Anirudh Khanna
Data Protection Solution Architect
Plano, Texas, United States
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With over 17 years of dedicated experience in the critical fields of backup and recovery, disaster recovery, and cyber recovery, I have developed a deep understanding and expertise in safeguarding data and ensuring business continuity in the face of ever-evolving cyber threats. My career journey has been driven by a relentless pursuit of excellence in protecting vital information assets and supporting organizations in their quest for robust, fail-safe recovery strategies.
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Sustainable Resilience: Green-Centric Backup and Cyber Recovery Strategies for a Digital-First World
As the energy and utility sectors increasingly embrace digital transformation, the demand for robust backup and recovery systems has never been higher. Yet, the environmental impact of traditional data protection practices often goes unnoticed. In this session, we explore a sustainable vision for resilient IT infrastructures.
Drawing on real-world deployments and innovations, this talk examines how to blend cyber resilience with environmental responsibility. Topics include:
Eco-friendly recovery strategies using AI, deduplication, and tiered storage
Green cloud-native backup solutions and energy-efficient DRaaS models
Resilience-driven architectures leveraging predictive analytics and real-time replication
Sustainability challenges and mitigation techniques in high-scale recovery
The role of blockchain and quantum-safe encryption in immutable, future-proof data recovery
We’ll also showcase case studies from the utility industry, including how organizations have navigated natural disasters and ransomware attacks through cloud-based DR, offsite replication, and AI-powered proactive restoration. Attendees will gain actionable insights into building cyber-secure and carbon-conscious backup strategies—ensuring business continuity without compromising sustainability goals.
This session is designed for cybersecurity leaders, resilience architects, energy sector IT strategists, and academic researchers focused on the convergence of digital resilience and environmental stewardship.
Cybersecurity for Smart Grids: AI-Driven Defense Strategies for Modern Energy Infrastructure
As utilities increasingly adopt smart grids to modernize energy delivery, the integration of IoT, AI, and real-time data systems has significantly expanded the cybersecurity threat landscape. This session explores the evolving challenges and advanced solutions for securing critical energy infrastructure in the digital age.
This session will provide an in-depth examination of cyber threats targeting smart grids—from false data injection and denial-of-service (DoS) attacks to ransomware and insider threats. It presents actionable strategies that combine real-time monitoring, AI-enhanced intrusion detection systems (IDS), and deep learning techniques like RNNs, GANs, and autoencoders to detect and neutralize sophisticated attacks. The session also highlights proactive risk management practices, collaborative defense frameworks, and regulatory considerations to ensure uninterrupted energy delivery.
Attendees will learn:
How to detect and respond to FDI and DoS attacks using deep learning models
Best practices for implementing resilient architectures with secure communication protocols
The role of real-time analytics and AI in dynamic threat mitigation
How utilities can align with NERC CIP, NIST, and IEC cybersecurity standards
Case studies on cyber events in critical infrastructure and how to prepare recovery responses
This presentation delivers a forward-looking blueprint for energy providers, cybersecurity professionals, and researchers to build smart grid environments that are not only intelligent—but secure, resilient, and future-ready.
AI-Driven Cybersecurity: Interpretable Models for Anomaly Detection
This session highlights cutting-edge approaches to cybersecurity powered by AI and machine learning. It emphasizes the use of Generalized Isolation Forest algorithm for detecting anomalies in network traffic, coupled with Explainable AI (XAI) techniques to provide transparency in threat detection. Attendees will learn how to enhance trust and accountability in security systems while maintaining high detection performance — a crucial step toward safer, smarter, and more collaborative digital ecosystems.
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