Securing Ai Systems: a Comprehensive Overview of Cryptographic Techniques for Enhanced Confidentiality and Integrity

dc.authorid MOLLAKUQE, Elissa/0000-0003-0508-105X
dc.authorscopusid 59232916800
dc.authorscopusid 59232916900
dc.authorscopusid 59233422300
dc.authorscopusid 59233764600
dc.authorscopusid 6507328166
dc.authorscopusid 37010805100
dc.authorscopusid 37010805100
dc.authorwosid MOLLAKUQE, ELISSA/HKO-9388-2023
dc.contributor.author Garcia, Jose Luis Cano
dc.contributor.author Dağ, Hasan
dc.contributor.author Udechukwu, Izuchukwu Patrick
dc.contributor.author Ibrahim, Isiaq Bolaji
dc.contributor.author Chukwu, Ikechukwu John
dc.contributor.author Dag, Hasan
dc.contributor.author Dimitrova, Vesna
dc.contributor.author Mollakuqe, Elissa
dc.contributor.other Management Information Systems
dc.date.accessioned 2024-10-15T19:38:59Z
dc.date.available 2024-10-15T19:38:59Z
dc.date.issued 2024
dc.department Kadir Has University en_US
dc.department-temp [Garcia, Jose Luis Cano; Udechukwu, Izuchukwu Patrick; Ibrahim, Isiaq Bolaji; Chukwu, Ikechukwu John; Dag, Hasan; Mollakuqe, Elissa] Kadir Has Univ, Istanbul, Turkiye; [Dimitrova, Vesna] Cyril & Methodius Univ, Skopje, North Macedonia en_US
dc.description MOLLAKUQE, Elissa/0000-0003-0508-105X en_US
dc.description.abstract The rapid evolution of artificial intelligence (AI) has introduced transformative changes across industries, accompanied by escalating security concerns. This paper contributes to the imperative need for robust security measures in AI systems based on the application of cryptographic techniques. This research analyzes AI-ML systems vulnerabilities and associated risks and identifies existing cryptographic methods that could constitute security measures to mitigate such risks. Information assets subject to cyberattacks are identified, such as training data and model parameters, followed by a description of existing encryption algorithms and a suggested approach to use a suitable technique, such as homomorphic encryption CKKS, along with digital signatures based on ECDSA to protect the digital assets through all the AI system life cycle. These methods aim to safeguard sensitive data, algorithms, and AI-generated content from unauthorized access and tampering. The outcome offers potential and practical solutions against privacy breaches, adversarial attacks, and misuse of AI-generated content. Ultimately, this work aspires to bolster public trust in AI technologies, fostering innovation in a secure and reliable AI-driven landscape. en_US
dc.description.woscitationindex Conference Proceedings Citation Index - Science
dc.identifier.citationcount 0
dc.identifier.doi 10.1109/MECO62516.2024.10577883
dc.identifier.endpage 257 en_US
dc.identifier.isbn 9798350387568
dc.identifier.isbn 9798350387575
dc.identifier.issn 2377-5475
dc.identifier.scopus 2-s2.0-85199511185
dc.identifier.startpage 250 en_US
dc.identifier.uri https://doi.org/10.1109/MECO62516.2024.10577883
dc.identifier.uri https://hdl.handle.net/20.500.12469/6301
dc.identifier.wos WOS:001268606200069
dc.language.iso en en_US
dc.publisher Ieee en_US
dc.relation.ispartof 13th Mediterranean Conference on Embedded Computing (MECO) -- JUN 11-14, 2024 -- Budva, MONTENEGRO en_US
dc.relation.ispartofseries Mediterranean Conference on Embedded Computing
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 0
dc.subject Artificial Intelligence en_US
dc.subject Cryptography en_US
dc.subject Security en_US
dc.subject Neural Networks en_US
dc.title Securing Ai Systems: a Comprehensive Overview of Cryptographic Techniques for Enhanced Confidentiality and Integrity en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication
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