Anomaly Detection in Cloud Based Application using System Calls

Marin Aranitasi; Mats Neovius

Anomaly Detection in Cloud Based Application using System Calls

Marin Aranitasi, Mats Neovius

Forskningsoutput: Kapitel i bok/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

Sammanfattning

Cloud computing is a rapidly developing computing paradigm. It enables dynamic on-demand resource distribution computing in a cost-effective manner. However, it introduces compelling concerns related to privacy and security of the data. As many of these have been extensively studied and are monitored effectively, this paper proposes a novel solution relying on detecting anomalies in system calls behavior of the system. We use Dempster-Shafer theory of evidence for learning the normality and show how to parametrize this in the method presented. The method is scalable to any set of system calls. Finally, we propose further challenges on this track.

Originalspråk	Odefinierat/okänt
Titel på värdpublikation	CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization
Redaktörer	Westphall Carlos Becker, Lee Yong Woo, Duncan Bob, Olmsted Aspen, Vassilakopoulos Michael, Lambrinoudakis Costas, Katsikas Sokratis K., Ege Raimund
Förlag	Iaria xps press
Sidor	44–48
ISBN (tryckt)	978-1-61208-529-6
Status	Publicerad - 2017
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	International Conference on Cloud Computing, GRIDs, and Virtualization - Eighth International Conference on Cloud Computing, GRIDs, and Virtualization Varaktighet: 19 feb. 2017 → 23 feb. 2017

Konferens

Konferens	International Conference on Cloud Computing, GRIDs, and Virtualization
Period	19/02/17 → 23/02/17

Nyckelord

Cloud computing
Information Security
Kernel methods

ADVICeS: Adaptive Integrated Formal Design of Safety-Critical Systems (Academy of Finland)
Walden, M. (Ansvarig forskare), Olszewska, M. (CoI), Edmunds, A. (CoI), Ostroumov, S. (CoI), Petre, L. (CoI), Boström, P. (CoI) & Neovius, M. (CoI)
01/09/13 → 31/08/17
Projekt: Finlands Akademi/Övriga Forskningsråd

Citera det här

Aranitasi, Marin ; Neovius, Mats. / Anomaly Detection in Cloud Based Application using System Calls. CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization. redaktör / Westphall Carlos Becker ; Lee Yong Woo ; Duncan Bob ; Olmsted Aspen ; Vassilakopoulos Michael ; Lambrinoudakis Costas ; Katsikas Sokratis K. ; Ege Raimund. Iaria xps press, 2017. s. 44–48

@inproceedings{486fcd1a45834ee68cf3b02548148ebd,

title = "Anomaly Detection in Cloud Based Application using System Calls",

abstract = "Cloud computing is a rapidly developing computing paradigm. It enables dynamic on-demand resource distribution computing in a cost-effective manner. However, it introduces compelling concerns related to privacy and security of the data. As many of these have been extensively studied and are monitored effectively, this paper proposes a novel solution relying on detecting anomalies in system calls behavior of the system. We use Dempster-Shafer theory of evidence for learning the normality and show how to parametrize this in the method presented. The method is scalable to any set of system calls. Finally, we propose further challenges on this track.",

keywords = "Cloud computing, Information Security, Kernel methods, Cloud computing, Information Security, Kernel methods, Cloud computing, Information Security, Kernel methods",

author = "Marin Aranitasi and Mats Neovius",

year = "2017",

language = "Odefinierat/ok{\"a}nt",

isbn = "978-1-61208-529-6",

pages = "44–48",

editor = "{Carlos Becker}, Westphall and {Yong Woo}, Lee and Duncan Bob and Olmsted Aspen and Vassilakopoulos Michael and Lambrinoudakis Costas and K., {Katsikas Sokratis} and Ege Raimund",

booktitle = "CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization",

publisher = "Iaria xps press",

note = "International Conference on Cloud Computing, GRIDs, and Virtualization ; Conference date: 19-02-2017 Through 23-02-2017",

}

Aranitasi, M & Neovius, M 2017, Anomaly Detection in Cloud Based Application using System Calls. i W Carlos Becker, L Yong Woo, D Bob, O Aspen, V Michael, L Costas, KS K. & E Raimund (red), CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization. Iaria xps press, s. 44–48, International Conference on Cloud Computing, GRIDs, and Virtualization, 19/02/17.

Anomaly Detection in Cloud Based Application using System Calls. / Aranitasi, Marin; Neovius, Mats.
CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization. red. / Westphall Carlos Becker; Lee Yong Woo; Duncan Bob; Olmsted Aspen; Vassilakopoulos Michael; Lambrinoudakis Costas; Katsikas Sokratis K.; Ege Raimund. Iaria xps press, 2017. s. 44–48.

Forskningsoutput: Kapitel i bok/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

TY - GEN

T1 - Anomaly Detection in Cloud Based Application using System Calls

AU - Aranitasi, Marin

AU - Neovius, Mats

PY - 2017

Y1 - 2017

N2 - Cloud computing is a rapidly developing computing paradigm. It enables dynamic on-demand resource distribution computing in a cost-effective manner. However, it introduces compelling concerns related to privacy and security of the data. As many of these have been extensively studied and are monitored effectively, this paper proposes a novel solution relying on detecting anomalies in system calls behavior of the system. We use Dempster-Shafer theory of evidence for learning the normality and show how to parametrize this in the method presented. The method is scalable to any set of system calls. Finally, we propose further challenges on this track.

AB - Cloud computing is a rapidly developing computing paradigm. It enables dynamic on-demand resource distribution computing in a cost-effective manner. However, it introduces compelling concerns related to privacy and security of the data. As many of these have been extensively studied and are monitored effectively, this paper proposes a novel solution relying on detecting anomalies in system calls behavior of the system. We use Dempster-Shafer theory of evidence for learning the normality and show how to parametrize this in the method presented. The method is scalable to any set of system calls. Finally, we propose further challenges on this track.

KW - Cloud computing

KW - Information Security

KW - Kernel methods

KW - Cloud computing

KW - Information Security

KW - Kernel methods

KW - Cloud computing

KW - Information Security

KW - Kernel methods

M3 - Konferensbidrag

SN - 978-1-61208-529-6

SP - 44

EP - 48

BT - CLOUD COMPUTING 2017 The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization

A2 - Carlos Becker, Westphall

A2 - Yong Woo, Lee

A2 - Bob, Duncan

A2 - Aspen, Olmsted

A2 - Michael, Vassilakopoulos

A2 - Costas, Lambrinoudakis

A2 - K., Katsikas Sokratis

A2 - Raimund, Ege

PB - Iaria xps press

T2 - International Conference on Cloud Computing, GRIDs, and Virtualization

Y2 - 19 February 2017 through 23 February 2017

ER -

Anomaly Detection in Cloud Based Application using System Calls

Sammanfattning

Konferens

Nyckelord

Projekt

ADVICeS: Adaptive Integrated Formal Design of Safety-Critical Systems (Academy of Finland)

Citera det här