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Record W1939358669

SOCaaS: Security Operations Center as a Service for Cloud Computing Environments

2014· article· en· W1939358669 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

VenueIEEE International Conference on Cloud Computing Technology and Science · 2014
Typearticle
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer securityCloud computing securityCloud computingComputer scienceSecurity serviceSecurity information and event managementOutsourcingService providerService (business)Computer security modelInformation securityProcess managementBusiness
DOInot available

Abstract

fetched live from OpenAlex

The management of information security operations is a complex task, especially in a cloud environment.  The cloud service layers and multi-tenancy architecture creates a complex environment in which to develop and manage an information security incident management and compliance program. This paper presents a novel security operations center (SOC) framework as a service for cloud service providers and customers. The goal is to protect cloud services against new and existing attacks as well as comply with security policies and regulatory requirements. The SOCaaS design is based on multi-governance and defense in depth models and fits within the multi-tenancy cloud services. A SOCaaS provider is a trusted entity that collects event and system logs from cloud systems to ensure proactive incident management and compliance with regulations. The proposed approach provides better managed services for customers wanting to outsource their information security operations to attain reliable, transparent, and efficient security and privacy.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
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 head0.027
GPT teacher head0.284
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