Framework for Security and Privacy in RFID based Telematics

Abstract

Telematics by its nature requires the capture of sensor data, storage and exchange of data to obtain remote servicesMost of the commercial antivirus software fail to detect unknown and new malicious code. Proliferation of malicious code (viruses, worms, Trojans, root kits, spyware, crime ware, phishing attacks, and other malware designed to infiltrate or damage a system without user's consent) in recent years has presented a serious threat to Internet, individual users, and enterprises alike. In addition malware once confined to wired networks has now found a new breeding ground in mobile devices, automatic identification and collection (AIDC) technologies, and radio frequency identification devices (RFID) that use wireless networks to communicate and connect to the Internet. RFID systems encountered a number of threats and privacy issues. In order to stay ahead and be proactive in an asymmetric race against malicious code writers, developers of anti-malware technologies have to rely on automatic malware analysis tools. In this paper, we introduce a method of functionally classifying malware and malicious code by using well-known computational intelligent techniques. MEDiC (Malware Examiner using Disassembled Code) is our answer to a more accurate malware detection method. This work is an also attempt to address the information security issues chiefly the attacks through the databases that these RFID tags called iCLASS, which are of the active type. After a particular malicious code has been first identified, it can be analyzed to extract the signature, which provides a basis for detecting variants and mutants of the same malware in the future.