Uncovering Insurance Fraud Conspiracy with Network Learning

Fraudulent claim detection is one of the greatest challenges the insurance industry faces. Alibaba's return-freight insurance, providing return-shipping postage compensations over product return on the e-commerce platform, receives thousands of potentially fraudulent claims every day. Such deliberate abuse of the insurance policy could lead to heavy financial losses. In order to detect and prevent fraudulent insurance claims, we developed a novel data-driven procedure to identify groups of organized fraudsters, one of the major contributions to financial losses, by learning network information. In this paper, we introduce a device-sharing network among claimants, followed by developing an automated solution for fraud detection based on graph learning algorithms, to separate fraudsters from regular customers and uncover groups of organized fraudsters. This solution applied at Alibaba achieves more than 80% precision while covering 44% more suspicious accounts compared with a previously deployed rule-based classifier after human expert investigations. Our approach can easily and effectively generalizes to other types of insurance.Comment: Accepted by SIGIR '19. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. 201

Value-driven Security Agreements in Extended Enterprises

Today organizations are highly interconnected in business networks called extended enterprises. This is mostly facilitated by outsourcing and by new economic models based on pay-as-you-go billing; all supported by IT-as-a-service. Although outsourcing has been around for some time, what is now new is the fact that organizations are increasingly outsourcing critical business processes, engaging on complex service bundles, and moving infrastructure and their management to the custody of third parties. Although this gives competitive advantage by reducing cost and increasing flexibility, it increases security risks by eroding security perimeters that used to separate insiders with security privileges from outsiders without security privileges. The classical security distinction between insiders and outsiders is supplemented with a third category of threat agents, namely external insiders, who are not subject to the internal control of an organization but yet have some access privileges to its resources that normal outsiders do not have. Protection against external insiders requires security agreements between organizations in an extended enterprise. Currently, there is no practical method that allows security officers to specify such requirements. In this paper we provide a method for modeling an extended enterprise architecture, identifying external insider roles, and for specifying security requirements that mitigate security threats posed by these roles. We illustrate our method with a realistic example

Investigating and Validating Scam Triggers: A Case Study of a Craigslist Website

The internet and digital infrastructure play an important role in our day-to-day live, and it has also a huge impact on the organizations and how we do business transactions every day. Online business is booming in this 21st century, and there are many online platforms that enable sellers and buyers to do online transactions collectively. People can sell and purchase products that include vehicles, clothes, and shoes from anywhere and anytime. Thus, the purpose of this study is to identify and validate scam triggers using Craigslist as a case study. Craigslist is one of the websites where people can post advertising to sell and buy personal belongings online. However, with the growing number of people buying and selling, new threats and scams are created daily. Private cars are among the most significant items sold and purchased over the craigslist website. In this regard, several scammers have been drawn by the large number of vehicles being traded over craigslist. Scammers also use this forum to cheat others and exploit the vulnerable. The study identified online scam triggers including Bad key words, dealers’ posts as owners, personal email, multiple location, rogue picture and voice over IP to detect online scams that exists in craigslist. The study also found over 360 ads from craigslist based on our scam trigger. Finally, the study validated each and every one of the scam triggers and found 53.31% of our data is likelihood to be considered as a scam

Adversarial behaviours knowledge area

The technological advancements witnessed by our society in recent decades have brought improvements in our quality of life, but they have also created a number of opportunities for attackers to cause harm. Before the Internet revolution, most crime and malicious activity generally required a victim and a perpetrator to come into physical contact, and this limited the reach that malicious parties had. Technology has removed the need for physical contact to perform many types of crime, and now attackers can reach victims anywhere in the world, as long as they are connected to the Internet. This has revolutionised the characteristics of crime and warfare, allowing operations that would not have been possible before. In this document, we provide an overview of the malicious operations that are happening on the Internet today. We first provide a taxonomy of malicious activities based on the attacker’s motivations and capabilities, and then move on to the technological and human elements that adversaries require to run a successful operation. We then discuss a number of frameworks that have been proposed to model malicious operations. Since adversarial behaviours are not a purely technical topic, we draw from research in a number of fields (computer science, criminology, war studies). While doing this, we discuss how these frameworks can be used by researchers and practitioners to develop effective mitigations against malicious online operations.Published versio

Is it Possible to Reform a Customs Administration? The Role of the Customs Elite on the Reform Process in Cameroon

An ethnographic approach is applied to Cameroon customs in order to explore the role and the capacity of the bureaucratic elites to reform their institution. Fighting against corruption has led to the extraction and circulation of legal ‘collective money’ that fuels internal funds. This collective money is the core of the senior officers’ power and authority, and materially grounds their elite status. Nevertheless, when reforming, wilful senior officers face a major problem. On the one hand, the onus is on them to improve governance and transparency, which can challenge the way they exert their authority. On the other hand, goodwill is not sufficient. ‘Reformers’ depend on a violent and unpredictable appointment process, driven by the political will to fight against corruption and the fact that the political authority has to keep a close eye on the customs apparatus that tends towards autonomy, thanks to its internal funds. Violence and collective representations weaken the legitimacy of the senior officers, even the reformers, by pushing individual skills into the background. This paper questions whether Cameroon’s use of official customs data to evaluate individual performance can open up fissures among customs elites such that reformers are distinguished from others.customs, money circulation, elitism, Cameroon