By Ying Tan

This booklet offers with malware detection when it comes to synthetic Immune process (AIS), and provides a few AIS types and immune-based function extraction techniques in addition to their functions in computing device security

  • Covers the entire present achievements in computing device protection in keeping with immune rules, which have been bought via the Computational Intelligence Laboratory of Peking college, China
  • Includes state of the art details on designing and constructing man made immune platforms (AIS) and AIS-based ideas to laptop safety issues
  • Presents new options similar to immune risk thought, immune concentration,  and class-wise details achieve (CIG) 

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Extra info for Artificial Immune System: Applications in Computer Security

Example text

Artificial immune systems have been successfully applied to many practical fields, including computer security, optimization, fault diagnosis, and pattern recognition, to name a few. In particular, computer malware detection based on immune principles has been developed rapidly and achieved many fruitful results and achievements, attracting more and more researchers. Nevertheless, these artifi­ cial immune systems and malware detection methods are not perfect. Most of them have some deficiencies and shortcomings, which stimulates researchers to explore more efficient models and algorithms.

1 2 Chapter 1 Artificial Immune System distribution. We believe that the features of the immune system are the roots and original springs for us to build perfect computer security systems. 1 Overview Biological immune system (BIS) is a highly complex, distributed, and parallel natu­ ral system with multiple levels, which can identify the self, exclude the nonself, for maintaining security and stability in the biological environment. It makes use of innate immunity and adaptive immunity to generate accurate immune response against the invading antigens.

And Jiao, L. (2004) Feature selection based on immune clonal selection algorithm, Journal of Fudan University (Natural Science), 43 (5), 926–929. (in Chinese) 11. Jiao, L. and Du, H. (2003) Development and prospect of the artificial immune system. Acta Electron­ ica Sinica, 31 (10), 1540–1548. (in Chinese) 12. Ji, Z. and Dasgupta, D. (2007) Revisiting negative selection algorithms. Evolutionary Computation, 15 (2), 223–251. 13. Dasgupta, D. and González, F. (2002) An immunity-based technique to characterize intrusions in computer networks.

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