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Development of a Network Traffic Analysis Web Application for Malware Detection and Cyber Threat Forensics
  1. case
  2. Development of a Network Traffic Analysis Web Application for Malware Detection and Cyber Threat Forensics

Development of a Network Traffic Analysis Web Application for Malware Detection and Cyber Threat Forensics

profil-software.com
Energy & natural resources
Government
Telecommunications

Identifying Challenges in Network Traffic Analysis and Cybersecurity for Complex Infrastructure

The client faces significant challenges in analyzing large volumes of network traffic data captured in PCAP files to identify malicious patterns, anomalies, and potential cyber threats. Their existing tools lack the capability for comprehensive, real-time analysis and secure collaboration, hampering incident response and forensic investigations within their complex, segmented network environment.

About the Client

A mid-sized organization with complex network infrastructure seeking advanced cybersecurity measures to analyze network traffic, detect malicious activities, and enhance forensic investigation capabilities.

Goals to Enhance Network Security and Traffic Forensics Capabilities

  • Implement a web-based application capable of efficiently reading, parsing, and analyzing extensive PCAP data files for threat detection.
  • Enable detection of malicious software, unusual patterns, and anomalies within network traffic to preempt cyber threats.
  • Design a secure infrastructure incorporating best practices like firewalls, subnet segmentation, and access controls to protect sensitive data.
  • Create an intuitive and accessible user interface for cybersecurity teams to perform analysis and collaborate effectively.
  • Facilitate scalable processing to handle increasing data volumes with high performance and security standards.

Core Functionalities for Network Traffic Analysis and Threat Detection

  • Ability to upload, read, and parse PCAP files containing extensive network traffic data.
  • Advanced algorithms for detecting malicious activity, anomalies, and suspicious patterns in network traffic.
  • Visualization tools for traffic patterns, flow analysis, and threat alerts.
  • Secure user authentication and role-based access controls for sensitive data protection.
  • Collaborative workspace enabling team-based analysis and sharing of findings.
  • Real-time processing capabilities for timely threat detection and incident response.

Preferred Technologies and Architectural Approaches for Development

Kubernetes for scalable deployment
PostgreSQL for data management
Python for backend analytics
Secure web frameworks for frontend development with accessible UI design

Necessary External Integrations and Data Sources

  • Security Information and Event Management (SIEM) systems for threat correlation
  • Existing firewall and network access control systems for data import
  • Authentication and user management platforms for secure login
  • Internal threat intelligence feeds for enhanced detection

Critical Non-Functional System Requirements

  • System must process large PCAP files efficiently, supporting files of at least several gigabytes in size.
  • Achieve high security standards with data encryption, firewalls, and access controls.
  • Ensure system availability with 99.9% uptime and fast response times for analysis tasks.
  • Design for scalability to accommodate growing data volumes and user base.
  • Compliance with industry cybersecurity standards and data privacy regulations.

Projected Business Impact and Performance Benefits

The implementation of this network traffic analysis solution aims to significantly enhance cybersecurity incident response efficiency, enabling the detection and mitigation of malicious activity with greater accuracy. Expected outcomes include improved threat detection, reduced analysis time, and compliance with security standards, ultimately strengthening the organization's defense against cyber threats and minimizing potential data breaches.

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