Abdul Rauf¹, Muhammad Asif Khan^1,*, Hamid Hussain Awan², Waseem Shahzad³, Najeeb Ul Husaan⁴

Journal of Cyber Security, Vol.4, No.4, pp. 201-222, 2022, DOI:10.32604/jcs.2022.038791

Abstract In the modern world, law enforcement authorities are facing challenges due to the advanced technology used by criminals to commit crimes. Criminals follow specific patterns to carry out their crimes, which can be identified using machine learning and swarm intelligence approaches. This article proposes the use of the Ant Colony Optimization algorithm to create an associative classification of crime data, which can reveal potential relationships between different features and crime types. The experiments conducted in this research show that this approach can discover various associations among the features of crime data and the specific patterns that major crime types depend… 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 >

Yeshi Nidup^*

Journal of Cyber Security, Vol.3, No.3, pp. 133-148, 2021, DOI:10.32604/jcs.2021.024136

Abstract This study aimed to find out the awareness about the online security threat and understanding of the preventive measuresto secure the youthsfrom online risks. For this, a quantitative method was applied and the survey questionnaire was instituted to collect the data randomly from the youths studying in class eleven and higher. A total of 264 youths, 147 female and 117 male responded to the survey questionnaire. The data was organized and analyzed using Excel data analysis tool package, interpreted and represented in the form of graphs with some explanations. The awareness about the online security threat was found to be… More >

Maha M. Althobaiti^*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 167-177, 2021, DOI:10.32604/iasc.2021.016660

Abstract Cybersecurity threats, including those involving machine learning, malware, phishing, and cryptocurrency, have become more sophisticated. They target sensitive information and put institutions, governments, and individuals in a continual state of risk. In 2019, phishing attacks became one of the most common and dangerous cyber threats. Such attacks attempt to steal sensitive data, such as login and payment card details, from financial, social, and educational websites. Many universities have suffered data breaches, serving as a prime example of victims of attacks on educational websites. Owing to advances in phishing tactics, strategies, and technologies, the end-user is the main victim of an… More >