Author: Emerald Knox (Emerald Knox)

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Efficient Protection of Design IP: Disguising the Interconnects

Satwik Patnaik , Mohammed Ashraf  , Johann Knechtel , and Ozgur Sinanoglu Ensuring the trustworthiness and security of electronics has become an urgent challenge in recent years. Among various concerns, the protection of design intellectual property (IP) is to be addressed, due to outsourcing trends for the manufacturing supply chain and malicious end-user. In other...

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Hardening the Hardware: A Reverse-engineering Resilient Secure Chip

Abhrajit Sengupta, Muhammad Yasin, Mohammed Nabeel, Mohammed Ashraf, Jeyavijayan Rajendran and Ozgur Sinanoglu With the globalization of integrated circuit (IC) supply chain, the semi-conductor industry is facing a number of security threats, such as Intellectual Property (IP) piracy, hardware Trojans, and counterfeiting. To defend against such threats at the hardware level, logic locking was proposed as...

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On Multi-Phase and Multi-Stage Game-Theoretic Modeling of Advanced Persistent Threats

Quanyan Zhu and Stefan Rass Advanced persistent threats (APT) are considered as a significant security threat today. Despite their diversity in nature and details, a common skeleton and sequence of phases can be identified that these attacks follow (in similar ways), which admits a game-theoretic description and analysis. This paper describes a general framework that...

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Adaptive and Resilient Revenue Maximizing Dynamic Resource Allocation and Pricing for Cloud-Enabled IoT Systems

Muhammad Junaid Farooq and Quanyan Zhu Cloud computing is becoming an essential component in the emerging Internet of Things (IoT) paradigm. The available resources at the cloud such as computing nodes, storage, databases, etc. are often packaged in the form of virtual machines (VMs) to be used by remotely located IoT client applications for computational...

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ADMM-based Networked Stochastic Variational Inference

Hamza Anwar and Quanyan Zhu Owing to the recent advances in “Big Data” modeling and prediction tasks, variational Bayesian estimation has gained popularity due to their ability to provide exact solutions to approximate posteriors. One key technique for approximate inference is stochastic variational inference (SVI) [1]. SVI poses variational inference as a stochastic optimization problem...