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
As cyber-attacks evolve in complexity and frequency; the development of effective network intrusion detection systems (NIDS) has become increasingly important. This paper investigates the efficacy of the XGBoost algorith…
In a cloud environment, software defined security services are highly vulnerable to malicious virus attacks. In response to software security issues, this project plans to use machine learning technology to achieve autom…
Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. The current Multiprotocol Label Switching (MPLS)-based communication system i…
An intrusion detection system (IDS) is one of the most effective ways to secure a network and prevent unauthorized access and security attacks. But due to the lack of adequately labeled network traffic data, researchers…
Advanced Persistent Threats (APT) are a type of sophisticated multistage cyber attack, and the defense against APT is challenging. Existing studies apply signature-based or behavior-based methods to analyze monitoring da…
The Vehicular Ad hoc Network (VANET) can be used to provide secured information to the user vehicles. However, these days the immunity of safeguarding the information from vulnerabilities and threats are of great challen…
In the modern world, information security and communications concerns are growing due to increasing attacks and abnormalities. The presence of attacks and intrusion in the network may affect various fields such as social…
In the era of cloud computing, the effectiveness of utilizing supervised machine-learning-based intrusion detection models for categorizing and detecting malicious network attacks depends on the preparation, extraction,…
Nowadays, various technological advancements in Intrusion Detection Systems (IDS) detects the malicious attacks and reinstate network security in the cloud platform. Cloud based IDS designed with hybrid elements combinin…
The practise of recognising unauthorised abnormal actions on computer systems is referred to as intrusion detection. The primary goal of an Intrusion Detection System (IDS) is to identify user behaviours as normal or abn…
