Design of an AI-Powered Intrusion Detection System for Federal University, Lafia, Nasarawa State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Background of the Study
Cybersecurity threats have evolved significantly, necessitating advanced security measures to protect institutional networks. Traditional Intrusion Detection Systems (IDS) rely on signature-based and rule-based techniques, which often fail to detect new or sophisticated attacks. Artificial Intelligence (AI)-powered IDSs have emerged as a robust alternative, leveraging machine learning (ML) and deep learning (DL) algorithms to identify anomalies and detect threats in real-time. AI-driven IDSs enhance cybersecurity by continuously learning from network traffic patterns, allowing them to adapt to new threats without requiring constant manual updates.
Federal University, Lafia, faces an increasing number of cyber threats due to its expanding digital infrastructure. The university’s reliance on traditional security mechanisms may leave it vulnerable to zero-day attacks, advanced persistent threats (APTs), and evolving malware. The integration of AI in IDSs offers a proactive approach to securing the university’s network by improving threat detection accuracy, reducing false positives, and enhancing response times. This study aims to design and implement an AI-powered IDS tailored to the university’s cybersecurity needs.
Statement of the Problem
Existing IDS solutions at Federal University, Lafia, primarily depend on static rule-based approaches, which are ineffective against sophisticated cyber threats. The increasing frequency of cyberattacks, including ransomware, phishing, and distributed denial-of-service (DDoS) attacks, underscores the need for an advanced, intelligent IDS. The inability of traditional IDSs to detect novel attack patterns, coupled with their high false-positive rates, makes network security management challenging.
The adoption of AI-powered IDSs remains limited due to concerns about computational overhead, integration complexity, and accuracy. There is a need for a customized AI-driven IDS that can efficiently analyze the university’s network traffic, detect anomalies, and minimize security breaches. This study seeks to bridge this gap by designing a scalable, AI-powered IDS that enhances cybersecurity at Federal University, Lafia.
Objectives of the Study
-
To design an AI-powered intrusion detection system for monitoring network traffic at Federal University, Lafia.
-
To evaluate the effectiveness of AI-driven IDS in detecting and mitigating cyber threats compared to traditional IDS.
-
To assess the computational efficiency and scalability of the proposed IDS within the university’s network infrastructure.
Research Questions
-
How effective is an AI-powered IDS in detecting cyber threats compared to traditional IDS?
-
What are the computational and operational challenges of deploying an AI-based IDS?
-
How can AI-driven IDS be optimized for real-time threat detection in a university network?
Scope and Limitations of the Study
This study focuses on the design and implementation of an AI-powered IDS for Federal University, Lafia, Nasarawa State. The evaluation will cover detection accuracy, response time, and system efficiency. The study will not include commercial IDS comparisons or non-AI security solutions. Limitations include computational resource constraints and the availability of labeled attack datasets for training the AI model.
Definitions of Terms
-
Intrusion Detection System (IDS): A security mechanism that monitors network traffic for malicious activities.
-
Artificial Intelligence (AI): The simulation of human intelligence in machines to perform tasks such as pattern recognition.
-
Anomaly Detection: A technique that identifies deviations from normal network behavior to detect cyber threats.
Related Project Materials
THE EFFECT OF MARKETING COMMUNICATION ON CONSUMER BUYING BEHAVIOUR
ABSTRACT
This study was carried out on the effect of marketing communication on consumer buying behavior. The case study...
Exploring the Role of AI-Based Predictive Analytics in University Research Funding Allocation: A Case Study of Bayero University, Kano (Gwale LGA, Kano State)
Background of the Study
University research plays a central role in academic advancement, innovation, and societal progress...
An Evaluation of the Role of Venture Capital in Promoting Innovation in Nigeria
Background of the Study
Venture capital (VC) plays a pivotal role in fostering innovation by providing startups and emergi...
An examination of urban transportation challenges and commuter satisfaction in Ibadan North Local Government Area, Oyo State
Background of the Study
Urban transportation is a critical component of urban living that significantly influences commute...
The Impact of Healthcare Worker Migration on Healthcare Delivery in Gombe State
Background of the Study
Healthcare worker migration, also known as "brain drain," refers to the movement of trained medical pro...
An Assessment of Nurses’ Awareness and Practices on Early Childhood Development in Kaduna State
Background of the Study
Early childhood development (ECD) is critical for the long-term physical, cog...
Assessing the Role of Econometric Models in Reducing Policy Uncertainty in Nigeria
Background of the Study
Econometric models are widely used to analyze economic data and forecast future trends, providing...
PHARMACOGNOSTIC AND ANTIMICROBIAL STUDIES ON THE STEM-BARK OF FICUS KAMERUNENSIS WARB. (MORACEAE)
ABSTRACT
Ficus kamerunensis is an epiphytic shrub or tree growing up to 20 m high. The plant used in ethnomedicine to treat microbial inf...
EXAMINING THE EFFECTIVENESS OF MOBILE LEARNING APPLICATIONS IN VOCATIONAL EDUCATION
ABSTRACT: Examining the effectiveness of mobile learning applications in vocational education explores how digital tools can enhance learning...
A Case Study of Cyber Resilience Strategies in Nigerian Banks: A Study of Commercial Banks in Sokoto State
Background of the Study
Cyber resilience refers to an organization's ability to continuously deliver essential servi...
