|Author||Griggs, Christopher ♦ Sturton, Cynthia ♦ Chi, Andrew ♦ Stanley, Natalie ♦ Zhang, Rui|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Hardware security ♦ Supervised learning ♦ Processor errata ♦ Security properties|
|Abstract||We present a methodology for identifying security critical properties for use in the dynamic verification of a processor. Such verification has been shown to be an effective way to prevent exploits of vulnerabilities in the processor, given a meaningful set of security properties. We use known processor errata to establish an initial set of security-critical invariants of the processor. We then use machine learning to infer an additional set of invariants that are not tied to any particular, known vulnerability, yet are critical to security. We build a tool chain implementing the approach and evaluate it for the open-source OR1200 RISC processor. We find that our tool can identify 19 (86.4%) of the 22 manually crafted security-critical properties from prior work and generates 3 new security properties not covered in prior work.|
|Description||Affiliation: The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA (Zhang, Rui; Stanley, Natalie; Griggs, Christopher; Chi, Andrew; Sturton, Cynthia)|
|Age Range||18 to 22 years ♦ above 22 year|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||ACM SIGOPS Operating Systems Review (OPSR)|
Ministry of Human Resource Development (MHRD) under its National Mission on Education through Information and Communication Technology (NMEICT) has initiated the National Digital Library of India (NDLI) project to develop a framework of virtual repository of learning resources with a single-window search facility. Filtered and federated searching is employed to facilitate focused searching so that learners can find out the right resource with least effort and in minimum time. NDLI is designed to hold content of any language and provides interface support for leading vernacular languages, (currently Hindi, Bengali and several other languages are available). It is designed to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is being developed to help students to prepare for entrance and competitive examinations, to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is being developed at Indian Institute of Technology Kharagpur.
NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.
Ministry of Human Resource Development (MHRD), through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
For any issue or feedback, please write to email@example.com