MétaCan
Menu
Back to cohort
Record W1549104937

Technique for preventing DoS attacks on RFID systems

2010· article· en· W1549104937 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 Conference on Software, Telecommunications and Computer Networks · 2010
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDenial-of-service attackComputer scienceEavesdroppingComputer securityProtocol (science)Synchronization (alternating current)Intrusion detection systemComputer networkOperating systemThe Internet
DOInot available

Abstract

fetched live from OpenAlex

RFID systems are vulnerable to many types of malicious attacks, ranging from passive eavesdropping to complete denial of service (DoS). Hence it is becoming increasingly important to develop and design intrusion detection and prevention mechanisms for RFID. One of the ultra lightweight techniques to prevent DoS on RFID systems is the Gossamer protocol. In this paper, we show that although the Gossamer protocol is effective, it is vulnerable to one particular type of DoS, namely, DoS by de-synchronization. We further present a novel technique that extends the Gossamer protocol to prevent DoS attacks in general, and the de-synchronization DoS attack in particular. We validate our approach by a proof-of-concept simulation using a java framework.

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 score0.887
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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