Bio-Inspired Cyber Security for Communications and Networking

Wojciech Mazurczyk , Sean Moore , Erin W. Fulp , Hiroshi Wada , Kenji Leibnitz


Nature is Earth's most amazing invention machine for solving problems and adapting to significant environmental changes. Its ability to address complex, large-scale problems with robust, adaptable, and efficient solutions results from many years of selection, genetic drift, and mutations. Thus, it is not surprising that inventors and researchers often look to natural systems for inspiration and methods to solve problems in human-created artificial environments. This has resulted in the development of evolutionary algorithms including genetic algorithms and swarm algorithms, and of classifier and pattern detection algorithms, such as neural networks, for addressing hard computational problems.
Author Wojciech Mazurczyk (FEIT / IT)
Wojciech Mazurczyk,,
- The Institute of Telecommunications
, Sean Moore - [Centripetal Networks]
Sean Moore,,
- Centripetal Networks
, Erin W. Fulp - [Wake Forest University (WFU)]
Erin W. Fulp,,
- Wake Forest University
, Hiroshi Wada - [University of Massachusetts (UMASS)]
Hiroshi Wada,,
- University of Massachusetts
, Kenji Leibnitz - [Osaka University]
Kenji Leibnitz,,
- Osaka University
Journal seriesIEEE Communications Magazine, ISSN 0163-6804
Issue year2016
Publication size in sheets0.3
Keywords in EnglishSpecial issues and sections, Biological system modeling, Machine learning, Communication networks, Wireless sensor networks, Particle swarm optimization, Computer security
ASJC Classification2208 Electrical and Electronic Engineering; 1705 Computer Networks and Communications; 1706 Computer Science Applications
ProjectThe Develpment of Digital Communicatios. Project leader: Siuzdak Jerzy, , Phone: +48 22 234-7868, start date 27-04-2015, end date 31-12-2016, IT/2015/statut, Completed
WEiTI Działalność statutowa
Languageen angielski
2016 Mazurczyk Bio-Inspired Cyber Security for Communications and Networking.pdf 519.91 KB
Score (nominal)45
Score sourcejournalList
ScoreMinisterial score = 45.0, 02-02-2020, ArticleFromJournal
Ministerial score (2013-2016) = 45.0, 02-02-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus Citations = 2; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 4.768; WoS Impact Factor: 2016 = 10.435 (2) - 2016=9.119 (5)
Citation count*2 (2020-08-07)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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