Notice bibliographique
Résumé
Cyber-attack studies are at the core of cybersecurity studies.Cyber-attacks threaten our ability to use the Internet safely, productively, and creatively worldwide and are the source of many security concerns.However, the "cyberattack" concept is underdeveloped in the academic literature and what is meant by cyber-attack is not clear.To advance theory, design and operate databases to support scholarly research, perform empirical observations, and compare different types of cyber-attacks, it is necessary to first clarify the "concept of cyber-attack".In this thesis, the following research question is addressed: How to represent a cyber-attack?Entity Relationship Diagrams are used to examine definitions of cyber-attacks available in the literature and information on ten successful high-profile attacks that is available on the Internet.This exploratory research contributes a representation and a definition of the concept of cyber-attack.The representation organizes data on cyber-attacks that is publicly available on the Internet into nine data entities, identifies the attributes of each entity, and the relationships between entities.In this representation, Adversary 1 (i.e., attacker) acts to: i) undermine Adversary 2's networks, systems, software or information or ii) damage the physical assets they control.Both adversaries share cyberspace and are affected by factors extrinsic to their organizations.Adversary 2 is comprised of two parts; one includes the organizations that operate the network and the other that is extrinsic to the iii organizations that operate the network.Although this research will be of interest to a broad community, it will be of particular interest to senior executives, government contractors, and researchers interested in contributing to the development of an interdisciplinary and global theory of cybersecurity.has been a tremendous mentor for me.You have done beyond a supervisor's responsibility.It has been such a great honour to be your student.I can write a dissertation on how a wonderful human being you are.This thesis would not have been possible without the guidance and the help of Professor Bailetti.Thank you for being best possible role model I could have hoped for.Working with you has been a most rewarding moment of my life.For your patience, kindness, advice and devotion, thank you.I would like to express my sincere appreciation to Dan Craigen for his generous sharing of his unique knowledge.I will be forever grateful to him for the many ways he contributed to this thesis.A special thank to my family, which this journey would not have been possible without the support of them.Words cannot express how grateful I am to my father, Mohammad Hassan, whom has 2 PhDs, which was the biggest motivation for me to do my master's.I understood the real meaning of love when you said that you were proud of me even when I failed.Thank you for working hard to provide for our family.I owe my deepest gratitude to my mother
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,012 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,004 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».