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Record W2897475637 · doi:10.1109/bsc.2018.8494695

Single Packet Authorization in a Multi-Layered Security Architecture

2018· article· en· W2897475637 on OpenAlexaff
Mohammad Mirheydari, Pavol Zavarsky, Sergey Butakov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Security and Intrusion Detection
Canadian institutionsConcordia University of Edmonton
Fundersnot available
KeywordsFirewall (physics)Computer scienceAuthorizationComputer networkNetwork packetComputer securityArchitectureNetwork securityAccess controlEnterprise information security architectureServerFocus (optics)Distributed System Security ArchitectureNetwork Access ControlOperating systemCloud computing security

Abstract

fetched live from OpenAlex

Single Packet Authorization (SPA) is a concealment method that hides the open ports, devices, and network components behind a firewall. SPA suffers from a known weakness i.e., the SPA client, and if the SPA client gets compromised by an attacker, the attacker can find his way to the SPA server. This paper explores the possible attacks from the SPA client with the focus on the implementation of SPA in multilevel security architecture such as Industrial Control Systems (ICS). It identifies the limitations of SPA on cascading the authorization packet in multiple security levels and proposes to combine SPA with access control. It is shown in the paper that the security of the whole SPA architecture can be improved by adding some features to the SPA server.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
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 head0.026
GPT teacher head0.259
Teacher spread0.233 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

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