Cybersecurity is the practice of protecting computer systems, networks, and data from unauthorized access, disruption, or damage. It spans multiple layers of defense, including network security such as firewalls and VPNs, application security such as secure coding and vulnerability testing, endpoint protection, identity and access management, and cryptography for confidentiality and integrity. Common threat categories include malware, phishing, denial-of-service attacks, SQL injection, and increasingly sophisticated ransomware campaigns; a 2026 industry threat report recorded more than 7,500 ransomware disclosures for the year, continuing a four-year upward trend. Modern cybersecurity research draws heavily on machine learning for anomaly-based threat detection, behavioral analysis, and automated incident response, alongside traditional signature-based and rule-based defenses. Other active research areas include securing cloud infrastructure, IoT device security, blockchain-based authentication schemes, and privacy-preserving techniques such as differential privacy. As an open-access cybersecurity journal, IJACSA publishes peer-reviewed work on threat detection models, security architectures, cryptographic protocols, and vulnerability assessment methods.
Published in International Journal of Advanced Computer Science and Applications (IJACSA)
· list last refreshed September 2026
The convergence of artificial intelligence (AI) and blockchain has become an active axis of interdisciplinary research in healthcare data security. This paper reports a bibliometric analysis of 434 Scopus-indexed article…
Early detection of cyberattacks remains a major challenge in enterprise networks due to encrypted traffic, protocol diversity, and highly dynamic service behavior. This study evaluates a machine learning-based intrusion…
Electronic medical records (EMRs) in sports medicine contain rich clinical insights but often remain in unstructured, bilingual formats. While locally-deployed large language models (LLMs) offer a privacy-preserving solu…
The rapid expansion of internet services and cloud-based platforms has increased cybersecurity threats, particularly phishing attacks that deceive users into disclosing sensitive information. Traditional phishing detecti…
The acceleration of multi-centric medical AI studies hinges on the ability to share imaging data without exposing burnt-in Protected Health Information (PHI). Manual redaction remains the dominant practice, but it erases…
Smart Internet of Things (IoT) technologies, which include artificial intelligence (AI) are increasingly being implemented in the infrastructures of smart cities to enhance the efficiency, sustainability, and service del…
The blistering development of digital image sharing raises privacy concerns, especially in cultural contexts where image exposure could be ethically and socially provocative. In Islamic societies, sharing images of women…
Federated learning (FL) makes it possible to train models across distributed data sources without collecting raw data in one place. However, even in federated settings, trained models may still leak sensitive information…
This study presents a user behaviour analysis approach for detecting insider threats in an enterprise web application environment. The approach applies machine learning techniques to analyze patterns of user activity. Us…
Injection attacks persist as dominant threats in modern web systems due to obfuscation, polymorphism, and multi-vector exploitation across SQLi, XSS, LDAP Injection, and Command Injection. Existing defenses often rely on…