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Computer immunology
Open accessAbstract
Natural immune systems protect animals from dangerous foreign pathogens, including bacteria, viruses, parasites, and toxins. Their role in the body is analogous to that of computer security systems in computing. Although there are many differences between living organisms and computers, the similarities are compelling and could point the way to improved computer security. Improvements can be achieved by designing computer immune systems with some of the important properties of natural immune systems, including multilayered protection, highly distributed detector. The computer security problem is difficult. There are many legitimate changes to self, like new users and new programs, and many paths of intrusion, and the periphery of a networked computer is less clearly defined than the periphery of an individual animal. Firewalls attempt to construct such a periphery, often with limited success. As an initial step toward defining self in a realistic computing environment, programmers are developing an intrusion-detection system for networked computers. Discrimination must be based on some characteristic structure that is both compact and universal in the protected system. INSET: A Database of Normal Patterns.
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Cited by
Intrusion detection using sequences of system calls
Hofmeyr, S. A., Forrest, S., & Somayaji, A. (1998) · Journal of Computer Security · doi:10.3233/jcs-980109 · Cited by 1,313
Self-citationUse of K-Nearest Neighbor classifier for intrusion detection
Liao, Y., & Vemuri, V. R. (2002) · Computers & Security · doi:10.1016/s0167-4048(02)00514-x · Cited by 802
An artificial immune system architecture for computer security applications
Harmer, P. K., Williams, P. D., Gunsch, G. H., & Lamont, G. B. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2002.1011540 · Cited by 353
State of the Practice of Intrusion Detection Technologies
Allen, J., Christie, A., Fithen, W., McHugh, J., & Pickel, J. (2000) · doi:10.21236/ada375846 · Cited by 347
Self-healing systems — survey and synthesis
Ghosh, D., Sharman, R., Raghav Rao, H., & Upadhyaya, S. (2007) · Decision Support Systems · doi:10.1016/j.dss.2006.06.011 · Cited by 305
Metadata
- Authors
- Forrest, S., Hofmeyr, S. A., & Somayaji, A.
- Venue
- Communications of the ACM
- Published
- 1997-10
- Volume
- 40
- Issue
- 10
- Pages
- 88-96
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2338717024
- Cited by
- 848
- References
- 0
- FWCI
- 16.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.