Identity theft

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

Quantifying e-risk for Cyber-insurance Using Logit and Probit Models

Abstract:  Abstract—The common e-threats deterring ecommerce are identity theft, hacking, virus attack, graffiti, phishing, Denial-of- Service (DoS), sabotage by disgruntled employees, loss of laptop, financial fraud and telecom driven frauds. These threats discourage users from online transactions. Organizations spend millions of dollars to implement the latest perimeter and core security technologies, to deter malicious attackers and to ensure confidentiality, integrity and availability of data. Yet, security breaches are common, resulting in loss of opportunity cost, market capitalization and brand equity for organizations. We propose e-risk insurance as a strategy to supplement the security technologies, and to mitigate these financial losses. In this paper, we propose two generalized linear models (GLM) namely Logit and Probit for quantification of the probability of an e-threat, using CSI/FBI data. We also compute the expected loss amount for organizations using collective risk model. Based on it, we ascertain the net premium to be accrued to the insurance companies.

Anomaly Recognition in Online Social Networks

Abstract: The popularity of social networking sites has increased throughout the decade and everything that gains immense popularity with great human involvement also brings many challenges and issues along with it. Similarly the excessive use of online social networking causes a great increase in anomalies. In social networking the anomalies are like fake account, account hack, identity theft, spams and many other illegitimate activities. It is thus necessary to detect such anomalous and suspicious behavior of any user at these social platforms, as they could have an adverse impact on users, especially on teenagers. In this paper, we propose various methodologies for early detection of suspicious and anomalous activities. We have done the analysis of various parameters of social networking and its graph like indegree, outdegree, active time of a node (user) and its behavior.

Security threats to social media technologies

Abstract: This chapter begins by discussing what security means. There must be objectives that one wishes to attain and security controls are utilized to realize them. Some public service organizations, such as government departments, are continuously under attack. The chapter outlines the security threats that social media sites are particularly susceptible to, which will enable readers to appreciate the importance of having robust security measures. Social engineering and associated problems such as handling unsolicited messages (opening files, hyperlinks, and problems associated with communicating with strangers) are also described. The topic of “trust” is discussed, and this does not just include trust in one’s communication with strangers. There could be legal and regulatory ramifications of not trying to combat risks. Risks include identity theft, malware, and damage to a public service department’s reputation. All manner of erroneous communication could take place. One also needs to be aware of privacy concerns associated with using web applications within social media sites.

Detection and Prevention of Profile Cloning in Online Social Networks

Abstract: In today's world, online social networking sites are becoming quite popular. They influence the way people communicate with each other. Social Sites like Facebook, Twitter, LinkedIn, and Google have tens or hundreds of millions of users across the globe that generates billions of personal data content. With such a huge amount of data available there is always a fear of this data being stolen or misused by some kind of adversaries or attackers. Hence such huge amount of data generates security and privacy threats to the users worldwide. These can be Identity Theft Attack (profile cloning) or may be some kind of Malware Attacks or Structural Attacks. Profile cloning is a kind of stealing identity of existing user to duplicate or to create a duplicate profile of a user using these credentials. In this paper an attempt has been made to propose a methodology for detection of profile cloning in various social networks. Also, we tried to suggest some measures that can be followed by the users and OSN providers to protect the users from these kinds of attacks.