Cybersecurity Engineer – DDoS Traffic Simulation, Data Attack Analysis \& Dataset DevelopmentJob Overview
We are seeking a highly skilled Cybersecurity Engineer with strong expertise in network attack simulation, Layer 3 \& Layer 4 DDoS traffic generation, feature engineering, and dataset development. The ideal candidate will design and execute end-to-end pipelines for generating high-fidelity network datasets used for research, detection modeling, and cybersecurity system evaluation. This role involves hands-on work with tools such as Hping3, Mininet, Wireshark/tcpdump, and CICFlowMeter, and requires strong analytical skills for validating dataset quality and integrity.
Key Responsibilities1. DDoS Attack Simulation \& Traffic Generation
Design and execute Layer 3 and Layer 4 DDoS attack scenarios using tools such as Hping3, Mininet, and custom traffic scripts.
Simulate at least 10 realistic DDoS attack vectors, including SYN floods, UDP floods, ICMP floods, TCP fragmentation attacks, and other volumetric or protocol-abusing scenarios.
Generate controlled normal and malicious network traffic while maintaining a clean, reproducible simulation environment.
2. Dataset Pipeline Development
Design, implement, and document a complete dataset generation pipeline, including:
Network topology setup (Mininet/virtual lab)
Attack execution and traffic orchestration
PCAP capture using tcpdump/Wireshark
Flow-based feature extraction with CICFlowMeter
CSV dataset generation and metadata alignment
Ensure the pipeline is modular, reproducible, and version-controlled.
3. Flow Labeling \& Dataset Composition
Generate, balance, and label normal (60%) and attack (40%) traffic flows.
Assign accurate ground-truth labeling for all flows across the 10 selected scenarios.
4. Feature Engineering \& Analysis
Extract 70+ network features, including but not limited to:
Source IP entropy, TTL variance, packet size distribution
Flow IAT statistics
TCP/UDP flag patterns
SYN/ACK ratios and incomplete handshake indicators
Port entropy, burstiness, flow duration metrics
Perform exploratory data analysis to assess feature distributions, correlations, anomalies, and dataset completeness.
5. Dataset Quality Validation
Validate dataset correctness by analyzing:
Feature integrity and consistency
Corruption or missing-flow detection
Correlation matrices and multicollinearity
Attack/normal traffic separability
Produce summary statistics, validation reports, and visualizations as required.
6. Documentation \& Deliverables
Deliver a complete, well-structured research package, including:
All PCAP files, CSV datasets, and extracted features
All simulation and attack scripts
Step-by-step technical documentation
Architecture diagrams, flow charts, and reproducibility notes
Ensure the dataset meets standards of originality, academic integrity, and reproducibility.
Required Skills \& Qualifications
Bachelor’s or Master’s degree in Cybersecurity, Computer Science, Network Engineering, or related field.
Strong understanding of TCP/IP, L3/L4 protocols, and DDoS attack fundamentals.
Hands-on experience with Hping3, Mininet, CICFlowMeter, tcpdump, and Linux-based network tools.
Experience with dataset development, feature engineering, and network traffic analysis.
Proficiency in Python or Bash for automation and workflow scripting.
Familiarity with packet analysis, flow analysis, and security research methodologies.
Preferred Qualifications
Experience with network simulation frameworks or SDN.
Background in cybersecurity research or academic dataset development.
Knowledge of anomaly detection, ML-based intrusion detection systems (IDS), or traffic classification.
Contact person:
Gray-95661 33822
Job Types: Part-time, Freelance, Volunteer
Contract length: 1 month
Pay: From ₹10,000.00 per month
Work Location: Remote