Detecting Slow DDos Attacks on Mobile Devices

Date
2016-12-11
Authors
Cusack, B
Lutui, R
Khaleghparast, R
Supervisor
Item type
Conference Contribution
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Australasian Conference on Information Systems (ACIS)
Abstract

Denial of service attacks, distributed denial of service attacks and reflector attacks are well known and documented events. More recently these attacks have been directed at game stations and mobile communication devices as strategies for disrupting communication. In this paper we ask, How can slow DDos attacks be detected? The similarity metric is adopted and applied for potential application. A short review of previous literature on attacks and prevention methodologies is provided and strategies are discussed. An innovative attack detection method is introduced and the processes and procedures are summarized into an investigation process model. The advantages and benefits of applying the metric are demonstrated and the importance of trace back preparation discussed.


Denial of service attacks, distributed denial of service attacks and reflector attacks are well known and documented events. More recently these attacks have been directed at game stations and mobile communication devices as strategies for disrupting communication. In this paper we ask, How can slow DDos attacks be detected? The similarity metric is adopted and applied for potential application. A short review of previous literature on attacks and prevention methodologies is provided and strategies are discussed. An innovative attack detection method is introduced and the processes and procedures are summarized into an investigation process model. The advantages and benefits of applying the metric are demonstrated and the importance of trace back preparation discussed.

Description
Keywords
Slow DDoS; Detection; Mobile Devices; Metrics
Source
Proceedings of the 27th Australasian Conference on Information Systems (ACIS2016), University of Wollongong Faculty of Business, 2016.
DOI
Rights statement
© 2016 authors. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Australia License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original authors and ACIS are credited.