Efficient Black-box JTAG Discovery

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dc.contributor.advisor Focardi, Riccardo it_IT
dc.contributor.author Francescato, Riccardo <1993> it_IT
dc.date.accessioned 2018-02-18 it_IT
dc.date.accessioned 2018-06-22T08:42:23Z
dc.date.available 2018-06-22T08:42:23Z
dc.date.issued 2018-03-21 it_IT
dc.identifier.uri http://hdl.handle.net/10579/12266
dc.description.abstract Embedded devices represents the most widespread form of computing device in the world. Almost every consumer product manufactured in the last decades contains an embedded system, e.g., refrigerators, smart bulbs, activity trackers, smart watches and washing machines. This computing devices are also used in safety and security-critical systems, e.g., autonomous driving cars, cryptographic tokens, avionics, alarm systems. Often, manufacturers do not take much into consideration the attack surface offered by low level interfaces such as JTAG. In the last decade, JTAG port has been used by the research community to show a number of attacks and reverse engineering techniques. Therefore, finding and identifying the JTAG port of a device or a de-soldered integrated circuit (IC) can be the first step required for performing a successful attack. In this work we analyse the design of JTAG port and develop methods and algorithms aimed at searching the JTAG port. Specifically we will cover the following arguments: i) an introduction to the problem and related attacks; ii) a general description of the JTAG port and his functions; iii) the analysis of the problem and the naive solution; iv) an efficient algorithm based on 4-state GPIO; v) a randomized algorithm using the 4-states GPIO; vi) an overview on the problem and search methods used in PCBs; vii) the conclusions and the suggestions for a proficient use. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Riccardo Francescato, 2018 it_IT
dc.title Efficient Black-box JTAG Discovery it_IT
dc.title.alternative Efficient Black-box JTAG Discovery it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Informatica - computer science it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Scienze Ambientali, Informatica e Statistica it_IT
dc.description.academicyear 2016/2017, sessione straordinaria it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 857609 it_IT
dc.subject.miur INF/01 INFORMATICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend it_IT
dc.provenance.upload Riccardo Francescato (857609@stud.unive.it), 2018-02-18 it_IT
dc.provenance.plagiarycheck Riccardo Focardi (focardi@unive.it), 2018-03-05 it_IT


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