Iterative selection of countermeasures for intelligent threat agents. (30th June 2015)
- Record Type:
- Journal Article
- Title:
- Iterative selection of countermeasures for intelligent threat agents. (30th June 2015)
- Main Title:
- Iterative selection of countermeasures for intelligent threat agents
- Authors:
- Baiardi, Fabrizio
Tonelli, Federico
Bertolini, Alessandro
Sperotto, A.
Hofstede, R.
Dainotti, A.
Schmitt, C.
Dreo Rodosek, G. - Abstract:
- <abstract abstract-type="main" id="nem1899-abs-0001"> <title>Summary</title> <p id="nem1899-para-0004">We describe a model‐based approach to select cost‐effective countermeasures for an information and communication technology infrastructure under attack by intelligent agents. Each agent tries to reach some predefined goals through a sequence of attacks. The proposed approach builds the models of the infrastructure and of the agents, and then it applies a Monte Carlo method that runs multiple, independent simulations of the agent attacks. These simulations produce a statistical sample that is used to assess the risk. The selection of countermeasures works in an iterative way where each iteration selects some countermeasures and applies the Monte Carlo method to evaluate any residual risk. In this way, it takes into account that an intelligent agent may select distinct attacks to replace those affected by the countermeasures. To improve cost effectiveness, the selection focuses on useful attacks to reach a goal. The Haruspex suite is an integrated set of tool to support this approach. Some of its tools build the models of the agents and the one of the system. Another tool uses these models to apply the Monte Carlo method and simulate the agent attacks. This tool is iteratively invoked by the one that select countermeasures. We describe the adoption of the suite to assess and manage the risk of three industrial control systems. Copyright © 2015 John Wiley &amp; Sons, Ltd.</p><abstract abstract-type="main" id="nem1899-abs-0001"> <title>Summary</title> <p id="nem1899-para-0004">We describe a model‐based approach to select cost‐effective countermeasures for an information and communication technology infrastructure under attack by intelligent agents. Each agent tries to reach some predefined goals through a sequence of attacks. The proposed approach builds the models of the infrastructure and of the agents, and then it applies a Monte Carlo method that runs multiple, independent simulations of the agent attacks. These simulations produce a statistical sample that is used to assess the risk. The selection of countermeasures works in an iterative way where each iteration selects some countermeasures and applies the Monte Carlo method to evaluate any residual risk. In this way, it takes into account that an intelligent agent may select distinct attacks to replace those affected by the countermeasures. To improve cost effectiveness, the selection focuses on useful attacks to reach a goal. The Haruspex suite is an integrated set of tool to support this approach. Some of its tools build the models of the agents and the one of the system. Another tool uses these models to apply the Monte Carlo method and simulate the agent attacks. This tool is iteratively invoked by the one that select countermeasures. We describe the adoption of the suite to assess and manage the risk of three industrial control systems. Copyright © 2015 John Wiley &amp; Sons, Ltd.</p> </abstract> … (more)
- Is Part Of:
- International journal of network management. Volume 25:Number 5(2015:Sep./Oct.)
- Journal:
- International journal of network management
- Issue:
- Volume 25:Number 5(2015:Sep./Oct.)
- Issue Display:
- Volume 25, Issue 5 (2015)
- Year:
- 2015
- Volume:
- 25
- Issue:
- 5
- Issue Sort Value:
- 2015-0025-0005-0000
- Page Start:
- 340
- Page End:
- 354
- Publication Date:
- 2015-06-30
- Subjects:
- Computer networks -- Management -- Periodicals
004.6 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-1190 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/nem.1899 ↗
- Languages:
- English
- ISSNs:
- 1055-7148
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.373300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 3525.xml