. Many video sensor network studies focus on lowering power… More >

Magdy M. Fadel^1,*, Sally M. El-Ghamrawy², Amr M. T. Ali-Eldin¹, Mohammed K. Hassan³, Ali I. El-Desoky¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2293-2312, 2022, DOI:10.32604/cmc.2022.028287

Abstract Distributed denial-of-service (DDoS) attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks. Furthermore, the enormous number of connected devices makes it difficult to operate such a network effectively. Software defined networks (SDN) are networks that are managed through a centralized control system, according to researchers. This controller is the brain of any SDN, composing the forwarding table of all data plane network switches. Despite the advantages of SDN controllers, DDoS attacks are easier to perpetrate than on traditional networks. Because the controller is a single point of failure, if it fails, the… More >

Tariq Ahamed Ahanger^1,*, 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 the state-of-the-art DL techniques. Specifically,… More >

B. Dhiyanesh^1,*, 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 (ID3-MMDP) is used to overcome… More >

R. S. Aashmi¹, T. Jaya^2,*

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 and hence there is a… More >

S. Hariprasad^1,*, 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 machine (hybrid SSRNN-ELM) algorithm that… More >