PROBLEM STATEMENT - PACKET SNIFFER CASE STUDY

📡 Network Packet Analyzer for Educational Purposes

1. 🌐 Project Overview

In computer networks education, students and educators need practical tools to understand how data flows across networks. A packet sniffer is an essential learning tool that captures and displays network packets, helping users understand network protocols, troubleshoot connectivity issues, and learn network security concepts.

2. 🎯 Problem Description

Educational institutions lack accessible, easy-to-understand packet analysis tools for teaching network concepts. Existing tools like Wireshark, while powerful, can be overwhelming for beginners. There's a need for a simplified, educational-focused packet sniffer that provides:

  • Educational Focus: Clear explanations of network protocols and packet structures
  • Simplified Interface: User-friendly design for students and educators
  • Real-time Monitoring: Live packet capture and analysis
  • Learning Features: Built-in tutorials and protocol explanations

3. 📋 Functional Requirements

Category Requirement Description
Core Features Packet Capture Capture packets from network interfaces (Ethernet, WiFi)
Protocol Analysis Decode common protocols (TCP, UDP, HTTP, ICMP, DNS)
Real-time Display Show captured packets in real-time with basic details
Basic Filtering Filter by IP address, port number, and protocol type
Educational Features Protocol Explanations Built-in help explaining each protocol and header field
Packet Structure View Visual representation of packet headers and data
Learning Mode Guided tutorials for understanding network concepts
Data Management Save/Export Save captured data to files (CSV, text format)
Session Management Start, stop, and manage capture sessions

4. 🔧 Technical Requirements

System Architecture:

Network Interface Layer
↓ Raw Packets
Packet Capture Engine
↓ Captured Data
Protocol Parser Layer
↓ Decoded Headers
Filter Engine Layer
↓ Filtered Results
User Interface Layer

Performance Specifications:

  • Packet Rate: Handle up to 100 packets per second
  • Memory Usage: Maximum 256 MB RAM usage
  • Response Time: Display packets within 500ms of capture
  • Storage: Store up to 10,000 packets per session
  • Platform: Windows and Linux compatibility

5. 👥 Target Users

  • Computer Science Students: Learning networking concepts
  • Network Instructors: Teaching network protocols and analysis
  • IT Support Staff: Basic network troubleshooting
  • Hobbyist Developers: Understanding network communications

6. 📊 Success Criteria

Metric Target Value Measurement Method
Packet Capture Accuracy 95% of packets captured Comparison with reference tools
User Interface Usability 4/5 user satisfaction rating User surveys and testing
Educational Effectiveness 80% improvement in learning Pre/post knowledge assessment
System Stability Run continuously for 2+ hours Stress testing and monitoring
Cross-platform Compatibility Works on Windows and Linux Testing on multiple platforms

7. ⚠️ Project Constraints

  • Development Time: 10-12 weeks (academic semester)
  • Team Size: 3-4 students
  • Budget: Zero budget (open-source tools only)
  • Technology Stack: Python with standard libraries
  • Legal Requirements: Educational use only, no malicious capabilities
SELECTED PROCESS MODEL - JUSTIFICATION

🎯 Selected Model: INCREMENTAL PROCESS MODEL

1. 📊 Model Selection Analysis

Comparison Matrix:

Criteria Waterfall Incremental Evolutionary Agile
Fixed Timeline Excellent Good Poor Fair
Modular Architecture Poor Excellent Fair Good
Early Testing Poor Excellent Good Excellent
Student Team Suitability Good Excellent Poor Fair
Documentation Excellent Good Poor Poor
Risk Management Poor Excellent Good Good
DETAILED JUSTIFICATION

2. 🔍 Detailed Justification

A) Project Characteristics Favoring Incremental Model:

📦 Natural Modularity:

The packet sniffer has distinct functional modules that can be developed independently:

  • Core Capture Engine: Network interface access and raw packet capture
  • Protocol Parser: Decoding different network protocols
  • Filter System: Packet filtering and search functionality
  • User Interface: Display and interaction components
  • Data Export: File saving and export features
⏰ Academic Timeline Constraints:

The incremental approach fits perfectly with academic requirements:

  • Semester Duration: 10-12 weeks allows for 5 clear increments
  • Milestone Submissions: Each increment provides demonstrable progress
  • Professor Reviews: Regular evaluation at increment completion
  • Student Learning: Gradual skill building through increments

B) Implementation Strategy:

Increment Duration Features Deliverable
1 Weeks 1-2 Basic packet capture, Network interface selection Command-line tool that captures and displays raw packets
2 Weeks 3-4 TCP/UDP/ICMP parsing, Header extraction Enhanced tool showing protocol information
3 Weeks 5-6 Basic filtering, IP/Port filters Packet sniffer with filtering capabilities
4 Weeks 7-8 File export, Session management Complete CLI packet analyzer
5 Weeks 9-10 Graphical interface, Educational features Full GUI packet sniffer with learning features

3. ❌ Why Other Models Are Less Suitable:

🚫 Waterfall Model - Not Suitable:
  • Late Testing Risk: Network programming is complex and requires early testing
  • No Early Feedback: Students need continuous guidance and evaluation
  • Integration Challenges: Network protocols have many edge cases
  • Inflexible Timeline: Academic deadlines don't allow for major revisions
🚫 Agile Model - Not Optimal:
  • Overhead for Students: Sprint ceremonies consume valuable development time
  • Limited Customer Access: Professor availability is restricted
  • Documentation Requirements: Academic projects need formal documentation
  • Scope Creep Risk: Students may add unnecessary features
🚫 Evolutionary Model - Not Practical:
  • Time Constraints: Academic semester is too short for multiple evolution cycles
  • Resource Limitations: Students lack experience for rapid prototyping
  • Unclear Requirements: Educational objectives are well-defined
  • Assessment Challenges: Difficult to grade evolving prototypes

4. 🎯 Expected Benefits of Incremental Approach:

✅ Academic Benefits:

  • Progressive Learning: Students build skills incrementally
  • Regular Assessment: Professors can evaluate at each stage
  • Risk Mitigation: Problems identified early in development
  • Motivation: Working software at each increment
  • Teamwork: Clear division of responsibilities

✅ Project Benefits:

  • Quality Assurance: Testing at each increment
  • Modular Design: Clean, maintainable architecture
  • Early Functionality: Basic packet capture available early
  • Flexible Scope: Advanced features can be adjusted
  • Documentation: Incremental documentation development

5. 📋 Success Metrics for Incremental Development:

  • Increment Completion Rate: Target 100% on-time completion
  • Code Quality: Maintain consistent quality across increments
  • Integration Success: Smooth integration between increments
  • Learning Objectives: Meet educational goals at each stage
  • Team Collaboration: Effective teamwork and communication