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Assessing the Network Security Threats Posed by Unregulated Free Live Streaming Services

2025· article· W7127381483 on OpenAlexaff
Nithiya Shri Muruganandham, Sina Keshvadi

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicSpam and Phishing Detection
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsNews aggregatorPhishingEvent (particle physics)Consumer privacySecurity analysisBlacklistData breach

Abstract

fetched live from OpenAlex

Free live sports streaming sites (FLSs), which operate in legal gray areas and attract millions of viewers monthly, present a complex landscape of security and privacy risks. During UEFA Euro 2024, we conducted a one-month study of popular aggregator sites to quantify the security and privacy threats users face. Our analysis of over 370 unique FLSs uncovered numerous instances of malicious JavaScript, adware, blacklisted sites, and drive-by downloads, along with the use of cookies to track users and redirect them to malicious websites. Additionally, we identified several phishing websites active during the event that had not yet been flagged by Google’s Safe Browsing Lists. With over 17.5% of these aggregators attracting more than 10 million monthly views, our findings highlights the urgent need for increased user awareness and protective measures within this rapidly evolving online ecosystem.

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 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), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0040.002
Open science0.0030.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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