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
Global supply chains produce vast quantities of transactional data, yet most existing traceability systems force companies to choose between disclosing sensitive commercial relationships to a shared infrastructure and re…
The increasing adoption of large language mod-els (LLMs) and domain-adapted transformers in healthcare has created a new privacy challenge: fine-tuned models may memorize rare clinical strings and later reveal them throu…
Protecting the privacy of geospatial data, along with efficient encrypted query processing, remains a major challenge in cloud-based GIS applications and location-based applications (LBS). In this study, a privacy-preser…
This study analyzes phishing susceptibility among Indonesian internet users through Confirmatory Factor Analysis (CFA) and covariance-based Structural Equation Modeling (SEM). The latent factors examined include perceive…
The secure and scalable sharing of electronic health records (EHRs) remains a fundamental challenge in modern health-care systems due to conflicting requirements of privacy, regulatory compliance (HIPAA, GDPR), and real-…
The rapid increase in unstructured digital information has led to an urgent demand for effective systems for safeguarding Personally Identifiable Information (PII) across multiple sectors and application domains. Existin…
The explosive growth of online education platforms has led to increased exposure to cybersecurity threats, which makes secure Learning Management Systems (LMS) a critical requirement. However, the current methods often c…
This research provides a comprehensive synthesis of Multimodal Machine Learning (MML) as a transformative paradigm for IoT defense. By integrating heterogeneous data streams, including network flow statistics, device-lev…
The Google Play marketplace has introduced the Data Safety section to improve transparency regarding how mobile applications (apps) collect, share, and protect user data. This mechanism requires developers to disclose pr…
Protecting patient data confidentiality while enabling collaborative machine learning across distributed healthcare institutions remains a major challenge. This study presents ZK-FedMed, a privacy-preserving federated le…