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Intrusion detection and prevention system

 

Table Of Contents


Chapter ONE

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of Intrusion Detection Systems
2.2 Types of Intrusion Detection Systems
2.3 Intrusion Prevention Systems
2.4 Comparison of Intrusion Detection and Prevention Systems
2.5 Evolution of Intrusion Detection and Prevention Systems
2.6 Machine Learning in Intrusion Detection
2.7 Challenges in Intrusion Detection and Prevention
2.8 Best Practices in Intrusion Detection and Prevention
2.9 Case Studies on Intrusion Detection and Prevention
2.10 Future Trends in Intrusion Detection and Prevention Systems

Chapter THREE

3.1 Research Methodology Overview
3.2 Research Design
3.3 Data Collection Methods
3.4 Sampling Techniques
3.5 Data Analysis Techniques
3.6 Ethical Considerations
3.7 Validity and Reliability
3.8 Limitations of the Methodology

Chapter FOUR

4.1 Overview of Research Findings
4.2 Analysis of Data Collected
4.3 Comparison with Existing Literature
4.4 Key Insights from the Findings
4.5 Implications of Findings
4.6 Recommendations for Practice
4.7 Recommendations for Future Research
4.8 Conclusion of Findings

Chapter FIVE

5.1 Summary of Research
5.2 Conclusions Drawn
5.3 Contributions to the Field
5.4 Practical Implications
5.5 Recommendations for Action
5.6 Areas for Future Research
5.7 Reflections on the Research Process
5.8 Final Thoughts and Acknowledgments

Thesis Abstract

Abstract
Intrusion detection and prevention systems (IDPS) play a critical role in safeguarding computer networks from unauthorized access, malicious activities, and potential security breaches. These systems continuously monitor network traffic, analyze patterns, and detect anomalies or suspicious behavior that could indicate a security threat. By identifying and responding to potential intrusions in real-time, IDPS helps organizations mitigate risks, protect sensitive data, and ensure the integrity of their network infrastructure. Traditional IDPS solutions typically employ a combination of signature-based detection, anomaly detection, and rule-based analysis to identify and respond to security incidents. Signature-based detection relies on predefined patterns or signatures of known threats to detect malicious activities, while anomaly detection identifies deviations from normal network behavior that could indicate a security breach. Rule-based analysis involves setting specific rules or policies to govern network traffic and trigger alerts or responses when certain conditions are met. Recent advancements in IDPS technologies have introduced more sophisticated techniques such as machine learning, artificial intelligence, and behavioral analysis to enhance the accuracy and efficiency of intrusion detection and prevention. Machine learning algorithms enable IDPS to adapt and learn from new data patterns, improving its ability to detect emerging threats and evolving attack techniques. Artificial intelligence algorithms can analyze vast amounts of network data to identify complex attack patterns and make real-time decisions to prevent potential intrusions. Furthermore, behavioral analysis techniques focus on understanding normal user behavior and network patterns to detect deviations that could indicate unauthorized access or malicious activities. By continuously monitoring and analyzing network traffic, IDPS can establish baseline behavior profiles and detect abnormal activities that may pose a security risk. This proactive approach allows organizations to respond swiftly to security incidents and prevent potential data breaches or system compromises. In conclusion, the implementation of an effective intrusion detection and prevention system is essential for organizations to enhance their cybersecurity posture and protect their network assets from cyber threats. By leveraging a combination of traditional and advanced detection techniques, IDPS can provide real-time threat detection, incident response, and security policy enforcement to safeguard critical infrastructure and mitigate security risks. As cyber threats continue to evolve and become more sophisticated, organizations must invest in robust IDPS solutions to defend against potential intrusions and ensure the confidentiality, integrity, and availability of their network resources.

Thesis Overview

INTRODUCTION

An intrusion detection system (IDS) monitors network traffic and monitors for suspicious activity and alert the system or network administrator. In some cases the IDS may also respond to anomalous or malicious traffic by taking action such blocking the user or source IP address from accessing the network. IDS come in a variety of β€œflavors” and approach the goal of detecting suspicious traffic in different ways. There are network based (NIDS) and host based (HIDS) intrusion detection systems are placed at a strategic point or points within the network to monitor traffic to and from all devices on the network. HIDS host intrusion detection system on the network. HIDS monitors the inbound and outbound pockets from the device only and will alert the user. Intrusion detection, prevention and trace back system are primarily focused on identifying possible incidents, logging information about them, attempting to stop them and reporting them to security administers. Intrusion prevention systems (IPS), also known as intrusion detection and prevention systems (IDPS), are network or system activities for malicious activity.  Guide to intrusion detection and prevention systems (IDPS). Computer security resource center, Scarf one [1].

 Guide to intrusion detection and prevention systems (IDPS). Computer security resource center, Scarf one [1].

1.1     Statement of the Problem

The following problems were identified in the existing system that necessitated the development of the intrusion detection and prevention system:

  1. Absence of an intrusion detection and prevention system.
  2. Insecurity of customer information.
  3. Inability to prevent intruders from gaining access to sensitive information stored in the computer system.
  4. Low level of file security.

1.2     Aim and Objectives of Study

The aim of this project is to develop an Intrusion Detection and Prevention System with the following objectives:

(1)  To design a system that will encrypt information pertaining to customers to prevent intrusion.

(2)  To develop a system that will require an encryption key before bank transaction information can be viewed.

(3) To implement a system that will prevent disclosure of customers’ data to fraudsters by utilizing cipher text.

  • Significance of the study

This study is significant in the following ways:

  1. It will help prevent unauthorized individuals (intruders) from gaining access to the financial information of customers.
  2. It will help in tightening the security level of the organization.
  3. The study will reveal how encryption can be applied to prevent intruders from gaining access to customer information.
  4. The study will serve as a useful reference material to other researchers seeking related information.

1.4     Scope of the Study

This study covers Intrusion Detection, and Prevention System using Gufax micro finance Bank Plc, Ikot Ekpene as a case study. It is limited to the use of cipher text encryption to prevent intruders from gaining access to vital information of customers,

1.5 Organization of the Research

This research work is organized into five chapters, chapter one is concerned with the introduction of the research study and it presents the preliminaries, theoretical background, and statement of the problem, aim and objectives of the study, significance of the study, scope of the study, and organization of the research, Limitation of the study and definition of terms.

Chapter two focuses on the literature review; contribution of other scholars on the subject matter is discussed.

Chapter three contains the system analysis and the design, it presents the research methodology used in development of the system, it analyses the present system to identify the problems and provide information on the merit of the proposed system. The system design is also presented in this chapter.

Chapter four present the system implementation, the choice of programming language used, and system requirement for implementation

Chapter five, this chapter focuses on the summary, conclusion and recommendation are also contained in this chapter based on the study carried out.

Detection is the extraction of particular information from a larger stream of information without specific cooperation from or synchronization with the sender.

Intrusion: It is an illegal act of entering possession of another’s property.

Password: A special code used by user to gain access to the database or a research.

Security: safety, freedom danger.

Files: Is the collection of logically related record.

Prevention: Maintenance performed to stop fault occurring or developing into major detects.

Codes: To write a computer program by putting one system of number, words symbols into another system.

System:  a group of interdependent items that interact regularly to perform task


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