Call for Papers

Scope

The International Conference on Intelligent Digital Forensics and Cybersecurity (IDFC 2026) aims to bring together leading researchers, practitioners, and policymakers to share advances in forensic science, cybersecurity defense, and intelligence analytics. With the proliferation of AI, including the recent rise of generative AI, IoT, blockchain, and cloud technologies, the boundaries between cybersecurity and forensics are increasingly intertwined. IDFC 2026 provides a platform to explore the convergence of these domains for effective cybercrime prevention, digital evidence handling, and trust preservation.

The conference invites novel contributions that address emerging threats, privacy challenges, and innovative tools that strengthen cyber defense and forensic investigations across multiple disciplines. In particular, IDFC 2026 seeks to highlight the transformative role of generative AI and other emerging technologies in shaping the future of digital forensics and cybersecurity. Contributions exploring the creation and detection of synthetic content, deepfake forensics, generative threat modeling, and AI-driven forensic intelligence are especially encouraged. By fostering dialogue on these cutting-edge intersections, IDFC 2026 aims to promote resilient, adaptive, and intelligent cyber-forensic ecosystems that uphold digital trust and transparency.

Key Research Areas:

Advanced Digital Forensics
Cybersecurity and Cyber Defense
AI/ML for Security and Forensics
Generative AI and Synthetic Media

Privacy-Preserving Forensics
Blockchain and Financial Crime
IoT and Cyber-Physical Systems
Human and Social Dimensions

Legal, Ethical, and Policy
Applied Systems and Case Studies
Visionary and Emerging Topics
Privacy-Preserving Federated Learning

Extended Topics of Interest

IDFC 2026 welcomes original research, case studies, systems, datasets, and visionary papers addressing (but not limited to) the following topics.

Advanced Digital Forensics

Memory, firmware, and hardware-assisted forensics
Live forensics and real-time evidence acquisition
Cross-platform and cross-device forensic correlation
Timeline reconstruction and event attribution at scale
Forensics for encrypted, ephemeral, and volatile data
Automated triage and prioritization of digital evidence
Multimedia forensics (image, video, audio, and sensor data)
Forensics for cyber-physical systems and smart infrastructures

Next-Generation Cybersecurity and Cyber Defense

AI-driven cyber defense and autonomous response systems
Adversarial attacks against security systems and AI models
Post-quantum cryptography and forensic readiness
Cyber deception, honeypots, and active defense strategies
Supply-chain attacks and software integrity verification
Detection and mitigation of insider threats
Security for 5G/6G networks and edge computing
Cyber resilience and recovery modeling

AI and Machine Learning for Security and Forensics

Foundation models for security analytics
Multimodal AI for forensic reasoning and correlation
Continual, online, and adaptive learning in forensic systems
Robust ML against poisoning and evasion attacks
Human-in-the-loop AI for investigative decision support
Causal AI for cyber incident attribution
Trust, fairness, and bias analysis in forensic AI
Benchmarking datasets and evaluation metrics for forensic AI

Generative AI and Synthetic Media Forensics

Detection, attribution, and provenance of AI-generated content
Deepfake forensics for images, video, voice, and text
Watermarking, fingerprinting, and content authenticity verification
Generative AI for attack simulation and red teaming
Generative models for reconstructing missing or damaged evidence
Prompt forensics and analysis of LLM misuse
Adversarial generative models and forensic countermeasures
Forensics of AI agents and autonomous systems

Privacy-Preserving, Distributed, and Trustworthy Forensics

Federated and decentralized forensic learning
Secure multi-party computation for investigations
Homomorphic encryption in forensic analytics
Confidential computing and trusted execution environments
Privacy-preserving evidence sharing across organizations
Secure data collaboration between law enforcement and industry
Transparency, auditability, and reproducibility in forensic systems

Blockchain, Web3, and Financial Crime Forensics

Smart contract analysis and vulnerability forensics
Cryptocurrency tracing and transaction graph analysis
DeFi fraud, rug pulls, and NFT-related crimes
Forensics for decentralized identity (DID) systems
Tokenomics manipulation and market abuse detection
Cross-chain forensic analysis and interoperability challenges

IoT, Edge, and Cyber-Physical System Forensics

Forensics for smart homes, vehicles, drones, and wearables
Industrial IoT (IIoT) and critical infrastructure forensics
Edge AI security and forensic challenges
Digital twins for forensic reconstruction
Sensor data integrity and provenance verification

Human, Social, and Cognitive Dimensions of Cybercrime

Social engineering and phishing analysis using AI
Behavioral analytics for insider threat detection
Cognitive forensics and decision-making under uncertainty
Misinformation, disinformation, and influence operations
Online radicalization and coordinated inauthentic behavior

Legal, Ethical, and Policy Perspectives

Legal implications of AI-generated evidence
Explainability requirements for AI in court proceedings
Standards and certification for forensic AI tools
Accountability and liability in automated investigations
Cross-border evidence sharing and digital sovereignty
Ethics-by-design for intelligent forensic systems
Policy frameworks for regulating generative AI misuse

Applied Systems, Tools, and Case Studies

End-to-end forensic platforms and real-world deployments
National and international cybercrime case studies
Public-private collaboration models in cyber investigations
Evaluation of forensic tools in operational environments
Lessons learned from large-scale cyber incidents

Visionary and Emerging Topics

Self-healing and self-forensic cyber systems
Autonomous cyber investigators and AI agents
Forensics for metaverse and extended reality (XR) environments
Digital trust ecosystems and evidence provenance at scale
The future of cyber forensics in an AI-native world

Privacy-Preserving Federated Learning

Federated learning for collaborative forensic analysis
Differential privacy in distributed cyber investigations
Secure multi-party computation for evidence sharing
Privacy-aware threat intelligence aggregation
Homomorphic encryption for forensic data processing