#Cybersecurity & Ethical Hacking

• Prompt-Injection-Resistant Enterprise Copilots: A Three-Layer Defense Framework
• Post-Quantum Readiness for Developers: A Practical Migration Plan for APIs, Keys, and Data in 2025
• Prompt Security Playbook: Defense-in-Depth for Enterprise LLM Copilots
• Edge AI for Threat Detection: Privacy-Preserving On-Device Anomaly Detection Accelerates Zero-Trust Security in IoT
• Post-quantum cryptography for 5G/6G networks: a practical roadmap for telecom operators to stay secure in the quantum era
• TinyML at the Edge: A practical blueprint for on-device anomaly detection to secure IoT devices with privacy-preserving AI in 2025
• On-Device AI for Real-Time Threat Detection: Edge ML Strategies to Secure IoT Devices Without Cloud Latency
• Edge AI for Real-Time, Privacy-Preserving Inference on Mobile Devices
• On-device Federated Learning for IoT Security: A practical blueprint for privacy-preserving, real-time threat detection at the edge
• Post-Quantum Migration Playbook for Fintech: Crypto Agility, Migration Timelines, and Regulatory Implications
• Federated On-Device AI for Zero-Trust Threat Detection in Cloud-Native and IoT Ecosystems
• PromptGuard: Practical framework for adversarial testing and runtime guardrails to secure LLM-powered applications against prompt injections
• Prompt Injection in Production LLM Security Tools: A Practical Mitigation Playbook for SOCs in 2025
• Preparing Cloud-Native Apps for Post-Quantum Cryptography: A Practical Phased Plan
• Prompt-Secure AI: Building an Enterprise Defense Playbook for LLM Deployments (2025)
• Prompt Security in Production AI: A Practical Lifecycle for Defending LLM Deployments Against Jailbreaks, Data Leaks, and Prompt Injection
• On-device Federated Learning for IoT Security: A Practical Blueprint for Lightweight Edge AIs to Detect Threats Without Transmitting Raw Data
• TinyML on the Edge: On-device Anomaly Detection and Autonomous Response for IoT Security
• Prompt Injection in AI copilots: practical defenses for production stacks in 2025
• Zero-Trust AI in the Cloud: How post-quantum cryptography, attestation, and secure enclaves enable quantum-resistant, privacy-preserving ML inference at scale
• Federated Learning at the Edge: Privacy-Preserving AI for Real-Time IoT Security in 5G/6G Smart Cities