A Memory-Based Approach to Anti-Spam Filtering for Mailing Lists
Information Retrieval
Content Based File Type Detection Algorithms
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 9 - Volume 9
Computer and Intrusion Forensics
Computer and Intrusion Forensics
Identification and Localization of Data Types within Large-Scale File Systems
SADFE '07 Proceedings of the Second International Workshop on Systematic Approaches to Digital Forensic Engineering
Statistical Disk Cluster Classification for File Carving
IAS '07 Proceedings of the Third International Symposium on Information Assurance and Security
SÁDI - Statistical Analysis for Data Type Identification
SADFE '08 Proceedings of the 2008 Third International Workshop on Systematic Approaches to Digital Forensic Engineering
On Improving the Accuracy and Performance of Content-Based File Type Identification
ACISP '09 Proceedings of the 14th Australasian Conference on Information Security and Privacy
File Fragment Classification-The Case for Specialized Approaches
SADFE '09 Proceedings of the 2009 Fourth International IEEE Workshop on Systematic Approaches to Digital Forensic Engineering
Proceedings of the 2010 ACM Symposium on Applied Computing
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
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With the everyday increasing importance of privacy, security, and wise use of computational resources, the corresponding technologies are increasingly being faced with the problem of file type detection. In digital forensic, there are numerous file formats in use. Criminals have started using either non-standard file formats or changing extensions of files while storing or transmitting them over a network. This makes recovering data out of these files difficult. An extension to the file name with the file type is stored in the disk directory, but when a file is deleted, the entry for the file in the directory may be overwritten and hence quite difficult to identify its type which is serious issue in computer forensics. But if the fragment of file has its header information containing type identifying information the mentioned problem may be solved. But it is difficult to identify the type of fragment from the middle or if the header information is deleted or unavailable the identification becomes more complex. This paper focuses on identifying the file types addressing the various scenarios of file type being changed by the malicious user to send some confidential or sensitive information by changing the file type (say.exe banned by Gmail can be converted to any acceptable format and sent across). E-mail spam has become an epidemic problem that can negatively affect the usability of electronic mail as a communication means. Besides wasting users' time and effort to scan and delete the massive amount of junk e-mails received, it consumes network bandwidth and storage space, slows down email servers, and provides a medium to distribute harmful and/or offensive content. Inspired by the success of fuzzy similarity in text classification and document retrieval, the approach investigates its effectiveness in filtering spam based on the textual content of e-mail messages.