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
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…
In this study, researchers propose a novel solution for efficient enhancement of vulnerability detection in several IoT environments. Efficient Vulnerability Classification has been introduced as the presented technique…
Higher education institutions in Ecuador face a growing exposure to unauthorized access and data exfiltration, compounded by fragmented log infrastructures that obstruct real-time threat visibility. This study addresses…
Customer segmentation plays a critical role in retail analytics by enabling personalized marketing, optimized resource allocation, and data-driven strategic decision-making. However, customer data is often distributed ac…
As mental health disorders such as stress, anxiety, depression, and post-traumatic stress disorder (PTSD) affect a substantial part of the world population, current diagnostic methodologies are still centralized, subject…
Accurate engineering vehicle detection is the core part of intelligent construction. Aiming at the problems of high training resource consumption and prominent privacy leakage risk of engineering vehicle image data, this…
This paper revisits a previously proposed authentication scheme for remote healthcare systems in Cloud-IoT. Although that protocol was introduced as a repair of an earlier healthcare design and was claimed to satisfy the…
This study proposes an intrusion-prediction framework for e-Health information systems that combines structured web-log analysis, supervised machine learning, and Apache Spark-based distributed processing. A corpus of 1,…