Advanced Technology Group
in the Corporate Strategy Office

On the Universally Composable Security of OpenStack

Hoda Maleki (University of Connecticut); Kyle Hogan (MIT); Reza Rahaeimehr (University of Connecticut); Ran Canetti, Mayank Varia, Jason Hennessey (Boston University and NetApp); Marten van Dijk (University of Connecticut); Haibin Zhang (UMBC)

Specifically, this work concentrates on the high-level struc-ture of OpenStack, leaving the further formalization and moredetailed analysis of specific OpenStack services to future work.Specifically, we formulate ideal functionalities that correspond tosome of the core OpenStack modules, and then proves securityof the overall OpenStack protocol given the ideal components.

FlexGroup Volumes: A Distributed WAFL File System

Ram Kesavan, Google; Jason Hennessey, Richard Jernigan, Peter Macko, Keith A. Smith, Daniel Tennant, and Bharadwaj V. R., NetApp

2019 USENIX Annual Technical Conference

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Jian Huang, University of Illinois at Urbana-Champaign

Hardware-Assisted Secure Flash-Based Storage

Modern storage systems have been developed for decades with the security-critical foundation provided by operating system (OS). However, they are still vulnerable to malware attacks and software defects. Adversaries can obtain the OS kernel privilege or leverage software vulnerabilities to bypass, terminate or destroy current malware detection and defense systems. For instance, encryption ransomware accounts for more than half of all malware attacks today, but current software-based defense systems often fail to enable the victims to say no to ransom collectors. Therefore, it is natural to utilize hardware techniques which have been proven effective in defending against malware attacks.

Eamonn Keogh, UC Riverside – August 2018

Time Series Snippets: A New Analytics Primitive with applications to IoT Edge Computing

While most of today’s always-connected tech devices take advantage of cloud computing, many Internet of Things (IoT) developers increasingly understand the benefits of doing more analytics on the devices themselves, a philosophy known as edge computing. By performing analytic tasks directly on the sensor, edge computing can drastically reduce the bandwidth, cloud processing, and cloud storage needed.

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