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Record W4309676759 · doi:10.1109/cns56114.2022.9947230

Survey of Remote TLS Vulnerability Scanning Tools and Snapshot of TLS Use in Banking Sector

2022· article· en· W4309676759 on OpenAlexaff
Jay Chung, Natalija Vlajic

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsYork University
Fundersnot available
KeywordsSnapshot (computer storage)PopularityComputer securityComputer scienceVulnerability (computing)Protocol (science)Transport Layer SecurityDatabaseMedicineEncryptionPolitical science

Abstract

fetched live from OpenAlex

With the increasing popularity and real-world use of TLS, the number of vulnerabilities identified in this protocol has also grown. As a result, the protocol has undergone several revisions, with TLS 1.3 being its latest and currently most secure version. In this paper we provide a brief review of some of the most critical vulnerabilities of the earlier versions of TLS (TLS 1.2 and 1.1), and we survey the performance of several popular TLS scanning tools. The paper also provides a summary of our findings obtained by performing remote TLS scanning of the world's 50 largest banks. Contrary to what one would expect, the state of TLS security in the surveyed banks appears to be at (or below) the state of TLS security across the whole WWW. For example, at present less than 50% of the surveyed banks deploy TLS 1.3, while a significant number of them appear vulnerable to some well-known TLS-based 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.007
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.082
GPT teacher head0.274
Teacher spread0.192 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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