G. Nagalalli^*, G. Ravi

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 475-490, 2023, DOI:10.32604/iasc.2023.026571

Abstract Wireless Sensor Network (WSN), which finds as one of the major components of modern electronic and wireless systems. A WSN consists of numerous sensor nodes for the discovery of sensor networks to leverage features like data sensing, data processing, and communication. In the field of medical health care, these network plays a very vital role in transmitting highly sensitive data from different geographic regions and collecting this information by the respective network. But the fear of different attacks on health care data typically increases day by day. In a very short period, these attacks may cause adversarial effects to the… More >

Masoud Alajmi¹, Mohamed K. Nour², Siwar Ben Haj Hassine³, Mimouna Abdullah Alkhonaini⁴, Manar Ahmed Hamza^5,*, Ishfaq Yaseen⁵, Abu Sarwar Zamani⁵, Mohammed Rizwanullah⁵

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5499-5513, 2022, DOI:10.32604/cmc.2022.026187

Abstract Recently, cyber physical system (CPS) has gained significant attention which mainly depends upon an effective collaboration with computation and physical components. The greatly interrelated and united characteristics of CPS resulting in the development of cyber physical energy systems (CPES). At the same time, the rising ubiquity of wireless sensor networks (WSN) in several application areas makes it a vital part of the design of CPES. Since security and energy efficiency are the major challenging issues in CPES, this study offers an energy aware secure cyber physical systems with clustered wireless sensor networks using metaheuristic algorithms (EASCPS-MA). The presented EASCPS-MA technique… More >

S. Karthic^1,*, S. Manoj Kumar²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 439-453, 2022, DOI:10.32604/iasc.2022.025153

Abstract In recent years, due to the rapid progress of various technologies, wireless computer networks have developed. However, the activities of the security threats and attackers affect the data communication of these technologies. So, to protect the network against these security threats, an efficient IDS (Intrusion Detection System) is presented in this paper. Namely, optimized long short-term memory (OLSTM) network with a stacked auto-encoder (SAE) network is proposed as an IDS system. Using SAE, significant features are extracted from the databases such as input NSL-KDD database and the UNSW-NB15 database. Then extracted features are given as input to the optimized LSTM… More >

Abdullah Saad AL-Malaise AL-Ghamdi¹, Mahmoud Ragab^2,3,4,*, Maha Farouk S. Sabir¹, Ahmed Elhassanein^5,6, Ashraf A. Gouda⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3385-3399, 2022, DOI:10.32604/cmc.2022.026477

Abstract Education acts as an important part of economic growth and improvement in human welfare. The educational sectors have transformed a lot in recent days, and Information and Communication Technology (ICT) is an effective part of the education field. Almost every action in university and college, right from the process from counselling to admissions and fee deposits has been automated. Attendance records, quiz, evaluation, mark, and grade submissions involved the utilization of the ICT. Therefore, security is essential to accomplish cybersecurity in higher security institutions (HEIs). In this view, this study develops an Automated Outlier Detection for CyberSecurity in Higher Education… More >

Mohammad Hafiz Mohd Yusof^1,*, Abdullah Mohd Zin², Nurhizam Safie Mohd Satar²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2445-2466, 2022, DOI:10.32604/cmc.2022.023571

Abstract Due to polymorphic nature of malware attack, a signature-based analysis is no longer sufficient to solve polymorphic and stealth nature of malware attacks. On the other hand, state-of-the-art methods like deep learning require labelled dataset as a target to train a supervised model. This is unlikely to be the case in production network as the dataset is unstructured and has no label. Hence an unsupervised learning is recommended. Behavioral study is one of the techniques to elicit traffic pattern. However, studies have shown that existing behavioral intrusion detection model had a few issues which had been parameterized into its common… More >

M. Anuradha^1,*, G. Mani², T. Shanthi³, N. R. Nagarajan⁴, P. Suresh⁵, C. Bharatiraja⁶

Computer Systems Science and Engineering, Vol.43, No.1, pp. 381-396, 2022, DOI:10.32604/csse.2022.023321

Abstract In the digital area, Internet of Things (IoT) and connected objects generate a huge quantity of data traffic which feeds big data analytic models to discover hidden patterns and detect abnormal traffic. Though IoT networks are popular and widely employed in real world applications, security in IoT networks remains a challenging problem. Conventional intrusion detection systems (IDS) cannot be employed in IoT networks owing to the limitations in resources and complexity. Therefore, this paper concentrates on the design of intelligent metaheuristic optimization based feature selection with deep learning (IMFSDL) based classification model, called IMFSDL-IDS for IoT networks. The proposed IMFSDL-IDS… More >

S. Navaneetha Krishnan¹, P. Sundara Vadivel^2,*, D. Yuvaraj³, T. Satyanarayana Murthy⁴, Sree Jagadeesh Malla⁵, S. Nachiyappan⁶, S. Shanmuga Priya⁷

Computer Systems Science and Engineering, Vol.43, No.1, pp. 17-26, 2022, DOI:10.32604/csse.2022.021590

Abstract Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization (MPSO) has… More >

Yoosef B. Abushark¹, Asif Irshad Khan^1,*, Fawaz Alsolami¹, Abdulmohsen Almalawi¹, Md Mottahir Alam², Alka Agrawal³, Rajeev Kumar⁴, Raees Ahmad Khan³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1765-1783, 2022, DOI:10.32604/cmc.2022.025604

Abstract Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the world. Machine learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security issues. It is crucial in offering a proactive security system in the field of cybersecurity. In real time, cybersecurity protects information, information systems, and networks from intruders. In the recent decade, several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity breaches. At an increasing rate, intruders are breaching information security. Anomaly detection, software… More >

M. Maheswari^1,2,*, R. A. Karthika¹

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 365-382, 2022, DOI:10.32604/iasc.2022.022259

Abstract With the advent of wireless communication and digital technology, low power, Internet-enabled, and reconfigurable wireless devices have been developed, which revolutionized day-to-day human life and the economy across the globe. These devices are realized by leveraging the features of sensing, processing the data and nodes communications. The scale of Internet-enabled wireless devices has increased daily, and these devices are exposed to various cyber-attacks. Since the complexity and dynamics of the attacks on the devices are computationally high, intelligent, scalable and high-speed intrusion detection systems (IDS) are required. Moreover, the wireless devices are battery-driven; implementing them would consume more energy, weakening… More >

Gautham Praveen Ramalingam¹, R. Arockia Xavier Annie¹, Shobana Gopalakrishnan^2,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1479-1492, 2022, DOI:10.32604/iasc.2022.022211

Abstract Detection of intrusion plays an important part in data protection. Intruders will carry out attacks from a compromised user account without being identified. The key technology is the effective detection of sundry threats inside the network. However, process automation is experiencing expanded use of information communication systems, due to high versatility of interoperability and ease off 34 administration. Traditional knowledge technology intrusion detection systems are not completely tailored to process automation. The combined use of fuzziness-based and RNN-IDS is therefore highly suited to high-precision classification, and its efficiency is better compared to that of conventional machine learning approaches. This model… More >