Detecting Slow DDos Attacks on Mobile Devices

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aut.relation.conferenceThe 27th Australasian Conference on Information Systemsen_NZ
aut.researcherCusack, Brian
dc.contributor.authorCusack, Ben_NZ
dc.contributor.authorLutui, Ren_NZ
dc.contributor.authorKhaleghparast, Ren_NZ
dc.contributor.editorGregor, Sen_NZ
dc.date.accessioned2019-04-04T04:26:13Z
dc.date.available2019-04-04T04:26:13Z
dc.date.copyright2016-12-11en_NZ
dc.date.issued2016-12-11en_NZ
dc.description.abstractDenial 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.en_NZ
dc.description.abstractDenial 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.
dc.identifier.citationProceedings of the 27th Australasian Conference on Information Systems (ACIS2016), University of Wollongong Faculty of Business, 2016.
dc.identifier.urihttps://hdl.handle.net/10292/12417
dc.publisherAustralasian Conference on Information Systems (ACIS)
dc.relation.urihttps://ro.uow.edu.au/acis2016/papers/1/57/
dc.rights© 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.
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectSlow DDoS; Detection; Mobile Devices; Metrics
dc.titleDetecting Slow DDos Attacks on Mobile Devicesen_NZ
dc.typeConference Contribution
pubs.elements-id218456
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Corporate Development & Support Group
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Communication Studies
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF Other DCT
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