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Record W2083421973 · doi:10.1373/clinchem.2010.151837

News & Views: Cyberintrusion—Happening Much Closer to You Than You Might Think!

2010· article· en· W2083421973 on OpenAlexaboutno aff
Hoi-Ying Elsie Yu

Bibliographic record

VenueClinical Chemistry · 2010
Typearticle
Languageen
FieldComputer Science
TopicCybercrime and Law Enforcement Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHackerFellComplaintLaw enforcementQuarter (Canadian coin)CybercrimeThe InternetHappeningLawInternet privacyHistoryPsychologyComputer securityPolitical scienceComputer scienceWorld Wide WebArt historyGeography

Abstract

fetched live from OpenAlex

According to the Internet Crime Complaint Center (IC3)2 (www.ic3.gov), cybercrimes are rising rapidly. In 2009, 336 655 cybercrime complaints were submitted to IC3, a 22.3% increase compared with 2008. Of these complaints, 146 663 were referred to law-enforcement agencies for further investigation. These referred cases represented a combined financial loss of $559.7 million. Although many may think these crimes were the results of careless individuals who fell for those “you just inherited a million dollars” scams, the reality is that if you have Internet connection, hackers have probably already attempted to attack the information stored in your computer. According to a report by Perkel (1), an average of 27 000 hacking attempts were made per day during the first quarter of 2010 at the San Diego Supercomputer Center of the University of California. The report also provides some practical tips to enhance cybersecurity. Despite the alarming number of incidents, hacking attempts can usually be blocked successfully by well-coded firewalls. Most computer hackers look for open access or a poorly coded firewall to steal or sabotage data and intellectual property. Therefore, information technology (IT) professionals should be hired to write protective firewalls. Sensitive data should be managed by a centralized IT team that can monitor traffic and limit access. E-mail should be encrypted when sending sensitive data. Computers should be password-protected and encrypted. These measures may seem quite straightforward, but many academic researchers do not endorse them because of limited funding to hire IT professionals and the inconvenience that comes with heightened security. For example, cybersecurity means that personal computers should not be allowed to handle sensitive data unless firewalls have been installed and the computers have been encrypted. In addition, the exchange of information between colleagues via cyberspace can no longer occur without professional encryption. Furthermore, researchers will not be able to install software as needed but will require authorization by an “administrator.” Many researchers therefore prefer the convenience and freedom of no IT professional oversight over the security of their data; however, the truth is that it only takes one successful intrusion to wipe out years, if not decades, of hard work. Is the convenience really worth it? The only way to protect intellectual property from hackers is to be proactive in implementing security measures and stopping the bad habits that may promote successful cyberintrusion. So, let's follow the advice from the IT professionals and secure our data. Internet Crime Complaint Center information technology. DO enable automatic operating-system updates. DO install and update your antivirus and anti-malware software, most of which is available for little or no cost from universities. DON'T run your computer with administrator privileges, but as a non-privileged user. Then, if somebody does hack into your computer, they cannot install anything. DO consider purging sensitive data from connected computers and confining them to offline machines. DO encrypt your hard drive, for instance with FileVault (Mac), TrueCrypt (Windows/Mac/Linux) or PGP Whole Disk Encryption (Windows/Mac/Linux). DON'T send sensitive data by standard e-mail. If you're not using encrypted e-mail, encrypt the material itself, for instance in a password-protected PDF. DO ensure all your applications are patched to the current level, for instance with Secunia's free Personal Software Inspector (Windows). DO password-protect your computer and smartphone. DON'T let your web browser remember your passwords; instead, use password vaults, such as KeePass and LastPass, which store them in encrypted databases. DO use strong passwords — or better, passphrases — that include both upper- and lower-case letters, numbers and symbols. Change passwords regularly, and don't use the same one for everything. Reprinted by permission from Macmillan Publishers Ltd: Nature. 464:1260–1, copyright 2010.

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)0.003
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.123
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.1230.078

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 head0.056
GPT teacher head0.355
Teacher spread0.299 · 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
GenreCommentary

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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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