Identity theft

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

Petty theft: criminological characteristics of the identity of the criminal

Abstract: The proposed article examines the social conditionality of petty theft. Social conditionality is revealed through the analysis of the historical aspect, legislation of the Soviet and modern period. The study is aimed at determining the criminological characteristics of persons committing petty theft. Petty thefts are mostly committed for a selfish purpose, but they can also be committed «for the sake of inter-est». The criminological characteristics of persons committing petty theft formulated in the article provide an opportunity to determine the motivation for committing illegal acts, as well as the peculiarities of behavior in preparation, commission of petty theft and after it.

Looking into the Crystal Ball

Abstract: If we had a crystal ball, what would it show for the future of identity management? As the swirling mists parted in our all-seeing globe, we believe it would undoubtedly show identity management becoming increasingly necessary in the future for several reasons. First, it is unlikely that hackers will stop hacking, which means we’ll continue to need security measures to protect against increasingly diverse and potentially more automated threats. At the same time, there will be many innovative new services and devices that will be beneficial in our lives, but they’ll need adequate identity management to reduce the risk of them being used against us. We’ll also see a rise in autonomous entities requiring identification, authentication, and authorization just like humans. The notion of identity will need to spread from humans to all manner of devices, agents, and robots acting on our behalf, and such entities will need identity management as part of their defenses against malicious attacks. In addition, the Covid-19 pandemic has greatly increased the number of employees working from home or other locations outside the corporate network. This has accelerated a shift from older enterprise security models that depended on a network perimeter to a different approach, based on Zero Trust principles, that relies more heavily on identity and access management to control access to digital resources that reside both within and outside a corporate network. For all these reasons, the need for identity management in the future will be more important than ever before, and we’ll need to find ways to make it easier to implement and manage effectively.

Augmenting the detection of online image theft using diagonal transformation and iris biometric watermarking

Abstract: The digitisation of data has brought in various social media platforms where a lot of data are compromised every day. Likewise, there is a possibility of theft for every photo published online. Hence, the research work proposes an image theft detection technique where biometric traits of the owner of the photo, are embedded into the image. This helps to prove rightful ownership in case of any ownership disputes on the image. The proposed architecture identifies the rightful owner by comparing the embedded traits from the claimed image with that of the person asserting ownership. The watermark imperceptibility is analysed and robustness against various attacks is proven. Also, the accuracy of the work is analysed in terms of the false acceptance rate and false rejection rate. By considering iris images taken from CASIA, and IIT-Delhi databases, the proposed approach achieved a better accuracy rate with a very low FAR and FRR.

Investigation on Privacy Hazards in Social Area Network

Abstract: The Social Area networking Platform (SANP) is a rapidly developing technology that allows users to meet friends, family, and others, who share their interests and express their personal feelings. The potential privacy threats include, Paedophilia, identity theft, spoofing, data breaches, the Koobface worm, phishing, and evil twin attacks. These attacks are major threat to user privacy information. Many people are not aware of the risks of impersonation. To avoid this, it is necessary to understand social network privacy concerns. This scenario includes a study of social network privacy concerns, as well as hazards and risks from recent events. This study significantly contributes to the classification of dangers and categorization of frauds relevant to social networks. Following the completion of a comprehensive research study of privacy concerns in SANP, optimized techniques were identified and performance for privacy threats was also evaluated. The proposed system has used Euclidean distance to evaluate the dataset based on privacy threats. It will be useful in establishing trustworthiness on social media.

Managing Data Protection and Privacy on Cloud

Abstract: When pandemic rose in 2020, people were fighting against COVID-19 virus and organizations had accelerated their digitization and cloud adoption rapidly (De et al. in Int J Inf Manag 55:102171, 2020 [1]) to meet the online based business during the lockdown. This chaos helped fraudsters and attackers taking advantage of the momentary lack of security controls and oversight. Federal Investigation Bureau (FBI) Internet Crime Compliant Center (IC3) 2020 reported highest number of complaints in 2020 (791 k + ) compared to prior five years (298 k + in 2016), with peak losses reported ($4.2 Billion in 2020 compared to $1.5 Billion in 2016) (Internet Crime Complaint Center in Internet crime report. Federal Bureau of Investigation, Washington, D.C., 2020 [2]). Majority of these incidents were connected to financial fraud, identity fraud, and phishing for personally identifiable information (PII). Considering the severity and impact of personal data exposure over cloud and hybrid environment, this paper provides a brief overview of prior research and discuss technical solutions to protect data across heterogeneous environments and ensure privacy regulations.