100 resultados para Fraudulent conveyances
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In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document.
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General note: Title and date provided by Bettye Lane.
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In the past decade, several major food safety crises originated from problems with feed. Consequently, there is an urgent need for early detection of fraudulent adulteration and contamination in the feed chain. Strategies are presented for two specific cases, viz. adulterations of (i) soybean meal with melamine and other types of adulterants/contaminants and (ii) vegetable oils with mineral oil, transformer oil or other oils. These strategies comprise screening at the feed mill or port of entry with non-destructive spectroscopic methods (NIRS and Raman), followed by post-screening and confirmation in the laboratory with MS-based methods. The spectroscopic techniques are suitable for on-site and on-line applications. Currently they are suited to detect fraudulent adulteration at relatively high levels but not to detect low level contamination. The potential use of the strategies for non-targeted analysis is demonstrated.
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With the increasing significance of information technology, there is an urgent need for adequate measures of information security. Systematic information security management is one of most important initiatives for IT management. At least since reports about privacy and security breaches, fraudulent accounting practices, and attacks on IT systems appeared in public, organizations have recognized their responsibilities to safeguard physical and information assets. Security standards can be used as guideline or framework to develop and maintain an adequate information security management system (ISMS). The standards ISO/IEC 27000, 27001 and 27002 are international standards that are receiving growing recognition and adoption. They are referred to as “common language of organizations around the world” for information security. With ISO/IEC 27001 companies can have their ISMS certified by a third-party organization and thus show their customers evidence of their security measures.
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The large number of opinions generated by online users made the former “word of mouth” find its way to virtual world. In addition to be numerous, many of the useful reviews are mixed with a large number of fraudulent, incomplete or duplicate reviews. However, how to find the features that influence on the number of votes received by an opinion and find useful reviews? The literature on opinion mining has several studies and techniques that are able to analyze of properties found in the text of reviews. This paper presents the application of a methodology for evaluation of usefulness of opinions with the aim of identifying which characteristics have more influence on the amount of votes: basic utility (e.g. ratings about the product and/or service, date of publication), textual (e.g.size of words, paragraphs) and semantics (e.g., the meaning of the words of the text). The evaluation was performed in a database extracted from TripAdvisor with opinionsabout hotels written in Portuguese. Results show that users give more attention to recent opinions with higher scores for value and location of the hotel and with lowest scores for sleep quality and service and cleanliness. Texts with positive opinions, small words, few adjectives and adverbs increase the chances of receiving more votes.
Development of a simple and fast “DNA extraction kit” for sea food identification and marine species
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Seafood products fraud, the misrepresentation of them, have been discovered all around the world in different forms as false labeling, species substitution, short-weighting or over glazing in order to hide the correct identity, origin or weight of the seafood products. Due to the value of seafood products such as canned tuna, swordfish or grouper, these species are the subject of the commercial fraud is mainly there placement of valuable species with other little or no value species. A similar situation occurs with the shelled shrimp or shellfish that are reduced into pieces for the commercialization. Food fraud by species substitution is an emerging risk given the increasingly global food supply chain and the potential food safety issues. Economic food fraud is committed when food is deliberately placed on the market, for financial gain deceiving consumers (Woolfe, M. & Primrose, S. 2004). As a result of the increased demand and the globalization of the seafood supply, more fish species are encountered in the market. In this scenary, it becomes essential to unequivocally identify the species. The traditional taxonomy, based primarily on identification keys of species, has shown a number of limitations in the use of the distinctive features in many animal taxa, amplified when fish, crustacean or shellfish are commercially transformed. Many fish species show a similar texture, thus the certification of fish products is particularly important when fishes have undergone procedures which affect the overall anatomical structure, such as heading, slicing or filleting (Marko et al., 2004). The absence of morphological traits, a main characteristic usually used to identify animal species, represents a challenge and molecular identification methods are required. Among them, DNA-based methods are more frequently employed for food authentication (Lockley & Bardsley, 2000). In addition to food authentication and traceability, studies of taxonomy, population and conservation genetics as well as analysis of dietary habits and prey selection, also rely on genetic analyses including the DNA barcoding technology (Arroyave & Stiassny, 2014; Galimberti et al., 2013; Mafra, Ferreira, & Oliveira, 2008; Nicolé et al., 2012; Rasmussen & Morrissey, 2008), consisting in PCR amplification and sequencing of a COI mitochondrial gene specific region. The system proposed by P. Hebert et al. (2003) locates inside the mitochondrial COI gene (cytochrome oxidase subunit I) the bioidentification system useful in taxonomic identification of species (Lo Brutto et al., 2007). The COI region, used for genetic identification - DNA barcode - is short enough to allow, with the current technology, to decode sequence (the pairs of nucleotide bases) in a single step. Despite, this region only represents a tiny fraction of the mitochondrial DNA content in each cell, the COI region has sufficient variability to distinguish the majority of species among them (Biondo et al. 2016). This technique has been already employed to address the demand of assessing the actual identity and/or provenance of marketed products, as well as to unmask mislabelling and fraudulent substitutions, difficult to detect especially in manufactured seafood (Barbuto et al., 2010; Galimberti et al., 2013; Filonzi, Chiesa, Vaghi, & Nonnis Marzano, 2010). Nowadays,the research concerns the use of genetic markers to identify not only the species and/or varieties of fish, but also to identify molecular characters able to trace the origin and to provide an effective control tool forproducers and consumers as a supply chain in agreementwith local regulations.
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Mestrado em Auditoria
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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.
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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.
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This guide gives important information about how to receive unemployment benefits. Topics include: Privacy Act, Equal Opportunity Statement, Income and Eligibility Verification Notice, Unemployment Insurance Benefits, Eligibility requirements, Unemployment Compensation for Federal Employees, Employment Compensation for Ex-Servicemembers,School Worker Claims, Pension Reduction, Official Court Appearances and Benefit eligibility, Benefits are Based on Wages Paid, Initial Determination, Benefit Year, Waiting Period, Maximum Weekly Benefit Amount, To Establish a Weekly Benefit Amount, Disqualification, Fraudulent claims, Requests for Reconsideration, Appeal Provisions, Standard and Alternate Base Period Explained, Partial Employment,Self-Employment, Students, Interstate Benefits, Benefits Will Be Taxable, Individual Benefits, Filing Your Weekly Claim, Filing Your Weekly Claim Online,Filing Your Weekly Claim by TelClaim and New Hires.