Anti-spam techniques based on artificial immune system by Ying Tan

By Ying Tan

Email has turn into an crucial conversation device in lifestyle. even if, excessive volumes of unsolicited mail waste assets, intrude with productiveness, and current critical threats to machine procedure safeguard and private privateness. This ebook introduces study on anti-spam suggestions according to the substitute immune procedure (AIS) to spot and clear out junk mail. It presents a unmarried resource of all anti-spam types and algorithms in line with the AIS which have been proposed by means of the writer for the previous decade in a variety of journals and conferences.

Inspired by way of the organic immune process, the AIS is an adaptive approach according to theoretical immunology and saw immune capabilities, rules, and types for challenge fixing. one of the number of anti-spam recommendations, the AIS has been powerful and is changing into some of the most very important how you can clear out unsolicited mail. The publication additionally specializes in numerous key subject matters relating to the AIS, including:

  • Extraction equipment encouraged by way of a variety of immune principles
  • Construction techniques in response to numerous focus equipment and models
  • Classifiers in response to immune chance theory
  • The immune-based dynamic updating algorithm
  • Implementing AIS-based unsolicited mail filtering systems

The booklet additionally contains numerous experiments and comparisons with state of the art anti-spam ideas to demonstrate the wonderful functionality AIS-based anti-spam techniques.

Anti-Spam strategies according to synthetic Immune System

provides practitioners, researchers, and teachers a centralized resource of particular details on effective types and algorithms of AIS-based anti-spam concepts. It additionally comprises the most up-tp-date details at the basic achievements of anti-spam examine and techniques, outlining innovations for designing and utilizing spam-filtering models.

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The regional similarity of a spam image is high, while the spam images have color heterogeneity. The color saturation of spam images differs from that of 12 ■ Anti-Spam Techniques Based on Artificial Immune Systems the normal images [83]. , as well as three types of normal images: photograph, map, and comic. Reference [130] pointed out that the smoothness of color distribution of spam images is not as good as normal images, because the spam images are generally synthetic and contain clear and sharp objects.

They propose a space-time evaluation method by combining spatial characteristics and historical data, whose error rate is half lower than that of traditional IP blacklist filtering. Ramachandran and Feamster [150] study the characteristics of network behavior during the sending process of spam, and they specifically analyze the distribution of IP addresses that send spam, situation of BGP (Border Gateway Protocol) routing hijack, persistency of spam sending hosts and characteristics of spam botnets.

213] extract edge features by using color-based edge detection method and corner information of character edge is also extracted in their work. Edges of characters and other objects are distinguished according to the corner information and width and height of the edges. Liu et al. [122] detect spam images through combining the text area features, which are edge information and corner information, and the color features. 4 OCR-Based Features Fumera et al. [72] extract the text information in images by using Optical Character Recognition (OCR), and the text information is further processed by adopting the text-based approaches.

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