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Enregistrement W2083421973 · doi:10.1373/clinchem.2010.151837

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

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

Notice bibliographique

RevueClinical Chemistry · 2010
Typearticle
Langueen
DomaineComputer Science
ThématiqueCybercrime and Law Enforcement Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHackerFellComplaintLaw enforcementQuarter (Canadian coin)CybercrimeThe InternetHappeningLawInternet privacyHistoryPsychologyComputer securityPolitical scienceComputer scienceWorld Wide WebArt historyGeography

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,123
Score d'incertitude au seuil0,410

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0040,003
Science ouverte0,0010,001
Intégrité de la recherche0,0070,006
Charge utile insuffisante (le modèle a refusé de juger)0,1230,078

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,056
Tête enseignante GPT0,355
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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