Identity theft

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

Survey results on adults and cybersecurity education

Abstract: Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat eduction seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring the online domain. However, seminars do not seem to be a priority as many individuals were only willing to spend 1-1.5h on seminars.

Malicious Bots: An Inside Look into the Cyber-Criminal Underground of the Internet

Abstract: Originally designed as neutral entities, computerized bots are increasingly being used maliciously by online criminals in mass spamming events, fraud, extortion, identity theft, and software theft. Malicious Bots: An Inside Look into the Cyber-Criminal Underground of the Internet explores the rise of dangerous bots and exposes the nefarious methods of "botmasters". This valuable resource assists information security managers in understanding the scope, sophistication, and criminal uses of bots. With sufficient technical detail to empower IT professionals, this volume provides in-depth coverage of the top bot attacks against financial and government networks over the last several years. The book presents exclusive details of the operation of the notorious Thr34t Krew, one of the most malicious bot herder groups in recent history. Largely unidentified by anti-virus companies, their bots spread globally for months, launching massive distributed denial of service (DDoS) attacks and warez (stolen software distributions). For the first time, this story is publicly revealed, showing how the botherders got arrested, along with details on other bots in the world today. Unique descriptions of the criminal marketplace - how criminals make money off of your computer - are also a focus of this exclusive book! With unprecedented detail, the book goes on to explain step-by-step how a hacker launches a botnet attack, providing specifics that only those entrenched in the cyber-crime investigation world could possibly offer. Authors Ken Dunham and Jim Melnick serve on the front line of critical cyber-attacks and countermeasures as experts in the deployment of geopolitical and technical bots. Their work involves advising upper-level government officials and executives who control some of the largest networks in the world. By examining the methods of Internet predators, information security managers will be better able to proactively protect their own networks from such attacks.

Do Data Breach Disclosure Laws Reduce Identity Theft

Abstract: In the United States, identity theft resulted in corporate and consumer losses of $56 billion dollars in 2005, with up to 35 percent of known identity thefts caused by corporate data breaches. Many states have responded by adopting “data breach disclosure laws” that require firms to notify consumers if their personal information has been lost or stolen. While the laws are expected to reduce identity theft, their effect has yet to be empirically measured. We use panel data from the U.S. Federal Trade Commission to estimate the impact of data breach disclosure laws on identity theft from 2002 to 2009. We find that adoption of data breach disclosure laws reduce identity theft caused by data breaches by 6.1 percent, on average.

Novel Solution Based on Face Recognition to Address Identity Theft and Cheating in Online Examination Systems

Abstract: The main objective of this research is to provide a solution for online exam systems by using face recognition to authenticate learners for attending an online exam. More importantly, the system continuously (with short time intervals), checks for learner identity during the whole exam period to ensure that the learner who started the exam is the same one who continued until the end and prevent the possibility of cheating by looking at adjacent PC or reading from an external paper. The system will issue an early warning to the learners if suspicious behavior has been noticed by the system. The proposed system has been presented to eight e-learning instructors and experts in addition to 32 students to gather feedback and to study the impact and the benefit of such system in e-learning environment.