Sachin Shetty
6 papers in the PaperMetrix corpus
Papers by this author
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Towards Optimal Cyber Defense Remediation in Energy Delivery Systems
2019
Prioritized cyber defense remediation plan is critical for effective risk management in Energy Delivery System (EDS). Due to the complexity of EDS in terms of heterogeneous nature blending Information Technology (IT) and Operation Technology (OT) …
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Blockchain and Self-Sovereign Identity Empowered Cyber Threat Information Sharing Platform
2021
Cyber threat information (CTI) sharing involves processes of the collection, analysis and sharing of cyber threat information among multiple organizations. CTI is highly sensitive and inadvertent access can harm an organisation’s reputation. Moreover, CTI sharing …
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ATTL: An Automated Targeted Transfer Learning with Deep Neural Networks
2021 · 2021 IEEE Global Communications Conference (GLOBECOM)
Success of machine learning algorithms hinges on access to labeled dataset. Obtaining a labeled dataset is an expensive, challenging and time-consuming process, leading to the development of transfer learning (TL) methodology. TL incorporates gained knowledge …
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LUUNU — Blockchain, MISP, Model Cards and Federated Learning Enabled Cyber Threat Intelligence Sharing Platform
2022
Cyber Threat Intelligence (CTI) is a process of threat data collection, processing, and analysis to understand a threat actor’s motives, targets, and attack behaviors. CTI involves highly sensitive data and any inadvertent access to it …
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Proof-of-Pedal — Pedal-Powered Byzantine Green Consensus for Blockchain
2023
Blockchain technologies have gained significant popularity for their decentralized and tamper-evident characteristics. The key component of these technologies is the consensus protocol that dictates the correctness and operational efficiency of the system. Bitcoin’s Proof of …
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Privacy Drift: Evolving Privacy Concerns in Incremental Learning
2024 · arXiv (Cornell University)
In the evolving landscape of machine learning (ML), Federated Learning (FL) presents a paradigm shift towards decentralized model training while preserving user data privacy. This paper introduces the concept of ``privacy drift", an innovative framework …