attackereconomics
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attackereconomics [2017/10/24 14:46] – [Exploit trading] lallodi | attackereconomics [2021/01/10 21:04] (current) – external edit 127.0.0.1 | ||
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* How are these markets operating, what makes them sustainable from an economic perspective, | * How are these markets operating, what makes them sustainable from an economic perspective, | ||
* How does the risk profile of an exploit change once the exploit is traded in a market? Can we pinpoint economic and technical characteristics that affect the risk of attacks at scale driven by that exploit? | * How does the risk profile of an exploit change once the exploit is traded in a market? Can we pinpoint economic and technical characteristics that affect the risk of attacks at scale driven by that exploit? | ||
- | ===== Market selection and infiltration | + | |
+ | ==== Market selection and infiltration ==== | ||
Criteria for market evaluation. It is important to rst evaluate whether the selected market is a credible candidate for analysis, or is yet another example of many ‘scam-for-scammers’ underground forums. We performed an analysis of the markets’ economic mechanisms (e.g. addressing information asymmetry, adverse selection, and moral hazard), traded goods, and participation, | Criteria for market evaluation. It is important to rst evaluate whether the selected market is a credible candidate for analysis, or is yet another example of many ‘scam-for-scammers’ underground forums. We performed an analysis of the markets’ economic mechanisms (e.g. addressing information asymmetry, adverse selection, and moral hazard), traded goods, and participation, | ||
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The boxplots report reputation levels in the failed market (left) and working market (right) by user group. User groups map levels of membership in the market and are ordered in the plots by increasing trustworthiness as explicitly specified in the market regulations. It is immediately apparent that reputation mechanism in the failed market failed to provide a sound signalling mechanism for trustworthy users, as //banned// users have on average a higher reputation than //normal// users. The mapping between user trust and reputation level is clearly more meaningful in the working market (plot on the right), for which the reputation mechanism appears to be at least coherent in identifying reputable market players. | The boxplots report reputation levels in the failed market (left) and working market (right) by user group. User groups map levels of membership in the market and are ordered in the plots by increasing trustworthiness as explicitly specified in the market regulations. It is immediately apparent that reputation mechanism in the failed market failed to provide a sound signalling mechanism for trustworthy users, as //banned// users have on average a higher reputation than //normal// users. The mapping between user trust and reputation level is clearly more meaningful in the working market (plot on the right), for which the reputation mechanism appears to be at least coherent in identifying reputable market players. | ||
- | ===== Exploit trading | + | ==== Exploit trading ==== |
In the paper [[https:// | In the paper [[https:// | ||
{{: | {{: | ||
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+ | Further, we find a clear relation between market dynamics and exploitation at scale. | ||
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+ | {{ : | ||
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+ | The figure above reports exploit package cost (left) and market activity (right) against presence of exploit at scale. Even by just looking at the descriptive statistics in the boxplot it is apparent that higher prices hinder odds of exploit adoption, and that the opposite is true for market activity. A more formal analysis of these aspects is provided in the [[https:// | ||
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+ | ===== Attacker models ===== | ||
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+ | The observation of the economic background of the attacker calls for new models of attacker decisions. A critical aspect of this is exploit introduction, | ||
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+ | {{ : | ||
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+ | The figure above reports the rate at which already-attacked users receive attacks targeting the same vulnerability (red line) or a different vulnerability (black dotted line). The data comes from the [[https:// | ||
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+ | The paper " | ||
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+ | ===== References ===== | ||
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+ | * Luca Allodi. Underground Economics for Vulnerability Risk. Usenix ;login: (2018), Vol 43, no. 1. [[https:// | ||
+ | * Jukka Ruohonen, Luca Allodi. A bug bounty perspective on the disclosure of web vulnerabilities. Presented at WEIS 2018, Innsbruck, AT. To appear. | ||
+ | * Luca Allodi, Marco Cremonini, Fabio Massacci, Woohyun Shim. The effect of security education and expertise on security assessments: | ||
+ | * Luca Allodi. Economic Factors of Vulnerability Trade and Exploitation: | ||
+ | * Luca Allodi, Fabio Massacci, Julian Williams. The Work-Averse Cyber Attacker Model. Evidence from two million attack signatures. Published in WEIS 2017. [[https:// | ||
+ | * Luca Allodi, Fabio Massacci. Attack potential in Impact and Complexity. To appear in ARES 2017. [[https:// | ||
+ | * Luca Allodi, Marco Corradin, Fabio Massacci. Then and Now: On The Maturity of the Cybercrime Markets. The lesson black-hat marketeers learned. IEEE Transactions on Emerging Topics in Computing, 4(1): | ||
+ | * Luca Allodi. The Heavy Tails of Vulnerability Exploitation In the Proceedings of ESSoS 2015. [[http:// | ||
+ | * Luca Allodi. Attacker economics for Internet-scale vulnerability risk assessment (Extended Abstract) Research proposal, in Proceedings of Usenix LEET 2013. [[http:// | ||
+ | * Luca Allodi, Vadim Kotov, Fabio Massacci. MalwareLab: Experimentation with Cybercrime Attack Tools. In Proceedings of Usenix CSET 2013. [[http:// | ||
+ | * Luca Allodi, Woohyun Shim, Fabio Massacci. Quantitative assessment of risk reduction with cybercrime black market monitoring. Proceedings of IEEE S&P 2013 International Workshop on Cyber Crime. [[http:// | ||
+ | * Woohyun Shim, Luca Allodi, Fabio Massacci. Crime Pays If You Are Just an Average Hacker. Proceedings of IEEE/ASE 2012 Cyber Security Conference. [[http:// |
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