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 October 2026
Machine learning-based network intrusion detection systems (NIDS) increasingly operate in environments where adversaries can adapt their behavior in response to deployed defenses. However, most empirical IDS studies eval…
Smart Internet of Toys (IoToys) can provide interactive learning and companionship for children, but many systems still provide limited support for guardian awareness and safety notification. This study presents the desi…
Web 3.0 shifts control of digital identity and data away from centralized platforms, moving authentication onto resource-constrained end-user devices, wallets, and smart contracts. RSA and ElGamal are computationally exp…
Federated learning (FL) enables distributed intrusion detection without centralizing raw Internet of Things (IoT), Industrial IoT (IIoT), or Internet of Medical Things (IoMT) traffic. Secure aggregation protects update c…
Clinical decision assistance that protects patient privacy is a prominent research issue in federated learning, edge computing, and intensive care analytics. However, typical differential privacy algorithms allocate equa…
Conventional Internet-of-Things (IoT) intrusion detection typically maps a model score directly to an alert, although autonomous defense must also determine whether the evidence is reliable, whether suspicious behavior p…
Defense-in-Depth (DiD) holds that a system should be protected by multiple independent layers of security, so that the failure or compromise of a single countermeasure does not result in total system compromise. Secondar…
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…