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Record W2125619860 · doi:10.1109/pacrim.2003.1235745

Network processors for communication security: a review

2004· review· en· W2125619860 on OpenAlexaff
Esam Khan, M. Watheq El‐Kharashi, Ammar Rafiq, Fayez Gebali, Mostafa Abd‐El‐Barr

Bibliographic record

Venuenot available
Typereview
Languageen
FieldComputer Science
TopicNetwork Packet Processing and Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceFlexibility (engineering)Wireless networkWirelessEmbedded systemBandwidth (computing)Computer networkComputer security modelNetwork securityDesign flowDistributed computingComputer architectureComputer securityTelecommunications

Abstract

fetched live from OpenAlex

Network processor units (NPUs) are application specific instruction processors (ASIPs) specialized and optimized to perform different network functionalities. As security is one of the essential network issues, it is better to be implemented using NPUs because of the need for fast processing to achieve high data rates. In this paper, we provide an overview on the use of NPUs for security. There exist three approaches to implement security using NPUs: the look-aside, the flow-through, and the integrated security blocks. Moreover, when we deal with wireless systems, wireless security processor implementation to meet the general design constraints of wireless devices. These constraints include limited bandwidth, low power consumption, and minimized area. In addition, designers of wireless security processors take into account the need for fast processing and flexibility.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.010

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 head0.344
Teacher spread0.296 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2004
Admission routes1
Has abstractyes

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