Mozamel M. Saeed^1,*, Zaher Al Aghbari²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 325-348, 2023, DOI:10.32604/cmc.2023.036894

Abstract Emailing is among the cheapest and most easily accessible platforms, and covers every idea of the present century like banking, personal login database, academic information, invitation, marketing, advertisement, social engineering, model creation on cyber-based technologies, etc. The uncontrolled development and easy access to the internet are the reasons for the increased insecurity in email communication. Therefore, this review paper aims to investigate deep learning approaches for detecting the threats associated with e-mail security. This study compiles the literature related to the deep learning methodologies, which are applicable for providing safety in the field of cyber… More >

Xiulai Li^1,2,3,4, Jieren Cheng^1,3,*, Zhaoxin Shi^2,3, Jingxin Liu^2,3, Bin Zhang^1,3, Xinbing Xu^2,3, Xiangyan Tang^1,3, Victor S. Sheng⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2597-2629, 2023, DOI:10.32604/cmc.2023.040596

Abstract As a distributed database, the system security of the blockchain is of great significance to prevent tampering, protect privacy, prevent double spending, and improve credibility. Due to the decentralized and trustless nature of blockchain, the security defense of the blockchain system has become one of the most important measures. This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense, and we first introduce the overview, classification, and threat assessment process of blockchain security threats. Then, we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize More >

Oliva Debnath¹, Saptarshi Debnath¹, Sreyashi Karmakar², MD Tausif Mallick³, Himadri Nath Saha^4,*

Journal on Internet of Things, Vol.5, pp. 13-43, 2023, DOI:10.32604/jiot.2023.039391

Abstract The Internet of Things (IoT) will significantly impact our social and economic lives in the near future. Many Internet of Things (IoT) applications aim to automate multiple tasks so inactive physical objects can behave independently of others. IoT devices, however, are also vulnerable, mostly because they lack the essential built-in security to thwart attackers. It is essential to perform the necessary adjustments in the structure of the IoT systems in order to create an end-to-end secure IoT environment. As a result, the IoT designs that are now in use do not completely support all of… More >

U. Sakthivelu, C. N. S. Vinoth Kumar^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3691-3707, 2023, DOI:10.32604/iasc.2023.036946

Abstract The detection of cyber threats has recently been a crucial research domain as the internet and data drive people’s livelihood. Several cyber-attacks lead to the compromise of data security. The proposed system offers complete data protection from Advanced Persistent Threat (APT) attacks with attack detection and defence mechanisms. The modified lateral movement detection algorithm detects the APT attacks, while the defence is achieved by the Dynamic Deception system that makes use of the belief update algorithm. Before termination, every cyber-attack undergoes multiple stages, with the most prominent stage being Lateral Movement (LM). The LM uses… More >

R. Rema^*, N. Nalanth

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1497-1506, 2023, DOI:10.32604/iasc.2023.032540

Abstract Researchers worldwide have employed a varied array of sources to calculate the successful management of Construction and Demolition (C&DW). Limited research has been undertaken in the domain of Construction and Demolition Waste Management (C&DWM) and consequently leaving a large gap in the availability of effective management techniques. Due to the limited time available for building removal and materials collection, preparing for building materials reuse at the end of life is frequently a challenging task. In this research work Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) is proposed to predict the number of waste materials that are More >

R. T. Pavendan^1,*, K. Sankar¹, K. A. Varun Kumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3331-3348, 2023, DOI:10.32604/iasc.2023.028029

Abstract Attacks on the cyber space is getting exponential in recent times. Illegal penetrations and breaches are real threats to the individuals and organizations. Conventional security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats (APTs) they fails. These APTs are targeted, more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing defenses. Hence, there is a need for an effective defense system that can achieve a complete reliance of security. To address the above-mentioned issues, this paper proposes a novel honeypot system More >

Fadwa Alrowais¹, Sami Althahabi², Saud S. Alotaibi³, Abdullah Mohamed⁴, Manar Ahmed Hamza^5,*, Radwa Marzouk⁶

Computer Systems Science and Engineering, Vol.45, No.1, pp. 687-700, 2023, DOI:10.32604/csse.2023.030188

Abstract Recently, Internet of Things (IoT) devices produces massive quantity of data from distinct sources that get transmitted over public networks. Cybersecurity becomes a challenging issue in the IoT environment where the existence of cyber threats needs to be resolved. The development of automated tools for cyber threat detection and classification using machine learning (ML) and artificial intelligence (AI) tools become essential to accomplish security in the IoT environment. It is needed to minimize security issues related to IoT gadgets effectively. Therefore, this article introduces a new Mayfly optimization (MFO) with regularized extreme learning machine (RELM)… More >

Amjad Alsirhani, Mohamed Ezz, Ayman Mohamed Mostafa^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 967-984, 2022, DOI:10.32604/csse.2022.024854

Abstract Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security… More >

Mohd Anul Haq¹, Mohd Abdul Rahim Khan^1,*, Mohammed Alshehri²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 619-635, 2022, DOI:10.32604/iasc.2022.021430

Abstract The growth of edge computing, the Internet of Things (IoT), and cloud computing have been accompanied by new security issues evolving in the information security infrastructure. Recent studies suggest that the cost of insider attacks is higher than the external threats, making it an essential aspect of information security for organizations. Efficient insider threat detection requires state-of-the-art Artificial Intelligence models and utility. Although significant have been made to detect insider threats for more than a decade, there are many limitations, including a lack of real data, low accuracy, and a relatively low false alarm, which… More >

Weiwei Lin^1,2,*, Reiko Haga³

Journal on Big Data, Vol.3, No.4, pp. 147-153, 2021, DOI:10.32604/jbd.2021.017299

Abstract In this paper, a cybersecurity threat warning model based on ant colony algorithm is designed to strengthen the accuracy of the cybersecurity threat warning model in the warning process and optimize its algorithm structure. Through the ant colony algorithm structure, the local global optimal solution is obtained; and the cybersecurity threat warning index system is established. Next, the above two steps are integrated to build the cybersecurity threat warning model based on ant colony algorithm, and comparative experiment is also designed. The experimental results show that, compared with the traditional qualitative differential game-based cybersecurity More >