Abstract
In this paper, we describe REAL: An efficient Read Aligner for next generation sequencing reads structures to detect and compare the results of web spambots and Viruses. Email spam, also known as junk email or unsolicited bulk email (UBE), is a subset of electronic spam involving nearly identical messages sent to numerous recipients by email. In the last decade or so, Web spam has emerged to be a bigger than previous thought problem. It not only wastes resources, misleads people but also has the ability to trick search algorithms to gain unfair search result ranking, hence resulting in the decrease of quality and reliability of the World Wide Web (WWW) and its content.
The Internet brings a new dimension to the virus problem. Before, viruses generally spread from system to system on physical media, often the floppy disk. This is a fundamentally slow way for viruses to spread. The Internet changes all this. The viruses that really win in the Internet environment are the macro viruses. They are attached to data, not code, making them harder to avoid. An increasing number of documents on the Net are available as Word files, for example, with no alternative format, and Word documents are frequently exchanged via email.
Our experimental results show that the proposed system is successful for on-the-fly classification of web spambots and computer viruses hence eliminating spam in web 2.0 applications and detecting infected files in computers. Our comparison shows it is slightly harder to detect viruses due to nature of the complexity and especially if they have an executable packing to dodge antivirus engines.