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Intrusion Detection Systems

2005· book-chapter· en· W3144134378 on OpenAlexaff
H. Güneş Kayacık, A. Nur Zincir‐Heywood, Malcolm I. Heywood

Bibliographic record

VenueIGI Global eBooks · 2005
Typebook-chapter
Languageen
FieldComputer Science
TopicNetwork Security and Intrusion Detection
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer securityComputer scienceCompromiseDenial-of-service attackConfidentialityIntrusion detection systemScope (computer science)Network securitySecurity information and event managementInformation securityThe InternetCloud computing securityWorld Wide WebCloud computing

Abstract

fetched live from OpenAlex

Along with its numerous benefits, the Internet also created numerous ways to compromise the security and stability of the systems connected to it. In 2003, 137529 incidents were reported to CERT/CC© while in 1999, there were 9859 reported incidents (CERT/CC©, 2003). Operations, which are primarily designed to protect the availability, confidentiality, and integrity of critical network information systems, are considered to be within the scope of security management. Security management operations protect computer networks against denial-of-service attacks, unauthorized disclosure of information, and the modification or destruction of data. Moreover, the automated detection and immediate reporting of these events are required in order to provide the basis for a timely response to attacks (Bass, 2000). Security management plays an important, albeit often neglected, role in network management tasks.

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)0.005
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: Other · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0300.038

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 head0.013
GPT teacher head0.218
Teacher spread0.206 · 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
GenreOther

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

Citations63
Published2005
Admission routes1
Has abstractyes

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