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Record W7162442222 · doi:10.65521/ijasret.v8i9.2326

DESIGN AND DEVELOPMENT OF A REGIMEN (SYSTEM) TO DETECT AND MITIGATE CROSS SITE SCRIPTING

2024· article· W7162442222 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

VenueInternational Journal of Advance Scientific Research and Engineering Trends · 2024
Typearticle
Language
FieldComputer Science
TopicWeb Application Security Vulnerabilities
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsCross-site scriptingScripting languageClient-side scriptingJavaScriptWeb applicationWeb application securityDynamic web pageWeb developmentHacker

Abstract

fetched live from OpenAlex

Securing the web application against hacking is a big challenge. One of the common types of hacking techniques to attack the web application is cross-site scripting (XSS). Cross-site scripting vulnerabilities are being exploited by the attackers to steal web browser’s resources, such as cookies, credentials, etc., by injecting the malicious JavaScript code on the victim's web applications. Since Web browsers support the execution of commands embedded in Web pages to enable dynamic Web pages, attackers can make use of this feature to enforce the execution of malicious code in a user's Web browser. The analysis of detection and prevention of cross-site scripting (XSS) helps to avoid this type of attack. We describe a technique to detect and prevent this kind of manipulation and hence eliminate cross-site scripting attacks.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0010.001
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 head0.047
GPT teacher head0.356
Teacher spread0.309 · 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