MétaCan
Menu
Back to cohort
Record W2063939659 · doi:10.1109/comst.2015.2392629

A Survey of Security Attacks in Information-Centric Networking

2015· article· en· W2063939659 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Communications Surveys & Tutorials · 2015
Typearticle
Languageen
FieldComputer Science
TopicCaching and Content Delivery
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaBell Canada Enterprises
KeywordsComputer scienceConfidentialityComputer securityInformation-centric networkingInternet privacyRelation (database)Computer networkWorld Wide WebThe InternetDatabase

Abstract

fetched live from OpenAlex

Information-centric networking (ICN) is a new communication paradigm that focuses on content retrieval from a network regardless of the storage location or physical representation of this content. In ICN, securing the content itself is much more important than securing the infrastructure or the endpoints. To achieve the security goals in this new paradigm, it is crucial to have a comprehensive understanding of ICN attacks, their classification, and proposed solutions. In this paper, we provide a survey of attacks unique to ICN architectures and other generic attacks that have an impact on ICN. It also provides a taxonomy of these attacks in ICN, which are classified into four main categories, i.e., naming, routing, caching, and other miscellaneous related attacks. Furthermore, this paper shows the relation between ICN attacks and unique ICN attributes, and that between ICN attacks and security requirements, i.e., confidentiality, integrity, availability, and privacy. Finally, this paper presents the severity levels of ICN attacks and discusses the existing ICN security solutions.

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)0.013
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.337
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
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 head0.116
GPT teacher head0.316
Teacher spread0.200 · 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