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Record W4415360264 · doi:10.59934/jaiea.v5i1.1578

Implementation of Base 64 and AES Algorithms in Web-Based Email Message Security System

2025· article· W4415360264 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Artificial Intelligence and Engineering Applications (JAIEA) · 2025
Typearticle
Language
FieldEngineering
TopicEmbedded Systems and FPGA Design
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsEncryptionMessage brokerMessage authentication codeEncoding (memory)Decoding methodsPublic-key cryptographyMessage passingDigital signature

Abstract

fetched live from OpenAlex

This research is motivated by the increasing threat to message security in email communications due to the rapid development of information technology. To address this, this study aims to implement and test a web-based email message security system that combines Base64 and AES 256-bit algorithms to protect text messages and attachments from security threats. This system was developed using the PHP programming language and functions as an internal messaging system. The results show that the combination of the two algorithms successfully creates a system capable of securing messages strongly. During the delivery process, the system performs AES 256 encryption and Base64 encoding on messages and attachments. Meanwhile, when a message is received, the user must first enter the same key, after which the system will perform Base64 decoding and continue with AES 256 decryption to restore the message to its original form. Thus, the resulting system is proven effective in securing digital communications and ensuring that messages can only be accessed by authorized recipients.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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