Understanding Security Threats in Emerging Neuromorphic Computing Architecture
Neuromorphic computing marks the beginning of a new era in computing system design, owing to the introduction of complex and unorthodox non-Von Neumann architectures, in conjunction with new post-CMOS nano-ionic devices. These neuromorphic chips are projected to soon become a mainstay platform for a...
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Veröffentlicht in: | Journal of hardware and systems security 2021-03, Vol.5 (1), p.45-57 |
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creator | Rajamanikkam, Chidhambaranathan JS, Rajesh Roy, Sanghamitra Chakraborty, Koushik |
description | Neuromorphic computing marks the beginning of a new era in computing system design, owing to the introduction of complex and unorthodox non-Von Neumann architectures, in conjunction with new post-CMOS nano-ionic devices. These neuromorphic chips are projected to soon become a mainstay platform for a diverse set of applications, ranging from day-to-day rudimentary decision making, to safety critical defense and healthcare management. In this environment, hardware security can no longer take an auxiliary role in system design. In this work, we lay a solid foundation of understanding the broad security implications of emerging memristor-based neuromorphic computing paradigm. We investigate various security loopholes arising from an untrustworthy neuromorphic design environment. We propose, examine and evaluate the security threats arising from—
(a)
covert hardware Trojans and
(b)
external attacks exploiting implementation-specific vulnerabilities. Subsequently, we discuss three specific attacks targeting crucial components of the neuromorphic design and demonstrate how the security breaches in the neuromorphic systems can directly impact the end-user experience. Uncovering these security vulnerabilities in the emerging neuromorphic computing paradigm can be instrumental in shaping our design practices. |
doi_str_mv | 10.1007/s41635-021-00110-8 |
format | Article |
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(a)
covert hardware Trojans and
(b)
external attacks exploiting implementation-specific vulnerabilities. Subsequently, we discuss three specific attacks targeting crucial components of the neuromorphic design and demonstrate how the security breaches in the neuromorphic systems can directly impact the end-user experience. Uncovering these security vulnerabilities in the emerging neuromorphic computing paradigm can be instrumental in shaping our design practices.</description><identifier>ISSN: 2509-3428</identifier><identifier>EISSN: 2509-3436</identifier><identifier>DOI: 10.1007/s41635-021-00110-8</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Artificial intelligence ; Brain research ; Circuits and Systems ; Computer Hardware ; Confidentiality ; Cybersecurity ; Design ; Engineering ; Hardware ; Information Systems Applications (incl.Internet) ; Neuromorphic computing ; Safety critical ; Software ; Systems and Data Security ; Systems design ; Threat evaluation ; Threats ; User experience</subject><ispartof>Journal of hardware and systems security, 2021-03, Vol.5 (1), p.45-57</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1158-ae2dc537bd549a4ec7e5557672f8118bca0a8cd688877ec7e7071eaff4dcd53c3</cites><orcidid>0000-0003-3956-8106</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s41635-021-00110-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2932844423?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21369,27903,27904,33723,41467,42536,43784,51297</link.rule.ids></links><search><creatorcontrib>Rajamanikkam, Chidhambaranathan</creatorcontrib><creatorcontrib>JS, Rajesh</creatorcontrib><creatorcontrib>Roy, Sanghamitra</creatorcontrib><creatorcontrib>Chakraborty, Koushik</creatorcontrib><title>Understanding Security Threats in Emerging Neuromorphic Computing Architecture</title><title>Journal of hardware and systems security</title><addtitle>J Hardw Syst Secur</addtitle><description>Neuromorphic computing marks the beginning of a new era in computing system design, owing to the introduction of complex and unorthodox non-Von Neumann architectures, in conjunction with new post-CMOS nano-ionic devices. These neuromorphic chips are projected to soon become a mainstay platform for a diverse set of applications, ranging from day-to-day rudimentary decision making, to safety critical defense and healthcare management. In this environment, hardware security can no longer take an auxiliary role in system design. In this work, we lay a solid foundation of understanding the broad security implications of emerging memristor-based neuromorphic computing paradigm. We investigate various security loopholes arising from an untrustworthy neuromorphic design environment. We propose, examine and evaluate the security threats arising from—
(a)
covert hardware Trojans and
(b)
external attacks exploiting implementation-specific vulnerabilities. Subsequently, we discuss three specific attacks targeting crucial components of the neuromorphic design and demonstrate how the security breaches in the neuromorphic systems can directly impact the end-user experience. Uncovering these security vulnerabilities in the emerging neuromorphic computing paradigm can be instrumental in shaping our design practices.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Brain research</subject><subject>Circuits and Systems</subject><subject>Computer Hardware</subject><subject>Confidentiality</subject><subject>Cybersecurity</subject><subject>Design</subject><subject>Engineering</subject><subject>Hardware</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Neuromorphic computing</subject><subject>Safety critical</subject><subject>Software</subject><subject>Systems and Data Security</subject><subject>Systems design</subject><subject>Threat evaluation</subject><subject>Threats</subject><subject>User experience</subject><issn>2509-3428</issn><issn>2509-3436</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kEtLw0AQxxdRsNR-AU8Bz9F9ZjfHUuoDSj3YnpftZtKumIezyaHf3sSI3jzNMP_HwI-QW0bvGaX6IUqWCZVSzlJKGaOpuSAzrmieCimyy9-dm2uyiDEcqGA8EzoXM7Ld1wVg7FxdhPqYvIHvMXTnZHdCcF1MQp2sK8DjKG6hx6ZqsD0Fn6yaqu278bxEfwod-K5HuCFXpfuIsPiZc7J_XO9Wz-nm9elltdyknjFlUge88EroQ6Fk7iR4DUopnWleGsbMwTvqjC8yY4zWo6qpZuDKUha-UMKLObmbeltsPnuInX1veqyHl5bnghspJReDi08uj02MCKVtMVQOz5ZRO6KzEzo7oLPf6KwZQmIKxcFcHwH_qv9JfQFVg3Iy</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>Rajamanikkam, Chidhambaranathan</creator><creator>JS, Rajesh</creator><creator>Roy, Sanghamitra</creator><creator>Chakraborty, Koushik</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0003-3956-8106</orcidid></search><sort><creationdate>20210301</creationdate><title>Understanding Security Threats in Emerging Neuromorphic Computing Architecture</title><author>Rajamanikkam, Chidhambaranathan ; 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(a)
covert hardware Trojans and
(b)
external attacks exploiting implementation-specific vulnerabilities. Subsequently, we discuss three specific attacks targeting crucial components of the neuromorphic design and demonstrate how the security breaches in the neuromorphic systems can directly impact the end-user experience. Uncovering these security vulnerabilities in the emerging neuromorphic computing paradigm can be instrumental in shaping our design practices.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s41635-021-00110-8</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-3956-8106</orcidid></addata></record> |
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subjects | Algorithms Artificial intelligence Brain research Circuits and Systems Computer Hardware Confidentiality Cybersecurity Design Engineering Hardware Information Systems Applications (incl.Internet) Neuromorphic computing Safety critical Software Systems and Data Security Systems design Threat evaluation Threats User experience |
title | Understanding Security Threats in Emerging Neuromorphic Computing Architecture |
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