Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
The Analysis Function of the US-CERT Control Systems Security Center (CSSC) at the Idaho National Laboratory (INL) has prepared this report to document cyber security incidents for use by the CSSC. The description and analysis of incidents reported herein support three CSSC tasks: establishing a business case; increasing security awareness and private and corporate participation related to enhanced cyber security of control systems; and providing informational material to support model development and prioritize activities for CSSC. The stated mission of CSSC is to reduce vulnerability of critical infrastructure to cyber attack on control systems. As stated in the Incident Management Tool Requirements (August 2005) ''Vulnerability reduction is promoted by risk analysis that tracks actual risk, emphasizes high risk, determines risk reduction as a function of countermeasures, tracks increase of risk due to external influence, and measures success of the vulnerability reduction program''. Process control and Supervisory Control and Data Acquisition (SCADA) systems, with their reliance on proprietary networks and hardware, have long been considered immune to the network attacks that have wreaked so much havoc on corporate information systems. New research indicates this confidence is misplaced--the move to open standards such as Ethernet, Transmission Control Protocol/Internet Protocol, and Web technologies is allowing hackers to take advantage of the control industry's unawareness. Much of the available information about cyber incidents represents a characterization as opposed to an analysis of events. The lack of good analyses reflects an overall weakness in reporting requirements as well as the fact that to date there have been very few serious cyber attacks on control systems. Most companies prefer not to share cyber attack incident data because of potential financial repercussions. Uniform reporting requirements will do much to make this information available to Department of Homeland Security (DHS) and others who require it. This report summarizes the rise in frequency of cyber attacks, describes the perpetrators, and identifies the means of attack. This type of analysis, when used in conjunction with vulnerability analyses, can be used to support a proactive approach to prevent cyber attacks. CSSC will use this document to evolve a standardized approach to incident reporting and analysis. This document will be updated as needed to record additional event analyses and insights regarding incident reporting. This report represents 120 cyber security incidents documented in a number of sources, including: the British Columbia Institute of Technology (BCIT) Industrial Security Incident Database, the 2003 CSI/FBI Computer Crime and Security Survey, the KEMA, Inc., Database, Lawrence Livermore National Laboratory, the Energy Incident Database, the INL Cyber Incident Database, and other open-source data. The National Memorial Institute for the Prevention of Terrorism (MIPT) database was also interrogated but, interestingly, failed to yield any cyber attack incidents. The results of this evaluation indicate that historical evidence provides insight into control system related incidents or failures; however, that the limited available information provides little support to future risk estimates. The documented case history shows that activity has increased significantly since 1988. The majority of incidents come from the Internet by way of opportunistic viruses, Trojans, and worms, but a surprisingly large number are directed acts of sabotage. A substantial number of confirmed, unconfirmed, and potential events that directly or potentially impact control systems worldwide are also identified. Twelve selected cyber incidents are presented at the end of this report as examples of the documented case studies (see Appendix B).
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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