An inquiry into the nature and causes of the wealth of internet miscreants

By Jason Franklin, Adrian Perrig, Vern Paxson, Stefan Savage. Conference on Computer and Communications Security, 2007

459 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/abb1b2f06076124d1590bff7ba7ed6bad0ea2b4b

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Citations in the corpus

A survey of mobile malware in the wild (2011, background): “collected IRC logs relating to the Internet black market [30].”
Measuring Pay-per-Install: The Commoditization of Malware Distribution (2011, background): “…culture that has brought about a wide range of specialized providers for all stages in the malware-monetization life-cycle, such as malware toolkits [3, 15], packing tools to evade antivirus (AV) software [21], “bullet-proof” hosting [4], and forums for buying and selling ill-gotten gains [10].”
Secure or insure?: a game-theoretic analysis of information security games (2008, unknown): “Others have clearly demonstrated financial goals [17].”
Trafficking Fraudulent Accounts: The Role of the Underground Market in Twitter Spam and Abuse (2013, background): “A detailed summary of the restrictions placed on our study is available in Appendix A”
Your botnet is my botnet: analysis of a botnet takeover (2009, background): “Consistent with the past few years’ shift of malware from a forfun (or notoriety) activity to a for-profit enterprise [10, 15], Torpig is specifically crafted to obtain information that can be readily monetized in the underground market.”
A Learning-Based Approach to Reactive Security (2009, background): “Other attackers steal credit card numbers because credit card numbers have monetary value [10].”
Automatic analysis of malware behavior using machine learning (2011, unknown): “Proliferation of this threat is driven by a criminal industry which systematically comprises networked hosts for illegal purposes, such as distribution of spam messages or gathering of conﬁdential data (see [20,25]).”
All Your iFRAMEs Point to Us (2008, background): “While the monetary gains from the myriad of illicit behaviors being perpetrated today (e.g., phishing, spam) is just barely being understood [ 11 ], it is clear that there is a general shift in tactics—wide-scale attacks aimed at overwhelming computing resources are becoming less prevalent, and inst”
On the Security of Machine Learning in Malware C&C Detection (2016, background): “…ﬁnancially motivated, are responsible for the compromise of large numbers of machines, and result in the theft of ﬁnancial data, such as credit card numbers and online banking account credentials [Franklin et al. 2007], or used in carrying out attacks including Distributed Denial of Service (DDoS).”
Adversarial attacks against intrusion detection systems: Taxonomy, solutions and open issues (2013, background): “wealthy underground markets, where a wide variety of illicit services and exploitation tools are commercialized [51], [155].”
BotGrep: Finding P2P Bots with Structured Graph Analysis (2010, background): “This problem has worsened to a point where modern botnets control hundreds of thousands of hosts and generate revenues of millions of dollars per year for their owners [23, 42].”
Open problems in the security of learning (2008, unknown): “As the motivation for attacks becomes increasingly fiscal [8], attackers employ more sophisticated methods”
A survey of coordinated attacks and collaborative intrusion detection (2010, background): “After recruiting tens of thousands of compromised hosts through worm spread or from underground markets, the attacker can use large-scale DDoS attacks to blackmail service providers for monetary gain (Franklin et al., 2007).”
Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed through Cryptocurrencies? (2019, background): “Large-scale initiatives such as “Operation Onymous,” in which law enforcement agencies shut down several illegal marketplaces and made 17 arrests across 17 countries, can discourage illegal online activity by increasing the risk of detection (Franklin et al. 2007).”
Click Trajectories: End-to-End Analysis of the Spam Value Chain (2011, background): “seen on IRC chatrooms [10], forums [59], malware “dropzones” [16], or directly by intercepting communications to botnet C&C servers [50].”
An analysis of underground forums (2011, background): “[4], to provide a public medium for sharing information about the availability and pricing of goods and services (e.”