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Record W3124118120

Pengamanan Data Teks Menggunakan Algoritma Modular Multiplication Based Block Chiper

2021· article· en· W3124118120 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHumanitiesPolitical scienceComputer scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Pemanfaatan Teknologi Informasi dan Komunikasi (TIK) saat ini menjadi kebutuhan pokok bagi hampir seluruh penduduk bumi ini, dalam mencari informasi dan berkomunikasi kita akan memanfaatkan TIK. Salah satu pemanfaatan TIK melalui jaringan internet adalah cara pengiriman pesan teks melalui email, sosial media, atau alat komunikasi lainnya. Pesan yang disampaikan dari pengirim ke penerima ada kalanya berupa pesan yang bersifat rahasia sehingga tidak semua pihak dapat melihat pesan tersebut. Namun, seiring dengan berkembangnya hal tersebut berkembang pula  pelanggaran atau penyalah gunaan dalam keamanan data yang dikirim seperti dengan cara merusak, menyadap, merubah pesan tersebut untuk tujuan kepentingan si pelaku. Tindakan tersebut dapat membuat informasi atau pesan yang bersifat rahasia dapat dilihat oleh orang yang tidak bertanggung jawab. Dalam menangani masalah keaman data ini, perlu dilakukan penggunaan teknik peningkatan keamanan. Salah satu teknik yang dapat digunakan untuk mengamankan data adalah dengan menggunakan algoritma Modular Multiplication based Block Chiper (MMB), yang merupakan metode yang sederhana tidak terlalu kompleks namun pesan yang disembunyikan cukup aman.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.035
GPT teacher head0.284
Teacher spread0.250 · 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