Active Data Collection Techniques to Understand Online Scammers and Cybercriminals

Nigerian scam, also known as advance fee fraud or 419 scam, is a prevalent form of online fraudulent activity that causes financial loss to individuals and businesses. Nigerian scam has evolved from simple non-targeted email messages to more sophisticated scams targeted at users of classifieds, dating and other websites. Even though such scams are observed and reported by users frequently, the community’s understanding of Nigerian scams is limited since the scammers operate “underground”. To better understand the underground Nigerian scam ecosystem and seek effective methods to deter Nigerian scam and cybercrime in general, we conduct a series of active and passive measurement studies. Relying upon the analysis and insight gained from the measurement studies, we make four contributions: (1) we analyze the taxonomy of Nigerian scam and derive long-term trends in scams; (2) we provide an insight on Nigerian scam and cybercrime ecosystems and their underground operation; (3) we propose a payment intervention as a potential deterrent to cybercrime operation in general and evaluate its effectiveness; and (4) we offer active and passive measurement tools and techniques that enable in-depth analysis of cybercrime ecosystems and deterrence on them. We first created and analyze a repository of more than two hundred thousand user-reported scam emails, stretching from 2006 to 2014, from four major scam reporting websites. We select ten most commonly observed scam categories and tag 2,000 scam emails randomly selected from our repository. Based upon the manually tagged dataset, we train a machine learning classifier and cluster all scam emails in the repository. From the clustering result, we find a strong and sustained upward trend for targeted scams and downward trend for non-targeted scams. We then focus on two types of targeted scams: sales scams and rental scams targeted users on Craigslist. We built an automated scam data collection system and gathered large-scale sales scam emails. Using the system we posted honeypot ads on Craigslist and conversed automatically with the scammers. Through the email conversation, the system obtained additional confirmation of likely scam activities and collected additional information such as IP addresses and shipping addresses. Our analysis revealed that around 10 groups were responsible for nearly half of the over 13,000 total scam attempts we received. These groups used IP addresses and shipping addresses in both Nigeria and the U.S. We also crawled rental ads on Craigslist, identified rental scam ads amongst the large number of benign ads and conversed with the potential scammers. Through in-depth analysis of the rental scams, we found seven major scam campaigns employing various operations and monetization methods. We also found that unlike sales scammers, most rental scammers were in the U.S. The large-scale scam data and in-depth analysis provide useful insights on how to design effective deterrence techniques against cybercrime in general. We study underground DDoS-for-hire services, also known as booters, and measure the effectiveness of undermining a payment system of DDoS Services. Our analysis shows that the payment intervention can have the desired effect of limiting cybercriminals’ ability and increasing the risk of accepting payments.

EXISTENCE OF UNUSED MANAGED CAPACITY ON DEDICATED LANES AND AN ALTERNATIVE ON HOW TO SELL IT VIA AUCTIONS

This dissertation verifies whether the following two hypotheses are true: (1) High-occupancy/toll lanes (and therefore other dedicated lanes) have capacity that could still be used; (2) such unused capacity (or more precisely, “unused managed capacity”) can be sold successfully through a real-time auction. To show that the second statement is true, this dissertation proposes an auction-based metering (ABM) system, that is, a mechanism that regulates traffic that enters the dedicated lanes. Participation in the auction is voluntary and can be skipped by paying the toll or by not registering to the new system. This dissertation comprises the following four components: a measurement of unused managed capacity on an existing HOT facility, a game-theoretic model of an ABM system, an operational description of the ABM system, and a simulation-based evaluation of the system. Some other and more specific contributions of this dissertation include the following: (1) It provides a definition and a methodology for measuring unused managed capacity and another important variable referred as “potential volume increase”. (2) It proves that the game-theoretic model has a unique Bayesian Nash equilibrium. (3) And it provides a specific road design that can be applied or extended to other facilities. The results provide evidence that the hypotheses are true and suggest that the ABM system would benefit a public operator interested in reducing traffic congestion significantly, would benefit drivers when making low-reliability trips (such as work-to-home trips), and would potentially benefit a private operator interested in raising revenue.