Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31796
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dc.contributor.authorOJENIYI, Joseph Adebayo-
dc.contributor.authorFASOLA, Olusanjo Olugbemi-
dc.contributor.authorONYEABOR, Grace Amina-
dc.contributor.authorJOSHUA, D. H.-
dc.contributor.authorOLUGHU, U. S.-
dc.contributor.authorGANA, G. N.-
dc.contributor.authorADEIZA, I. R.-
dc.date.accessioned2026-07-08T20:00:30Z-
dc.date.available2026-07-08T20:00:30Z-
dc.date.issued2026-03-
dc.identifier.urihttp://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31796-
dc.description.abstractThe Learning Parity with Noise (LPN) problem is a foundational assumption for constructingbsimple and efficient post-quantum cryptographic primitives. While LPN-based Public-Key Encryption (PKE) schemes exist, achieving high-level security like Indistinguishability under Adaptive ChosenCiphertext Attack (IND-CCA2) simultaneously with a low Decryption Failure Rate (DFR) has been a persistent challenge. This paper presents a construction of an LPN-based PKE scheme that is proven IND-CCA2 secure in the standard model under the Decisional LPN (D-LPN) assumption. Critically, we introduce a modified decryption mechanism that significantly reduces the DFR, achieving a squaredexponential rate 2^(-Θ(k^2)), where k is the security parameter. This rate is a vast improvement over the linear-exponential rate, 2-Ɵ(k), of previous schemes in the low-noise regime, as identified by Xu et al. (2021). The resulting PKE scheme is highly practical and competitive for resource-constrained environments.en_US
dc.language.isoenen_US
dc.publisherSocial Informatics, Business, Politics, Law, Environmental Sciences & Technology Journal.en_US
dc.relation.ispartofseriesVol 12, No 1, March, 2026 Series;-
dc.subject, Squared-Exponential Decryption, Failure Rate, Low-Noise LPN-Based Public-Key Encryptionen_US
dc.titleAchieving IND-CCA2 Security and Squared-Exponential Decryption Failure Rate for Low-Noise LPN-Based Public-Key Encryptionen_US
dc.typeArticleen_US
Appears in Collections:Cyber Security Science

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