A Hybrid Cryptographic Algorithm for Web Security against Distributed Denial of Service Attacks

Abstract To prevent disruptions on the internet caused by distributed denial of service (DDoS), the study presents a hybrid cryptographic algorithm that enhances web security. To enhance security and mitigate the effects of DDoS attacks, the proposed algorithm combines symmetric and asymmetric encryption techniques with traffic analysis. First, Blowfish encryption is employed in the fast

Phishing Uniform Resource Locator Detection Using Machine Learning Methods

Abstract Phishing attacks are a serious threat to internet security because they can cause large financial losses and jeopardize user privacy. To overcome these obstacles, this research uses machine learning models to create an effective phishing URL detection system. The research includes an in-depth examination of different phishing tactics, the complexity of phishing websites, and

Modelling Cybersecurity Knowledge and Attitudes of Online Users

Abstract: Individuals and organizations are persistently being exploited by cybercriminals. With the increased dependence on the Internet, cyberattacks have become even more prominent. However, many of the Internet users under prioritize their online safety, and fall victims. Their unawareness and negligence of cybersecurity poses devastating consequences. It is thus essential to analyze the factors affecting

Human Factors influencing Compliance to Cyber Security Practices by Employees of Public Universities in Southeast Nigeria

Abstract: The increasing use of technology in workplaces has led to a rise in cyber threats, making it essential for employees to have adequate knowledge and skills to ensure cyber safety. The study examined the human factors that influence the cyber security practices of employees in public universities in Southeast in Nigeria. The theory of

Phishing Detection: Performance Evaluation of Both Ensemble and Classical Machine Learning Models

Abstract: The majority of bank customers have switched to e-banking for their regular financial activities as a result of the development of technology and the rise of electronic commerce in global trade. The emergence of e-commerce has also attracted scammers looking to swindle bank customers, rendering e-commerce platforms vulnerable to a number of assaults, the

Development of a Botnet Management Model for Cyber Security Networks using Machine Learning Algorithm

Abstract: The negative effects of Botnet on the cyberspace cannot be overemphasized. A Botnet is a group of compromised computer systems that are connected to a central controller called a Botmaster. The Botmaster uses command and control (C&C) channels to manipulate Botnets. Devices which are connected to the internet are prone to getting infected by