Fatmah Alanazi^*, Kamal Jambi, Fathy Eassa, Maher Khemakhem, Abdullah Basuhail, Khalid Alsubhi

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 923-938, 2022, DOI:10.32604/iasc.2022.024668 - 08 February 2022

Abstract Software-defined network (SDN) is an enabling technology that meets the demand of dynamic, adaptable, and manageable networking architecture for the future. In contrast to the traditional networks that are based on a distributed control plane, the control plane of SDN is based on a centralized architecture. As a result, SDNs are susceptible to critical cyber attacks that exploit the single point of failure. A distributed denial of service (DDoS) attack is one of the most crucial and risky attacks, targeting the SDN controller and disrupting its services. Several researchers have proposed signature-based DDoS mitigation and… More >

Wei Xiong^1,2, Xianshan Li^1,2,*, Yu Zou³, Shiwei Su^1,2, Li Zhi^1,2

Energy Engineering, Vol.119, No.2, pp. 755-765, 2022, DOI:10.32604/ee.2022.018009 - 24 January 2022

Abstract Among the end-users of the power grid, especially in the rural power grid, there are a large number of users and the situation is complex. In this complex situation, there are more leakage caused by insulation damage and a small number of users stealing electricity. Maintenance staff will take a long time to determine the location of the abnormal user meter box. In view of this situation, the method of subjective fuzzy clustering and quartile difference is adopted to determine the partition threshold. The power consumption data of end-users are divided into three regions: high, More >

S. Sreenivasa Chakravarthi^1,*, R. Jagadeesh Kannan², V. Anantha Natarajan³, Xiao-Zhi Gao⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5117-5133, 2022, DOI:10.32604/cmc.2022.022351 - 14 January 2022

Abstract In the global scenario one of the important goals for sustainable development in industrial field is innovate new technology, and invest in building infrastructure. All the developed and developing countries focus on building resilient infrastructure and promote sustainable developments by fostering innovation. At this juncture the cloud computing has become an important information and communication technologies model influencing sustainable development of the industries in the developing countries. As part of the innovations happening in the industrial sector, a new concept termed as ‘smart manufacturing’ has emerged, which employs the benefits of emerging technologies like internet… More >

A. Balasundaram^1,*, Golda Dilip², M. Manickam³, Arun Kumar Sivaraman⁴, K. Gurunathan⁵, R. Dhanalakshmi⁶, S. Ashokkumar⁷

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 693-704, 2022, DOI:10.32604/iasc.2022.022241 - 17 November 2021

Abstract In the present world, video surveillance methods play a vital role in observing the activities that take place across secured and unsecured environment. The main aim with which a surveillance system is deployed is to spot abnormalities in specific areas like airport, military, forests and other remote areas, etc. A new block-based strategy is represented in this paper. This strategy is used to identify unusual circumstances by examining the pixel-wise frame movement instead of the standard object-based approaches. The density and also the speed of the movement is extorted by utilizing optical flow. The proposed More >

Sivaramakrishnan Rajendar, Vishnu Kumar Kaliappan^*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 859-875, 2022, DOI:10.32604/iasc.2022.020936 - 17 November 2021

Abstract Automated Vehicles (AVs) reform the automotive industry by enabling real-time and efficient data exchange between the vehicles. While connectivity and automation of the vehicles deliver a slew of benefits, they may also introduce new safety, security, and privacy risks. Further, AVs rely entirely on the sensor data and the data from other vehicles too. On the other hand, the sensor data is susceptible to anomalies caused by cyber-attacks, errors, and faults, resulting in accidents and fatalities. Hence, it is essential to create techniques for detecting anomalies and identifying their sources before the wide adoption of More >

Jin Wang¹, Changqing Zhao¹, Shiming He^1,*, Yu Gu², Osama Alfarraj³, Ahed Abugabah⁴

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1207-1222, 2022, DOI:10.32604/csse.2022.022365 - 10 November 2021

Abstract System logs record detailed information about system operation and are important for analyzing the system's operational status and performance. Rapid and accurate detection of system anomalies is of great significance to ensure system stability. However, large-scale distributed systems are becoming more and more complex, and the number of system logs gradually increases, which brings challenges to analyze system logs. Some recent studies show that logs can be unstable due to the evolution of log statements and noise introduced by log collection and parsing. Moreover, deep learning-based detection methods take a long time to train models.… More >

Amgad Muneer^1,2,*, Shakirah Mohd Taib^1,2, Suliman Mohamed Fati³, Abdullateef O. Balogun¹, Izzatdin Abdul Aziz^1,2

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5363-5381, 2022, DOI:10.32604/cmc.2022.021113 - 11 October 2021

Abstract Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. Such a phenomenon is referred to as the “curse of dimensionality” that affects traditional techniques in terms of both accuracy and performance. Thus, this research proposed a hybrid model based on Deep Autoencoder Neural Network (DANN) with five layers to reduce the difference between the input and output. The proposed… More >

Sinil Mubarak¹, Mohamed Hadi Habaebi^1,*, Md Rafiqul Islam¹, Asaad Balla¹, Mohammad Tahir², Elfatih A. A. Elsheikh³, F. M. Suliman³

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1345-1360, 2022, DOI:10.32604/iasc.2022.020801 - 09 October 2021

Abstract Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped… More >

Rafia Afzal, Raja Kumar Murugesan^*

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1825-1841, 2022, DOI:10.32604/iasc.2022.020598 - 09 October 2021

Abstract The global Signalling System No. 7 (SS7) network protocol standard has been developed and regulated based only on trusted partner networks. The SS7 network protocol by design neither secures the communication channel nor verifies the entire network peers. The SS7 network protocol used in telecommunications has deficiencies that include verification of actual subscribers, precise location, subscriber’s belonging to a network, absence of illegitimate message filtering mechanism, and configuration deficiencies in home routing networks. Attackers can take advantage of these deficiencies and exploit them to impose threats such as subscriber or network data disclosure, intercept mobile… More >

Zhen Xu¹, Xiaoqian Zeng¹, Genlin Ji^1,*, Bo Sheng²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1703-1717, 2022, DOI:10.32604/iasc.2022.016919 - 09 October 2021

Abstract Anomaly detection in surveillance videos is an extremely challenging task due to the ambiguous definitions for abnormality. In a complex surveillance scenario, the kinds of abnormal events are numerous and might co-exist, including such as appearance and motion anomaly of objects, long-term abnormal activities, etc. Traditional video anomaly detection methods cannot detect all these kinds of abnormal events. Hence, we utilize multiple probabilistic models inference to detect as many different kinds of abnormal events as possible. To depict realistic events in a scene, the parameters of our methods are tailored to the characteristics of video… More >