Hasan H. Al-Khshali^1,*, Muhammad Ilyas²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 153-178, 2023, DOI:10.32604/cmc.2023.032182

Abstract One aspect of cybersecurity, incorporates the study of Portable Executables (PE) files maleficence. Artificial Intelligence (AI) can be employed in such studies, since AI has the ability to discriminate benign from malicious files. In this study, an exclusive set of 29 features was collected from trusted implementations, this set was used as a baseline to analyze the presented work in this research. A Decision Tree (DT) and Neural Network Multi-Layer Perceptron (NN-MLPC) algorithms were utilized during this work. Both algorithms were chosen after testing a few diverse procedures. This work implements a method of subgrouping features to answer questions such… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Mohamed K. Nour⁴, Mashael M. Asiri⁵, Ali M. Al-Sharafi⁶, Mahmoud Othman⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 607-621, 2023, DOI:10.32604/cmc.2023.031371

Abstract Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation,… More >

Eatedal Alabdulkreem¹, Saud S. Alotaibi², Mohammad Alamgeer^3,4, Radwa Marzouk⁵, Anwer Mustafa Hilal^6,*, Abdelwahed Motwakel⁶, Abu Sarwar Zamani⁶, Mohammed Rizwanullah⁶

Computer Systems Science and Engineering, Vol.45, No.1, pp. 971-983, 2023, DOI:10.32604/csse.2023.030362

Abstract Cyberattack detection has become an important research domain owing to increasing number of cybercrimes in recent years. Both Machine Learning (ML) and Deep Learning (DL) classification models are useful in effective identification and classification of cyberattacks. In addition, the involvement of hyper parameters in DL models has a significantly influence upon the overall performance of the classification models. In this background, the current study develops Intelligent Cybersecurity Classification using Chaos Game Optimization with Deep Learning (ICC-CGODL) Model. The goal of the proposed ICC-CGODL model is to recognize and categorize different kinds of attacks made upon data. Besides, ICC-CGODL model primarily… 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) model, named MFO-RELM for Cybersecurity… More >

Ashit Kumar Dutta^1,*, T. Meyyappan², Basit Qureshi³, Majed Alsanea⁴, Anas Waleed Abulfaraj⁵, Manal M. Al Faraj¹, Abdul Rahaman Wahab Sait⁶

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2701-2713, 2023, DOI:10.32604/csse.2023.028984

Abstract Recently, developments of Internet and cloud technologies have resulted in a considerable rise in utilization of online media for day to day lives. It results in illegal access to users’ private data and compromises it. Phishing is a popular attack which tricked the user into accessing malicious data and gaining the data. Proper identification of phishing emails can be treated as an essential process in the domain of cybersecurity. This article focuses on the design of biogeography based optimization with deep learning for Phishing Email detection and classification (BBODL-PEDC) model. The major intention of the BBODL-PEDC model is to distinguish… More >

Ashit Kumar Dutta^1,*, Basit Qureshi², Yasser Albagory³, Majed Alsanea⁴, Manal Al Faraj¹, Abdul Rahaman Wahab Sait⁵

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2395-2409, 2023, DOI:10.32604/csse.2023.027502

Abstract Fake news and its significance carried the significance of affecting diverse aspects of diverse entities, ranging from a city lifestyle to a country global relativity, various methods are available to collect and determine fake news. The recently developed machine learning (ML) models can be employed for the detection and classification of fake news. This study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning Machine (CAS-WELM) for Cybersecurity Fake News Detection and Classification. The goal of the CAS-WELM technique is to discriminate news into fake and real. The CAS-WELM technique initially pre-processes the input data and Glove technique is… More >

Manar Ahmed Hamza^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Saud S. Alotaibi⁴, Hany Mahgoub^5,6, Amal S. Mehanna⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6579-6594, 2022, DOI:10.32604/cmc.2022.031303

Abstract Internet of Everything (IoE), the recent technological advancement, represents an interconnected network of people, processes, data, and things. In recent times, IoE gained significant attention among entrepreneurs, individuals, and communities owing to its realization of intense values from the connected entities. On the other hand, the massive increase in data generation from IoE applications enables the transmission of big data, from context-aware machines, into useful data. Security and privacy pose serious challenges in designing IoE environment which can be addressed by developing effective Intrusion Detection Systems (IDS). In this background, the current study develops Intelligent Multiverse Optimization with Deep Learning… More >

Mesfer Al Duhayyim^1,*, Heba G. Mohamed², Saud S. Alotaibi³, Hany Mahgoub^4,5, Abdullah Mohamed⁶, Abdelwahed Motwakel⁷, Abu Sarwar Zamani⁷, Mohamed I. Eldesouki⁸

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5011-5024, 2022, DOI:10.32604/cmc.2022.031096

Abstract Cyberbullying (CB) is a challenging issue in social media and it becomes important to effectively identify the occurrence of CB. The recently developed deep learning (DL) models pave the way to design CB classifier models with maximum performance. At the same time, optimal hyperparameter tuning process plays a vital role to enhance overall results. This study introduces a Teacher Learning Genetic Optimization with Deep Learning Enabled Cyberbullying Classification (TLGODL-CBC) model in Social Media. The proposed TLGODL-CBC model intends to identify the existence and non-existence of CB in social media context. Initially, the input data is cleaned and pre-processed to make… More >

D. Doreen Hephzibah Miriam¹, Deepak Dahiya², Nitin³, C. R. Rene Robin^4,*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1889-1906, 2023, DOI:10.32604/iasc.2023.028850

Abstract Blockchain technology is critical in cyber security. The most recent cryptographic strategies may be hacked as efforts are made to build massive electronic circuits. Because of the ethical and legal implications of a patient’s medical data, cyber security is a critical and challenging problem in healthcare. The image secrecy is highly vulnerable to various types of attacks. As a result, designing a cyber security model for healthcare applications necessitates extra caution in terms of data protection. To resolve this issue, this paper proposes a Lionized Golden Eagle based Homomorphic Elapid Security (LGE-HES) algorithm for the cybersecurity of blockchain in healthcare… More >

Ahmed AL-Hthlool^1,*, Mounir Frikha²

Journal of Cyber Security, Vol.4, No.2, pp. 109-118, 2022, DOI:10.32604/jcs.2022.030498

Abstract Nowadays, emerging trends in the field of technology related to big data, cognitive computing, and the Internet of Things (IoT) have become closely related to people’s lives. One of the hottest areas these days is transforming traditional cities into smart cities, using the concept of IoT depending on several types of modern technologies to develop and manage cities in order to improve and facilitate the quality of life. The Internet of Things networks consist of a huge number of interconnected devices and sensors that process and transmit data. Such Activities require efficient energy to be performed at the highest quality… More >