AI and IoT: Accelerating the Power of DDoS Attacks
International Workshop on Understanding and Defending Against AI-Augmented IoT Threats
About This Course
AI and IoT: Accelerating the Power of DDoS Attacks is an advanced-level international workshop designed to uncover the growing intersection between AI, IoT proliferation, and cyber warfare tactics. While IoT enables real-time connectivity and data-driven automation, it also exposes critical vulnerabilities that cyber attackers now amplify using AI.
Participants will dive deep into DDoS attack vectors, AI-based botnet orchestration, anomaly detection, network traffic modeling, and real-time mitigation frameworks. Using tools like Wireshark, Scapy, TensorFlow, Snort, and Keras, attendees will gain hands-on experience in both attack simulation and intelligent defense implementation.
Aim
To explore how Artificial Intelligence (AI) and Internet of Things (IoT) technologies are being exploited to scale and automate Distributed Denial-of-Service (DDoS) attacks, and to train participants in identifying, simulating, and mitigating such cyber threats using advanced defense strategies.
Workshop Objectives
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Reveal the dual-use potential of AI in cybersecurity—both attacker and defender roles
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Train participants to implement robust, AI-based defense architectures
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Encourage ethical use of penetration testing tools in research and training
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Prepare professionals to defend next-gen smart ecosystems from intelligent threats
Workshop Structure
🔹 Day 1: The Evolving Cyber Threat Surface – DDoS in the Age of AI & IoT
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Understanding the Modern IoT Threat Landscape
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Device sprawl, vulnerabilities, and real-world incidents
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Anatomy of DDoS Attacks in IoT Ecosystems
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Volumetric, protocol exploitation, and application layer attacks
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AI as a Force Multiplier for DDoS Campaigns
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Target automation, dynamic payload generation, and swarm intelligence
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Global Case Studies & Cyber Intelligence
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Mirai Botnet 2.0, Mozi, Dark Nexus
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Interactive Demonstration
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Simulated DDoS traffic using open-source toolkits (e.g., LOIC, Hping3)
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Real-time packet analysis with Zeek and Wireshark
🔹 Day 2: Offensive Artificial Intelligence – Automating, Evolving, Attacking
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Adversarial Machine Learning in DDoS Attacks
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ML-based target profiling and attack path optimization
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Deep Reinforcement Learning for Dynamic Attack Strategies
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AI bots adapting in real-time to evade detection and maximize impact
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Bypassing AI Defenses: Adversarial Evasion & Model Poisoning
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Techniques for manipulating and defeating ML-based IDS systems
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Emerging Threat Vectors
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AI-generated network traffic mimicking normal behavior
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Practical Exercise
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Build and test a simple anomaly detection model using Python (e.g., Random Forest or SVM)
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Generate adversarial inputs using FGSM or textGAN
🔹 Day 3: Designing AI-Resilient IoT Architectures – From Detection to Defense
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AI-Augmented Intrusion Detection & Prevention Systems (IDPS)
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Supervised and unsupervised models for real-time traffic scoring
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Federated Learning for Edge-Based Defense
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Privacy-aware distributed models for smart devices
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Security Orchestration, Automation, and Response (SOAR)
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AI integration in automated mitigation pipelines
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Governance, Risk, and Compliance (GRC)
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Alignment with ISO/IEC 27001, NIST RMF, OWASP IoT Top 10, and GDPR
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Capstone Design Project
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Group design of a secure IoT network architecture
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Threat modeling using STRIDE and MITRE ATT&CK for IoT
Who Should Enrol?
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Cybersecurity professionals and network engineers
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AI/ML practitioners working on threat detection
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IoT product developers and embedded systems engineers
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Researchers in cyber warfare, data forensics, and smart systems
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Students with basic knowledge of networking and Python
Important Dates
Registration Ends
06/10/2025
IST 4 PM
Workshop Dates
06/10/2025 – 06/12/2025
IST 7 PM
Workshop Outcomes
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Understand how AI is used offensively in modern DDoS attack strategies
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Learn to simulate and detect malicious traffic patterns using ML models
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Design AI-enhanced security layers for vulnerable IoT networks
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Analyze large-scale network data for real-time anomaly identification
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Receive global certification in AI-driven cybersecurity strategies
Fee Structure
Student Fee
₹1999 | $50
Ph.D. Scholar / Researcher Fee
₹2999 | $60
Academician / Faculty Fee
₹3999 | $70
Industry Professional Fee
₹5999 | $90
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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