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Feature trade-off analysis for reconnaissance detection.

Kalutarage, Harsha Kumara; Shaikh, Siraj Ahmed


Siraj Ahmed Shaikh


Nick Heard

Niall Adams

Patrick Rubin-Delanchy

Melissa Turcotte


An effective cyber early warning system (CEWS) should pick up threat activity at an early stage, with an emphasis on establishing hypotheses and predictions as well as generating alerts on (unclassified) situations based on preliminary indications. The design and implementation of such early warning systems involve numerous challenges such as generic set of indicators, intelligence gathering, uncertainty reasoning and information fusion. This chapter begins with an understanding of the behaviours of intruders and then related literature is followed by the proposed methodology using a Bayesian inference-based system. It also includes a carefully deployed empirical analysis on a data set labelled for reconnaissance activity. Finally, the chapter concludes with a discussion on results, research challenges and necessary suggestions to move forward in this research line.


KALUTARAGE, H.K. and SHAIKH, S.A. 2018. Feature trade-off analysis for reconnaissance detection. In Heard, N., Adams, N., Rubin-Delanchy, P. and Turcotte, M. (eds.) Data science for cyber security. Security science and technology, 3. London: World Scientific [online], chapter 5, pages 95-126. Available from:

Acceptance Date Oct 8, 2018
Online Publication Date Nov 30, 2018
Publication Date Nov 30, 2018
Deposit Date Sep 1, 2020
Publicly Available Date Sep 7, 2020
Publisher World Scientific Publishing
Pages 95-126
Series Title Security science and technology
Series Number 3
Series ISSN 2059-1063
Book Title Data science for cyber-security
Chapter Number Chapter 5
ISBN 9781786345639
Keywords Cyber early warning system; Intruders; Behaviours; Threat; Reconnaissance
Public URL


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