Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 資訊管理學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56136
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor林永松
dc.contributor.authorYi-Jhen Linen
dc.contributor.author林怡蓁zh_TW
dc.date.accessioned2021-06-16T05:16:34Z-
dc.date.available2019-09-03
dc.date.copyright2014-09-03
dc.date.issued2014
dc.date.submitted2014-08-17
dc.identifier.citation1. Lab, K., Global IT Security Risks: 2012. Kaspersky, 2012.
2. Ponemon, Cost of Cyber Crime Study: United States. Ponemon Institute, Octorber 2013.
3. Robert, R., 2010/2011 Computer CrIme and Security Survey, 2011: Computer Security Institute.
4. IBM, The economics of IT risk and reputation. IBM Corporation, September 2013.
5. Casey, F., et al. Survivability analysis of distributed systems using attack tree methodology. in Military Communications Conference, 2005. MILCOM 2005. IEEE. 2005.
6. Hausken, K. and G. Levitin, Redundancy vs. Protection vs. False Targets for Systems Under Attack. Reliability, IEEE Transactions on, 2009. 58(1): p. 58-68.
7. Hausken, K. and G. Levitin, Protection vs. false targets in series systems. Reliability Engineering & System Safety, 2009. 94(5): p. 973-981.
8. Hausken, K. and G. Levitin, Is it wise to leave some false targets unprotected? Reliability Engineering & System Safety, 2013. 112(0): p. 176-186.
9. Wang, L., et al., Improving System Reliability Against Rational Attacks Under Given Resources. Systems, Man, and Cybernetics: Systems, IEEE Transactions on, 2013. PP(99): p. 1-1.
10. Kjell, H., V.M. Bier, and J. Zhuang, Defending Against Terrorism, Natural Disaster, and All Hazards. Springer, 2009.
11. Wei, J., et al. Optimal Network Security Strengthening Using Attack-Defense Game Model. in Information Technology: New Generations, 2009. ITNG '09. Sixth International Conference on. 2009.
12. Zhuang, J., V.M. Bier, and O. Alagoz, Modeling secrecy and deception in a multiple-period attacker–defender signaling game. European Journal of Operational Research, 2010. 203(2): p. 409-418.
13. Hausken, K. and G. Levitin, Resource Distribution in Multiple Attacks Against a Single Target. Risk Analysis, 2010. 30(8): p. 1231-1239.
14. Rasmusen, E., Games and Information: An Introduction to Game theory. February 2000, New York: Basil Blackwell.
15. Burke, D.A., Towards a Game Theory Model of Information Warfare. Master's thesis, Graduate School of Engineering and Management, Airforce Institute of Technology, Air University, Nov 1999.
16. Sheremeta, C.D.R.M., Fight or Flight?: Defending against Sequential Attacks in the Game of Siege. Journal of Conflict Resolution, July 2012.
17. Harsanyi, J.C., Games with Incomplete Information Played by “Bayesian” Players, I–III: Part I. The Basic Model&. Management Science, 2004. 50(12_supplement): p. 1804-1817.
18. Hausken, K. and G. Levitin, False targets efficiency in defense strategy. European Journal of Operational Research, 2009. 194(1): p. 155-162.
19. Peng, R., et al. Intelligence and impact contests in defending a single object with imperfect false targets. in Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on. 2009.
20. Peng, R., W. Wenbin, and Z. Fei. Object defense strategy with imperfect false targets and disinformation. in Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on. 2012.
21. Janczewski, L. and A.M. Colarik, Cyber Warfare and Cyber Terrorism. 2007, PA, USA: IGI Publishing Hershey.
22. Dunnigan, J.F. and A.A. Nofi, Victory and Deceit: Dirty Tricks at War. 1995: William Morrow & Co.
23. Rowe, N.C. and H.S. Rothstein, Two Taxonomies of Deception for Attacks on Information Systems. Journal of Information Warfare, July 2004. 3(2).
24. Copeck, T., S. Delisle, and S. Szpakowicz, Parsing and case analysis in TANKA, in Proceedings of the 14th conference on Computational linguistics - Volume 31992, Association for Computational Linguistics: Nantes, France. p. 1008-1012.
25. Bell, J.B. and B. Whaley, Cheating and Deception. 1982, New Brunswick, NJ: Transaction Publishers.
26. Yuill, J., D. Denning, and F.F. 3, Using Deception to Hide Things from Hackers: Processes, Principles, and Techniques Journal of Information Warfare, 2006.
27. Ellison, R.J., et al., Survivable Network Systems: An Emerging Discipline, in Technical Report CMU/SEI-97-TR-013November 1997.
28. Michael S Deutsch, R.R.W., Software quality engineering: A total technical and management approach. 1988: Englewood Cliffs, N.J. Prentice-Hall.
29. Wu, L., V.P. Varshney. On survivability measures for military networks. in Military Communications Conference, 1990. MILCOM '90, Conference Record, A New Era. 1990 IEEE. 1990.
30. Wilson, M.R., The quantitative impact of survivable network architectures on service availability. Communications Magazine, IEEE, 1998. 36(5): p. 122-126.

31. Linger, R.C., N.R. Mead, and H.F. Lipson. Requirements definition for survivable network systems. in Requirements Engineering, 1998. Proceedings. 1998 Third International Conference on. 1998.
32. J.C. Knight, K.J. Sullivan, On the Definition of Survivability, December 2000: Technical Report CS-TR-33-00.
33. Snow, A.P., U. Varshney, and A.D. Malloy, Reliability and survivability of wireless and mobile networks. Computer, 2000. 33(7): p. 49-55.
34. Voas, J.M. and A.K. Ghosh. Software fault injection for survivability. in DARPA Information Survivability Conference and Exposition, 2000. DISCEX '00. Proceedings. 2000.
35. Westmark, V.R. A definition for information system survivability. in System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on. 2004.
36. Zhanshan, M. and A.W. Krings. Survival Analysis Approach to Reliability, Survivability and Prognostics and Health Management (PHM). in Aerospace Conference, 2008 IEEE. 2008.
37. Bier, V.M., A. Nagaraj, and V. Abhichandani, Protection of simple series and parallel systems with components of different values. Reliability Engineering & System Safety, 2005. 87.
38. Skaperdas, S., Contest success functions. Economic Theory, 1996: p. 8.
39. Hartwig, R.P., Cyber Risks: The Growing Threat. Insurance Information Institute, 2013.
40. Hausken, K., Strategic defense and attack for series and parallel reliability systems. Journal of Operational Research, 2008. 186(2).
41. Hausken, K., Strategic defense and attack for reliability systems. Reliability Engineering and System Safety, 2008.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56136-
dc.description.abstract隨著網路的發展,資訊系統已成為企業運作中不可取代的部分,然而網路雖然給來企業許多好處,但同時也讓企業遭受更多的威脅。一旦連上網路的系統在遭受網路攻擊後造成系統無法正常運作時,將造成企業莫大的財物損失以及商譽上的毀損。因此如何有效配屬資源以抵禦攻擊者將是重要的議題。本篇論文的防禦者的防禦策略中,除了傳統的防禦機制外,由於攻擊者和防禦者間的資訊是不完全的,因此偽裝成為另一種有效的防禦機制。透過偽裝,我們得以運用假節點降低真實節點被攻擊的機率以及分散攻擊的火力以達到保護真實節點不受到摧毀的目的。因此如何在真假節點以及額外的偽裝方法下有效的分配有限的防禦資源以抵禦存在網路上的攻擊將會是一個重要的議題。
有鑑於此,在這篇論文中,我們建構了一個考慮在攻方具有攻擊喜好或稱為攻擊優先性之惡意攻擊環境下,防禦者的目標是最大化系統殘存的工作能力而攻擊者的目標是最小化系統殘存的工作能力。在情境中,攻擊者可以於每次攻擊發動前,先行分配一部分的智慧資源於探索系統並得到對於真假節點可能性的評分。評分較高者,代表其為真實節點的可能性高,因而在攻擊階段,攻擊者便可以透過評分機制來選擇攻擊的目標並分配適當的攻擊資源。而對防禦者而言,防禦者除了可以部屬所謂的假節點外,尚有其他種類的偽裝資源得以用來干擾攻擊者對攻擊目標的評分。最終,我們採用競爭成功函數來衡量競爭的結果,並求得最佳解。
zh_TW
dc.description.abstractWith the rapid growing of the Internet, information system has become an irreplaceable part of the businesses daily operation. However, although the Internet brings lots of advantages but also brings more threats to the businesses. It would create devastating financial and reputation damage to the business once the information system which is connected to the Internet is destroyed under cyber attack and caused the normal course of operations disrupted. Hence, it is important to efficiently allocate defense resource for the defender. In the defense strategy of the defender, besides traditional method to protect system, deception is another effective mechanism with the incomplete information between the defender and the attacker. Through deception, the false targets can be used to reduce the probability that the genuine targets are under attack and encounter less-attack effort to achieve the goal of protecting genuine targets from destruction. Therefore, it is an important issue to decide resources allocation strategies with the defense strategy includes false targets and additional deception under limited resources.
For this reason, we construct a model under the malicious attack with attack preference and the objective of the defender is to maximize the residual working capability while the objective of the attacker is to minimize that value. In our attack-defense scenario, the attacker can allocate part of budgets into exploring the system to obtain the evaluation of whether the target is valuable. When the value of evaluation is higher, it is more likely to be a genuine target. Therefore, the attacker can choose the targets to attack based on the evaluation and allocate proper resources to attack in the attack phase. In the view of the defender, besides deploys false targets, additional deception mechanisms can be used to interfere the evaluation of the attacker. Finally, the contest success function is adopted to evaluate the result and get the optimal solution in this problem.
en
dc.description.provenanceMade available in DSpace on 2021-06-16T05:16:34Z (GMT). No. of bitstreams: 1
ntu-103-R01725045-1.pdf: 3586376 bytes, checksum: f4f63a5e5fb9da53c2b2817ef0cdea96 (MD5)
Previous issue date: 2014
en
dc.description.tableofcontents誌謝 i
論文摘要 ii
ABSTRACT iii
CONTENTS v
LIST OF FIGURES vii
LIST OF TABLES x
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation 7
1.3 Literature Survey 10
1.3.1 Multi-round 10
1.3.2 Incomplete Information 11
1.3.3 Deception 13
1.3.4 Network survivability and Working Capability 19
1.4 Thesis Organization 23
Chapter 2 Problem Formulation 24
2.1 Contest Success Function 24
2.2 Problem Description 27
2.2.1 The Characteristic of the Defender and the Attacker 27
2.3 Problem Assumption 40
2.4 Mathematical Formulation 43
2.5 Mathematical Formulation II 50
Chapter 3 Solution Approach 58
3.1 The Solution Procedure 58
Chapter 4 Computational Experiments 60
4.1 Experiment Environment 60
4.2 The Experiments 62
4.2.1 Discussing the Impact of the Efficiency of Reduction Rate 62
4.2.2 Discussing the Impact of the Attack Percentage 88
4.2.3 Discussion the Impact of the Amount of the False Targets 93
Chapter 5 Summary and Future Work 107
5.1 Summary 107
5.2 Future Work 111
REFERENCE 113
dc.language.isozh-TW
dc.subject競爭成功函數zh_TW
dc.subject多階段zh_TW
dc.subject不完全資訊zh_TW
dc.subject資源配置zh_TW
dc.subject工作能力zh_TW
dc.subject偽裝策略zh_TW
dc.subject攻擊優先性zh_TW
dc.subjectResource Allocationen
dc.subjectWorking Capabilityen
dc.subjectAttack Preferenceen
dc.subjectDeceptionen
dc.subjectContest Success Functionen
dc.subjectMulti-rounden
dc.subjectInformationen
dc.title考量攻擊優先性以及多重偽裝方法下之資源分配策略zh_TW
dc.titleResource Allocation Strategies under Considerations of Attack Preference and Multiple Deceptive Methodsen
dc.typeThesis
dc.date.schoolyear102-2
dc.description.degree碩士
dc.contributor.oralexamcommittee林盈達,呂俊賢,鍾順平
dc.subject.keyword資源配置,不完全資訊,多階段,競爭成功函數,偽裝策略,攻擊優先性,工作能力,zh_TW
dc.subject.keywordResource Allocation,Information,Multi-round,Contest Success Function,Deception,Attack Preference,Working Capability,en
dc.relation.page115
dc.rights.note有償授權
dc.date.accepted2014-08-18
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept資訊管理學研究所zh_TW
顯示於系所單位:資訊管理學系

文件中的檔案:
檔案 大小格式 
ntu-103-1.pdf
  未授權公開取用
3.5 MBAdobe PDF
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved