Knowledge-Based Information Extraction: A Case Study of Recognizing Emails of Nigerian Frauds

Gao, Yanbin; Zhao, Gang

doi:10.1007/11428817_15

Cited by 16 publications

(9 citation statements)

References 3 publications

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“…This type of scams has been widely studied by the research community [12,17,18,21,23,25]. Despite the similarities, in this paper we showed that online dating scams are very different from these schemes, because they typically involve a long exchange of messages between the scammer and the victim before the actual scam is performed.…”

Section: Related Workmentioning

confidence: 76%

“…As an example, scammers commonly set up fake accounts on an online dating site, start interacting with a user on the site, and then lure her into sending them money, for example to pay for the flight needed to meet in person [36]. Such scams are similar in spirit to the infamous "419 scams," in which scammers ask their victims to send them a sum of money to establish trust and then promise to transfer a very large sum to them [17,18,23,25]. Online dating scams, however, are more insidious than "419 scams," because they target emotionally vulnerable people looking for love.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quit Playing Games with My Heart: Understanding Online Dating Scams

Huang

Stringhini

Yong

2015

Detection of Intrusions and Malware, and Vulnerability Assessment

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Abstract. Online dating sites are experiencing a rise in popularity, with one in five relationships in the United States starting on one of these sites. Online dating sites provide a valuable platform not only for single people trying to meet a life partner, but also for cybercriminals, who see in people looking for love easy victims for scams. Such scams span from schemes similar to traditional advertisement of illicit services or goods (i.e., spam) to advanced schemes, in which the victim starts a long-distance relationship with the scammer and is eventually extorted money. In this paper we perform the first large-scale study of online dating scams. We analyze the scam accounts detected on a popular online dating site over a period of eleven months, and provide a taxonomy of the different types of scammers that are active in the online dating landscape. We show that different types of scammers target a different demographics on the site, and therefore set up accounts with different characteristics. Our results shed light on the threats associated to online dating scams, and can help researchers and practitioners in developing effective countermeasures to fight them.

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Section: Related Workmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Quit Playing Games with My Heart: Understanding Online Dating Scams

Huang

Stringhini

Yong

2015

Detection of Intrusions and Malware, and Vulnerability Assessment

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“…This study also argued that scammers' email addresses and phone numbers are crucial factors of the clustering. Goa et al [4] investigates the use of ontology-based knowledge engineering for Nigerian scam email text mining. Unlike previous studies, in our investigation we have focused on 1) understanding in great depth the prevalence and techniques, and 2) identifying the structure of larger scale groups of scammers that are engaged in attempting to defraud people posting goods for sale on Craigslist.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, they often used abusive language to coerce their victims into actually shipping the items. In addition, it would be feasible to exploit common linguistic features of scam email contents [4]. The combination of these patterns and the different reply-to address might be effectively used to improve the filtering of these messages.…”

Section: Locations Of Scammersmentioning

confidence: 99%

Scambaiter: Understanding Targeted Nigerian Scams on Craigslist

Park¹,

Jones

McCoy

et al. 2014

Proceedings 2014 Network and Distributed System Security Symposium

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Abstract-Advance fee fraud scams, also known as Nigerian scams have evolved from simple untargeted email messages to more sophisticated scams targeted at users of classifieds, dating and other websites. Even though such scams are observed frequently, the community's understanding of targeted Nigerian scam is limited since the scammers operate "underground". In this paper, we focus on fake payment scams targeting users on Craigslist. To better understand this type of scam and associated scammers, we built an automated data collection system. The system relied on what we term magnetic honeypot advertisements. These are advertisements that are designed to attract scammers but repel legitimate users -similar to how a magnet attracts one side of a magnet but repels the other. Using advertisements of this type, we offered goods for sale on Craigslist, gathered scam emails and interacted with scammers. We use this measurement platform to gather three months of data and perform an in-depth analysis. Our analysis provides us with a better understanding of scammers' action patterns, automation tools, scammers' email account usage and distribution of scammers' geolocation. From our analysis of this dataset, we find that around 10 groups of scammers were responsible for nearly half of the over 13,000 total scam attempts we received. These groups use shipping address and phone numbers in both Nigeria and the U.S. We also identify potential methods of deterring these targeted scams based on patterns in the scammer's messages and usage of email accounts that might enable improved filter of their initial messages by content and email address.

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“…A simple example for extraction of relevant information using knowledge based approaches can be associated with the knowledge of the structure of documents to, for instance, extract keywords from the titles and abstracts of scientific documents. More complex examples, like (Gao & Zhao, 2005), are able to identify frauds on emails. However, these kinds of approaches are also quite limiting, mainly because the creation of ontologies isn't straightforward, and ontologies are something very specific to a certain subject and can't be easily generalized.…”

Section: Current State-of-the-art Methods For Unigram Extractionmentioning

confidence: 99%