Identity theft

About: Identity theft is a research topic. Over the lifetime, 2284 publications have been published within this topic receiving 31700 citations.

Online Transaction Security Using Face Recognition: A Review

Abstract: Abstract: The growing development of the e-commerce market is of great significance in the world. In this online shopping process, the security of personal information and debit card or credit card information increases the popularity of e-commerce and is an important part. This paper provides limited information and is necessary for transferring money by online transactions by securing data and trust of customers. Facial recognition technology identifies a person's information through a digital image. It is automatically determined. It is mainly used in security systems. It matches facial recognition from different angles. It is mainly used in airports. It will recognize the face and we can avoid some unwanted fraud by using the facial recognition system. The fundamental gain of face popularity is used for fraud restrict and crime controlling motive due to the fact face pictures which have been archived and recorded, on the way to assist us to perceive someone later. Facial recognition identifies each distinct skin tone on the surface of a human face, such as curves on cheeks, eyes and nostrils, and more. The technology can also be used in very dark conditions and prevent identity theft.

A study on the identity theft detection model in MMORPGs

Abstract: As game item trading becomes more popular with the rapid growth of online game market, the market for trading game items by cash has increased up to KRW 1.6 trillion. Thanks to this active market, it has been easy to turn these items and game money into real money. As a result, some malicious users have often attempted to steal other players` rare and valuable game items by using their account. Therefore, this study proposes a detection model through analysis on these account thieves` behavior in the Massive Multiuser Online Role Playing Game(MMORPG). In case of online game identity theft, the thieves engage in economic activities only with a goal of stealing game items and game money. In this pattern are found particular sequences such as item production, item sales and acquisition of game money. Based on this pattern, this study proposes a detection model. This detection model-based classification revealed 86 percent of accuracy. In addition, trading patterns when online game identity was stolen were analyzed in this study.

Detection and prevention of possible unauthorized login attempts through stolen credentials from a phishing attack in an online banking system

Abstract: With the current technological expansions customers wish to use online banking facilities due to its convenience and worldwide accessibility. The main challenge of going online for a bank is to provide sufficient security for the online customers and their accounts. The dramatic growth of the number of online banking customers has attracted cyber criminals and identity theft is a severe threat to online banking services. Phishing is a famous and easiest method to steal user credential of online customers where the sole intention is to obtain confidential information for the purpose of monetary gain. In such a situation the main purpose of this research paper is to analysis the usage of phishing attacks and the dangers it poses to customers and the bank, then to find out the available methods to detect and prevent unauthorized login attempts, the technologies and security weaknesses of those methods and finally to propose a solution to detect and prevent unauthorized login attempts using behavioral based analysis, IP and device identification technologies.

An Investigation of Using Time and Ambient Conditions to Sense the Unexpected Removal of RFID Tag

Abstract: The unexpected RFID tag removal is a severe problem to RFID-based information system. It can result in erroneous asset identification, mismatched item-level information, and such security threats as impersonation or identity theft. However, only very few scholars and practitioners have ever carefully investigated this problem and managed to solve it. On the other hand, many firms are going to tag their overall assets, products, etc. with RFID tags, but they are currently either clueless about the problem or limited in the choices for solving it. This study presents a solution prototype of integrating time and ambient conditions to sense the RFID tag unexpected removal in an autonomous and secured way.

Presentation-Level Privacy Protection Techniques for Automated Face Recognition - A Survey

Abstract: The use of Biometric Facial Recognition (FR) Systems have become increasingly widespread, especially since the advent of deep neural network-based architectures (DNNs). Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This paper discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.