Background

With the increasing sophistication of cyber threats such as Advanced Persistent Threats (APTs), ransomware, insider attacks, and data exfiltration, malicious activities are often concealed within legitimate network traffic. Traditional security systems struggle to detect such stealthy attacks in real time.

Law enforcement agencies, including the Cyber Crime Branch, Ahmedabad City, require advanced forensic tools capable of deep packet inspection, traffic analysis, and evidence generation to investigate cyber incidents effectively.

A centralized platform for capturing, analysing, and visualizing network traffic can significantly enhance the ability to detect hidden threats, reconstruct attack patterns, and generate legally admissible digital evidence.

Problem Statement

Design and develop a Network & Packet Forensics Platform capable of capturing, storing, and analysing live as well as historical network traffic to detect anomalies such as data exfiltration, covert communication channels, insider threats, and malware activity.

The system should provide deep packet inspection, protocol decoding, signature-based detection, and AI-driven anomaly detection, along with visualization tools for traffic flows and attack patterns. It must support forensic investigation workflows and enable secure export of evidence for legal proceedings.

The objective is to equip the Cyber Crime Branch with a robust, scalable, and intelligent network forensic system for proactive threat detection and post-incident investigation.

Key Objectives

• Capture and analyse live and stored network traffic
• Detect anomalies including APTs, exfiltration, and hidden tunnels
• Provide deep packet inspection and protocol decoding
• Enable signature-based and AI-based threat detection
• Visualize network flows and suspicious activities
• Support forensic investigation and evidence generation
• Integrate with cybercrime investigation systems
• Ensure secure and legally compliant data handling

Functional Requirements

1. Packet Capture & Ingestion System

• Capture live network traffic (PCAP format support)
• Import and analyse stored packet capture files
• High-throughput packet processing
• Filtering based on IP, protocol, port, etc.

 

 

2. Deep Packet Inspection (DPI)

• Protocol decoding (HTTP, HTTPS, DNS, FTP, SMTP, etc.)
• Payload inspection for hidden data
• Detection of encrypted and obfuscated traffic patterns
• Session reconstruction

3. Threat Detection Module

• Signature-based detection (known attack patterns)
• Detection of malware communication and botnets
• Identification of data exfiltration attempts
• Detection of covert channels and tunnelling (DNS, ICMP, etc.)

4. AI-Based Anomaly Detection

• Behavioural analysis of network traffic
• Detection of unusual traffic spikes and patterns
• Insider threat detection
• Identification of zero-day or unknown attacks

5. Traffic Flow Visualization

• Graph-based visualization of network communication
• Flow diagrams (source → destination mapping)
• Timeline-based activity tracking
• Highlighting suspicious nodes and connections

6. Forensic Investigation Module

• Search and filter historical traffic
• Reconstruction of attack scenarios
• Timeline correlation of events
• Case management for investigators

7. Evidence Collection & Reporting

• Export of forensic data (PCAP, logs, reports)
• Tamper-proof storage with timestamps
• Chain-of-custody tracking
• Automated report generation for legal use

8. Integration with Cyber Crime Systems

• Integration with Cyber Crime Branch databases
• Linking network evidence with reported cases
• Support for digital forensic workflows
• API-based integration with other investigation tools

9. Dashboard & Analytics

• Real-time monitoring dashboard
• Alerts for suspicious activities
• Traffic statistics and trends
• Investigator-friendly UI

10. Data Security & Compliance

• Encryption of captured data
• Role-based access control
• Secure storage and access logs
• Compliance with digital evidence standards

Evaluation Criteria

• Accuracy of anomaly and threat detection
• Efficiency of packet capture and processing
• Quality of traffic visualization and insights
• Effectiveness in forensic investigation workflows
• Scalability and system performance
• Data security and legal compliance
• Usability for law enforcement personnel
• Real-world applicability in cybercrime investigations

Suggested Tools/Technologies

• Backend: Python (Django/Flask), Node.js
• Packet Processing: Wireshark libraries, Scapy, Zeek
• Frontend: React.js / Angular
• Database: Elasticsearch / PostgreSQL / MongoDB
• AI/ML: TensorFlow / PyTorch / Scikit-learn
• Streaming: Apache Kafka
• Visualization: D3.js / Kibana

Bonus Points

• Real-time alerting system for active threats
• Integration with SIEM systems
• Encrypted traffic analysis without decryption (metadata-based)
• Automated attack classification
• Multi-language support for reports
• Cloud-based scalable deployment

Deliverables

• Working prototype/demo (live or simulated traffic)
• Packet analysis and visualization dashboard
• Threat detection demonstration
• Forensic report generation sample
• Documentation (architecture, workflows, detection methods)
• Deployment setup (containerized/cloud-ready preferred)