Job Description

Freelance Researcher - Layer 3 & Layer 4 DDoS Traffic Simulation, Feature Engineering, and Dataset Development

Lead the design and development of a

network traffic simulation and dataset generation pipeline

focused on OSI Layer 3 and Layer 4 DDoS attack scenarios using

Hping3, Mininet, and CICFlowMeter

.

Implement and document the generation of

normal and attack traffic flows

, ensuring the dataset contains 70+ engineered features, including entropy, TCP flag counts, timing characteristics, and packet-level metadata.

Simulate and capture

ICMP, SYN, UDP, ACK, RST, amplification

, and other L3/L4 attack vectors using controlled Mininet scenarios, producing both

PCAP

and

CSV-formatted

datasets.

Conduct dataset validation, quality assessment, and prepare the dataset for training, testing, and evaluation--particularly against benchmark datasets such as

CICDDoS2019

.

Master's or Ph.D. in

Cybersecurity

,

Computer Networks

,

Information Security

,

Computer Science

, or

Network Engineering

.

Demonstrated academic or practical experience in

network traffic analysis

,

DDoS attack simulation

, or

intrusion detection research

.

Familiarity with

OSI Layer 3 & 4 protocols

, packet structures, and traffic behavior under adversarial conditions.

Traffic Generation:

Hping3 / Scapy (Hping3 is preferred)

Network Emulation/Simulation:

Mininet

Feature Extraction Tools:

CICFlowMeter (CICFlowMeter-V3 preferred)

Data Processing:

Python, Pandas, NumPy

Packet Capture/Analysis:

Wireshark, Tshark, PCAP handling

Minimum

2 years

of hands-on experience in network security research, traffic monitoring, or DDoS simulation.

Prior work involving

network flow feature extraction

, entropy calculations, TCP/UDP behavioral analysis, or attack emulation in virtualized environments.

Experience conducting research involving

custom network datasets

, flow-based IDS/IPS, or anomaly detection models is highly desirable.

Strong understanding of

Layer 3 (ICMP/IP)

and

Layer 4 (TCP/UDP)

protocol behavior under normal and attack conditions.

Ability to generate and analyze attacks such as

ICMP Flood, SYN Flood, UDP Flood, ACK Flood, RST Flood, amplification attacks, and TCP connection exhaustion

.

Knowledge of

entropy-based detection

,

TCP flag analysis

,

flow timing

,

inter-arrival times

, and packet distribution metrics.

Proficiency in handling

PCAP ? CSV

conversions and designing reproducible feature extraction pipelines.

Design, implement, and document a

complete dataset generation pipeline

, including simulation setup, attack execution, PCAP capture, and CSV conversion using CICFlowMeter.

Generate and label

normal (60%)

and

attack (40%)

network flows across 10 selected L3/L4 DDoS attack scenarios.

Extract 70+ dataset features, including

Source IP entropy, TTL variance, packet size distribution, Flow IAT, TCP/UDP flag statistics, SYN/ACK ratio, incomplete handshakes, port entropy

, etc.

Validate dataset quality by analyzing feature distributions, correlations, and flow integrity.

Provide all deliverables, including

PCAP files

,

CSV datasets

,

simulation scripts

, and

technical documentation

.

Ensure originality, academic integrity, and reproducibility throughout the project.

Contact Person:

Gray

+91 95661 33822

Job Types: Freelance, Volunteer
Contract length: 12 months

Pay: ₹20,000.00 - ₹25,000.00 per month

Work Location: Remote