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Record W4252556839 · doi:10.6028/nist.ir.7399

Computer Security Division 2006 annual report

2007· report· en· W4252556839 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsnot available
FundersInformation Technology LaboratoryDefense Advanced Research Projects AgencyNational Institute of Standards and TechnologyU.S. Department of DefenseAustralian GovernmentNational Security AgencyJess and Mildred Fisher College of Science and MathematicsU.S. Department of Homeland SecurityAdvanced Research Projects AgencyGovernment of Canada
KeywordsDivision (mathematics)Computer scienceComputer securityArithmeticMathematics

Abstract

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I n 2006, the Computer Security Division (CSD) of NIST's Information Technology Laboratory engaged in a number of initiatives for improving information system security in the Federal government.Both automated tool development and increased outreach activities were initiated to communicate information technology risks, vulnerabilities, and protection requirements-particularly for new and emerging technologies.The CSD continued to research and publicize IT vulnerabilities.Emphasis was placed on development of techniques for affordable security and privacy mechanisms for Federal information systems.We continued to develop standards, metrics, tests, and validation programs to promote, measure, and validate security in systems and services.We also developed guidance to increase secure IT planning, implementation, management, and operation.Affected customer organizations include federal, state, and local governments, the healthcare community, colleges and universities, small businesses, the private sector, and the international community.This year also brought additional security challenges along with the everadvancing improvements in technology, improvements in citizens' access to government systems and information, faster communications, reduced paperwork, and streamlined processes.Our work this year met those security challenges with a breadth and depth of security areas intended to allow our customers to accomplish their missions while providing for confidentiality of their information, maintaining the availability of their resources and ensuring the integrity of their data.High priority was given to initiating a competitive program for replacement of current secure hashing algorithms employed in data source and content integrity protection mechanisms.One highlight of our work in 2006 was expanding and refining the Federal Information Processing Standards (FIPS) 201 standard suites and supporting implementation of Homeland Security Presidential Directive 12's mandate for common procedures and mechanisms for identity verification of Federal employees and contractors.We also continued our progress in fulfilling the mandates of the Federal Information Security Management Act of 2002 (FISMA), which resulted in revision of NIST Special Publication (SP) 800 53, Recommended Security Controls for Federal Information Systems; coordination of the draft SP 800-53A, Guide for Assessing the Security Controls in Federal Information Systems; and publication of FIPS 200, Minimum Security Requirements for Federal Information and Information Systems.The Cryptographic Module Validation Program was expanded to include 13 laboratories in 4 countries and continues to ensure the protection of sensitive information in computer and telecommunication systems, including voice systems.Research and development efforts included security for Radio Frequency IDentification (RFID) devices and other wireless communications systems, digital forensic tools and methods, Internet security protocols, and expansion of the National Vulnerability Database.We will continue to strive to provide products and services that protect and enhance confidence in the nation's information technology systems.

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)0.003
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.228
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2280.262

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 head0.017
GPT teacher head0.289
Teacher spread0.272 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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