The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on intrusion detection — including network-based, cloud-based, and AI/ML-driven intrusion detection systems across multiple computing environments.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
Network anomaly detection systems face challenges with imbalanced datasets, particularly in classifying underrepresented attack types. This study proposes a novel framework for improving F1-scores in multi-class imbalanc…
The increasing diversity of network attack behaviors has led to increasingly serious network security issues. Based on this, this study proposes an optimized fireworks algorithm to build an intrusion detection model. Fir…
Cloud Computing has revolutionized the technological landscape, offering a platform for resource provisioning where organizations can access computing resources, storage, applications, and services. The shared nature of…
Internet of Things (IoT) strongly involves intelligent objects sharing information to achieve tasks in the environment with an excellence of living standards. In resource-constrained it is extremely difficult chore to im…
The applications of the Internet of Things (IoT) are becoming increasingly popular nowadays. Network security and privacy are major concerns of the IoTs, as many IoT devices are connected to the network via the Internet,…
Intrusion detection systems (IDS) play a critical role in safeguarding network security by identifying malicious activities within network traffic. However, the effectiveness of an IDS hinges on its ability to extract re…
The paper explores the evolving landscape of network security, in Software Defined Networking (SDN) highlighting the challenges faced by security measures as networks transition to software-based control. SDN revolutioni…
Digital systems in the connected world of today bring convenience but also complicated cyber security challenges. The inadequacies of conventional intrusion detection techniques are exposed by the constant adaptation and…
As cyber threats continue to evolve in complexity, the need for robust intrusion detection systems (IDS) becomes increasingly critical. Machine learning (ML) models have demon-strated their effectiveness in detecting ano…
Given the proliferation of connected devices and the evolving threat landscape, intrusion detection plays a pivotal role in safeguarding IoT networks. However, traditional methodologies struggle to adapt to the dynamic a…
