Identity theft

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

Detection of Peer-to-Peer Botnet Using Machine Learning Techniques and Ensemble Learning Algorithm

Abstract: Peer-to-peer (P2P) botnet is one of the greatest threats to digital data. It has become a common tool for performing a lot of malicious activities such as DDoS attacks, phishing attacks, spreading spam, identity theft, ransomware, extortion attack, and many other fraudulent activities. P2P botnets are very resilient and stealthy and keep mutating to evade security mechanisms. Therefore, it has become necessary to identify and detect botnet flow from the normal flow. This paper uses supervised machine learning algorithms to detect P2P botnet flow. This paper also uses an ensemble learning technique to combine the performances of various supervised machine learning models to make predictions. To validate the results, four performance metrics have been used. These are accuracy, precision, recall, and F1-score. Experimental results show that the proposed approach delivers 99.99% accuracy, 99.81% precision, 99.11% recall, and 99.32% F1 score, which outperform the previous botnet detection approaches.

Anonymous Identity Authentication scheme for Internet of Vehicles based on moving target Defense

Abstract: As one of the effective methods to enhance traffic safety and improve traffic efficiency, the Internet of vehicles has attracted wide attention from all walks of life. V2X secure communication, as one of the research hotspots of the Internet of vehicles, also has many security and privacy problems. Attackers can use these vulnerabilities to obtain vehicle identity information and location information, and can also attack vehicles through camouflage.Therefore, the identity authentication process in vehicle network communication must be effectively protected. The anonymous identity authentication scheme based on moving target defense proposed in this paper not only ensures the authenticity and integrity of information sources, but also avoids the disclosure of vehicle identity information.

Identity verification system

Abstract: A computerized and networked system protects individuals against identity theft without the need to disclose the detailed personal information of the individuals Furthermore, the system helps prevent loss and damage to consumers, financial institutions and merchants caused by financial crimes related to identity theft In addition, users can conduct payments in a secure manner without the need to use any traditional financial instrument A pass code can be generated for each transaction and sent to a user's personal communications device When the correct pass code is received from the user, the transaction is then authorized

On Identity Theft Prevention and Control of the Legal System

Abstract: In this paper,the author analyzes the concept of identity theft,lists the main means of identity theft in the second part of the article.The author describes the hazards of identity theft in the third part of the article and how to set up identity theft prevention and treatment of the legal system in the last part of the article.