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Record W7019748365

An Information Security System for Image Encryption Applications: Architecture and Performance Evaluation

2023· dissertation· en· W7019748365 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicChaos-based Image/Signal Encryption
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaRoyal University Hospital Foundation
KeywordsEncryptionCloud computingCryptographyClass (philosophy)Cloud computing securityAccess controlHealth careSoftwareData security
DOInot available

Abstract

fetched live from OpenAlex

Among many socio-industrial sectors of a technologically driven society, including but not limited to the military, education, and business, healthcare has been the most targeted institution. There are many underlying reasons, namely, legacy software and technologies used by healthcare providers, lack of systematic data governance, non-robust infrastructure, insufficient training for employees, individual sets of regulations and governance for each province in Canada, and insufficient control over data access by staff. Surprisingly, the personal information of patients (address, SIN number, phone number, etc.) and patients’ records are sometimes even not encrypted on the cloud. Most of the attacks happen on the cloud which can lead to catastrophic consequences (data usually is stored on public clouds without implementing any guards like zero trust). There are many algorithms developed after 1974 to provide security (confidentiality, authentication, integration, access control, etc.). However, these algorithms are not efficient solutions for healthcare data including images. There is an urgent need for a class of efficient and optimized algorithms that can be used by all healthcare centers as a standard to provide fast and secure encryption. In this thesis, a novel information security system is proposed to incorporate an innovative and emerging class of cryptographic algorithms. Unlike existing algorithms in the literature, these new algorithms exhibit unique properties, which make them particularly suitable for delivering a practical and efficient architecture for securing telemedicine. Accordingly, a comprehensive and strategic panoply of tests is developed and examined in this research to investigate the practical real-world performance of this class of algorithms, and to prove their engineering suitability as the heart of the proposed information security system. The results show that this class of algorithms is superior to publicly known cryptographic methods, notably being resistant against currently known classical and quantum attack schemes. Altogether, from an information security perspective, these findings reinforce the merits of the proposed system as a compelling competitor against state-of-the-art solutions for engineering an efficient and secure telemedicine architecture. Moreover, this research presents the design and implementation of a graphical user interface (GUI) tailored for the execution and assessment of emerging classes of cryptographic algorithms. Recognizing the growing need for accessible and user-friendly cryptographic tools, this work addresses the gap between complex algorithmic implementations and end-users.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.009
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.188
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it