Call for papers/Topics
Topics of interest for submission include any topics related to:
Artificial Intelligence, Machine Learning, and Automated Systems
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Generative AI Models and Architecture: Development of foundation models, large language models, and diffusion systems driving automated tasks.
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Adversarial Machine Learning: Engineering resilience against data poisoning, model inversion, and prompt injection attacks.
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AI-Powered Threat Detection: Applying continuous anomaly detection and behavioral predictive models to isolate network attacks.
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Automated Software Engineering: AI-assisted code generation, static security scanning, and automated bug refactoring during production.
Quantum Information Processing and Hardware
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Quantum Computing Architectures: Hardware implementations using superconducting qubits, trapped ions, and photonic circuits.
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Post-Quantum Cryptography: Designing lattice-based and code-based cryptographic primitives immune to quantum decryption.
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Quantum Key Distribution: Quantum physics-based communication protocols ensuring untamperable key exchange over optical channels.
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Quantum Simulation for Engineering: Utilizing quantum systems to model material physics, chemical reactions, and thermal mechanics.
Cyber-Physical Systems, IoT, and Critical Infrastructure
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Industrial Control System Security: Protecting SCADA and operational technology (OT) platforms from targeted physical and digital sabotage.
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Internet of Things Architecture: Designing low-power processing hardware and micro-kernels for distributed sensors.
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Autonomous Vehicle Engineering: Software safety standards, sensor fusion, and anti-hijacking controls for autonomous transit.
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Digital Twins for Systems Engineering: Virtual mirror modeling of physical infrastructure to simulate wear, load, and cyber-attack scenarios.
Distributed Systems, Cloud, and Edge Computing
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Confidential Computing: Utilizing hardware-enforced Trusted Execution Environments (TEEs) to process encrypted data safely.
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Edge Intelligence and Fog Computing: Distributing compute capacity closer to data sources to lower latency and preserve network bandwidth.
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Zero Trust Architecture: Continuous identity verification, strict access controls, and micro-segmentation across distributed multi-cloud networks.
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Decentralized Infrastructure and Ledger Systems: Using consensus mechanisms and smart contract security to secure supply chains and immutable logging.
Software Engineering, DevSecOps, and Supply Chain
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DevSecOps Automation: Embedding static and dynamic continuous integration pipeline security testing directly into development workflows.
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Software Supply Chain Security: Managing Software Bill of Materials (SBOMs), verifying open-source dependencies, and preventing repository attacks.
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Microservices and Container Security: Securing orchestration platforms, API gateways, and container runtime environments.
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Formal Verification and Code Correctness: Mathematical proof techniques applied to software systems to guarantee safety and vulnerability absence.
Privacy-Preserving and Applied Cryptography
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Homomorphic Encryption: Cryptographic schemes allowing mathematical computations directly on encrypted data without prior decryption.
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Federated Learning and Differential Privacy: Training machine learning models across decentralized nodes while mathematically protecting individual node privacy.
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Zero-Knowledge Proofs: Cryptographic methods proving statement validity without revealing underlying sensitive information.
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Hardware Security and Roots of Trust: On-chip cryptographic coprocessors, physically unclonable functions (PUFs), and side-channel attack countermeasures.





