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
Although cloud storage platforms are widely used to safeguard personal images, data leakage and unauthorized access remain persistent threats, exposing sensitive visual content. Linear obfuscation methods such as Gaussia…
The digital transformation of Critical Information Infrastructure (CII) and Industrial Control Systems (ICS) through Industry 4.0 technologies introduces significant cybersecurity challenges. While existing research exam…
Electronic Health Record (EHR) systems store sensitive patient information and require strong access control and reliable audit records. Traditional centralized Role-Based Access Control (RBAC) systems may be vulnerable…
Machine learning-based intrusion detection systems are often constrained by severe class imbalance, while generative augmentation may memorize distinctive network-flow records and expose membership information. This stud…
Smart cities are becoming more interconnected, data-driven, and increasingly autonomous, with 6th-generation communication, edge-cloud computing, Internet of Things infrastructures, digital twins, federated learning, and…
Based on Sommerville’s robust software reliability theory and eight design principles based on best practices (DPG), this study conducted a comparative assessment of two Dexcom software platforms: the Dexcom Clarity web…
Digital financial ecosystems face mounting exposure to fraudulent transactions that collectively account for trillions of dollars in losses each year. Existing approaches suffer from three recurring deficiencies: they re…
Lung cancer is among the deadliest cancers worldwide, largely because it is usually caught too late. Building AI tools for earlier, stage-aware diagnosis is hard in practice: patient scans are scattered across hospitals…
Strong cybersecurity measures are essential in our digital world. This study presents a new cryptographic algorithm called CBT “Combined Blowfish Trilogy” which greatly improves the security of the traditional Blowfish a…
This study introduces a privacy-preserving data preparation and feature engineering framework designed for machine learning-based cybersecurity vulnerability risk prediction, utilizing real-world enterprise scan data fro…