How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control

Jarno Salonen; Tatu Niskanen; Pia Raitio

How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control

Jarno Salonen, Tatu Niskanen, Pia Raitio

BA6403 Applied cybersecurity

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

Industry 4.0 and the ongoing digital transformation along with a large number interconnected machines and devices increase the role of cybersecurity, cyber incident handling and incident response in the factories of the future (FoF). Cyber incident information sharing plays a major role when we need to formulate situational pictures about FoF operations and environment, and respond to cybersecurity threats related to e.g. the implementation of novel technologies. Sharing of incident information has a major drawback since it may reveal too much about the attack target, e.g. in the case of legacy systems and therefore restrictions may apply. We have developed a proof-of-concept service that combines access control and encryption of data at high granularity and a mechanism for requesting access to restricted cyber incident information. The objective was to demonstrate how access to restricted incident data fields could be managed in a fine-grained manner to enhance information sharing.

Original language	English
Title of host publication	Data Mining and Machine Learning
Subtitle of host publication	3rd International Conference on Data Mining and Machine Learning (DMML 2022)
Editors	David Wyld, Dhinaharan Nagamalai
Publisher	AIRCC Publishing Corporation
Number of pages	14
Volume	12
Edition	7
ISBN (Electronic)	978-1-925953-66-4
Publication status	Published - 2022
MoE publication type	A4 Article in a conference publication
Event	3rd International Conference on Data Mining and Machine Learning, DMML 2022 - Copenhagen, Denmark Duration: 23 Apr 2022 → 24 Apr 2022

Conference

Conference	3rd International Conference on Data Mining and Machine Learning, DMML 2022
Abbreviated title	DMML 2022
Country/Territory	Denmark
City	Copenhagen
Period	23/04/22 → 24/04/22

Keywords

incident management
visualisation
cybersecurity
information sharing

Access to Document

https://aircconline.com/csit/papers/vol12/csit120717.pdf

SeCoIIA: Secure Collaborative Intelligent Industrial Assets
Salonen, J.
1/12/19 → 31/05/22
Project: EU project

Cite this

Salonen, J., Niskanen, T., & Raitio, P. (2022). How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control. In D. Wyld, & D. Nagamalai (Eds.), Data Mining and Machine Learning: 3rd International Conference on Data Mining and Machine Learning (DMML 2022) (7 ed., Vol. 12). [17] AIRCC Publishing Corporation. https://aircconline.com/csit/papers/vol12/csit120717.pdf

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title = "How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control",

abstract = "Industry 4.0 and the ongoing digital transformation along with a large number interconnected machines and devices increase the role of cybersecurity, cyber incident handling and incident response in the factories of the future (FoF). Cyber incident information sharing plays a major role when we need to formulate situational pictures about FoF operations and environment, and respond to cybersecurity threats related to e.g. the implementation of novel technologies. Sharing of incident information has a major drawback since it may reveal too much about the attack target, e.g. in the case of legacy systems and therefore restrictions may apply. We have developed a proof-of-concept service that combines access control and encryption of data at high granularity and a mechanism for requesting access to restricted cyber incident information. The objective was to demonstrate how access to restricted incident data fields could be managed in a fine-grained manner to enhance information sharing.",

keywords = "incident management, visualisation, cybersecurity, information sharing",

author = "Jarno Salonen and Tatu Niskanen and Pia Raitio",

year = "2022",

language = "English",

volume = "12",

editor = "David Wyld and Dhinaharan Nagamalai",

booktitle = "Data Mining and Machine Learning",

publisher = "AIRCC Publishing Corporation",

address = "India",

edition = "7",

note = "3rd International Conference on Data Mining and Machine Learning, DMML 2022, DMML 2022 ; Conference date: 23-04-2022 Through 24-04-2022",

}

Salonen, J, Niskanen, T & Raitio, P 2022, How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control. in D Wyld & D Nagamalai (eds), Data Mining and Machine Learning: 3rd International Conference on Data Mining and Machine Learning (DMML 2022). 7 edn, vol. 12, 17, AIRCC Publishing Corporation, 3rd International Conference on Data Mining and Machine Learning, DMML 2022, Copenhagen, Denmark, 23/04/22. <https://aircconline.com/csit/papers/vol12/csit120717.pdf>

How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control. / Salonen, Jarno; Niskanen, Tatu; Raitio, Pia.
Data Mining and Machine Learning: 3rd International Conference on Data Mining and Machine Learning (DMML 2022). ed. / David Wyld; Dhinaharan Nagamalai. Vol. 12 7. ed. AIRCC Publishing Corporation, 2022. 17.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control

AU - Salonen, Jarno

AU - Niskanen, Tatu

AU - Raitio, Pia

PY - 2022

Y1 - 2022

N2 - Industry 4.0 and the ongoing digital transformation along with a large number interconnected machines and devices increase the role of cybersecurity, cyber incident handling and incident response in the factories of the future (FoF). Cyber incident information sharing plays a major role when we need to formulate situational pictures about FoF operations and environment, and respond to cybersecurity threats related to e.g. the implementation of novel technologies. Sharing of incident information has a major drawback since it may reveal too much about the attack target, e.g. in the case of legacy systems and therefore restrictions may apply. We have developed a proof-of-concept service that combines access control and encryption of data at high granularity and a mechanism for requesting access to restricted cyber incident information. The objective was to demonstrate how access to restricted incident data fields could be managed in a fine-grained manner to enhance information sharing.

AB - Industry 4.0 and the ongoing digital transformation along with a large number interconnected machines and devices increase the role of cybersecurity, cyber incident handling and incident response in the factories of the future (FoF). Cyber incident information sharing plays a major role when we need to formulate situational pictures about FoF operations and environment, and respond to cybersecurity threats related to e.g. the implementation of novel technologies. Sharing of incident information has a major drawback since it may reveal too much about the attack target, e.g. in the case of legacy systems and therefore restrictions may apply. We have developed a proof-of-concept service that combines access control and encryption of data at high granularity and a mechanism for requesting access to restricted cyber incident information. The objective was to demonstrate how access to restricted incident data fields could be managed in a fine-grained manner to enhance information sharing.

KW - incident management

KW - visualisation

KW - cybersecurity

KW - information sharing

M3 - Conference article in proceedings

VL - 12

BT - Data Mining and Machine Learning

A2 - Wyld, David

A2 - Nagamalai, Dhinaharan

PB - AIRCC Publishing Corporation

T2 - 3rd International Conference on Data Mining and Machine Learning, DMML 2022

Y2 - 23 April 2022 through 24 April 2022

ER -

How to Enhance the Sharing of Cyber Incident Information via Fine-Grained Access Control

Abstract

Conference

Keywords

Access to Document

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Projects

SeCoIIA: Secure Collaborative Intelligent Industrial Assets

Cite this