Abstract of botnet attack:

The rise of cyber threats, particularly botnet attack, poses a significant challenge to computer network security. This postgraduate student project aims to comprehensively study and address the complexities associated with botnet attacks. The project focuses on developing a Java-based solution that enhances network security by detecting, mitigating, and analyzing botnet attack.

Existing System: The current landscape of computer network security faces challenges in effectively detecting and countering botnet attacks. Traditional security measures often fall short in dealing with the dynamic and sophisticated nature of modern botnets.

Proposed System: Our proposed system employs advanced algorithms and real-time monitoring techniques to identify and mitigate botnet activities effectively. The system incorporates machine learning models for behavior analysis, anomaly detection, and signature-based identification to enhance its ability to detect known and emerging botnet threats.

System Requirements:

The proposed system requires a robust computing environment, including servers with sufficient processing power and memory to handle real-time network traffic analysis. Additionally, reliable network infrastructure is essential to ensure seamless communication between system components.

Hardware Requirements:

  1. Server: Multi-core processor, minimum 8GB RAM
  2. Network Monitoring Devices
  3. Storage: Adequate storage capacity for log data and analysis results

Software Requirements:

  1. Operating System: Linux or Windows Server
  2. Java Development Kit (JDK)
  3. Database Management System (e.g., MySQL, PostgreSQL)
  4. Network Monitoring Tools

Architecture: The system architecture is designed with modularity and scalability in mind. It comprises multiple components, including a data collector, analyzer, and response module. The system utilizes a layered architecture to facilitate easy integration with existing network infrastructures.

Technologies Used:

  1. Java for application development
  2. Machine Learning Libraries (e.g., TensorFlow, scikit-learn) for behavior analysis
  3. Network Packet Analysis Tools
  4. Database Management System for storing and retrieving relevant data
  5. Secure Socket Layer (SSL) for secure communication between system components

Web User Interface: The project includes a user-friendly web interface for system administrators to monitor and manage security incidents. The interface provides real-time visualizations, alerts, and reports, enabling efficient decision-making and response to potential threats.

In conclusion, this project addresses the critical issue of botnet attacks in computer network security by proposing a comprehensive solution that leverages advanced technologies and methodologies. The system’s architecture, coupled with a user-friendly web interface, ensures that it can be seamlessly integrated into existing network environments, enhancing overall security posture.

botnet attack in computer network security, final year projects
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