AWDRAT: A Cognitive Middleware System for Information Survivability. (bibtex)
by Howard E. Shrobe, Robert Laddaga, Robert Balzer, Neil M. Goldman, David S. Wile, Marcelo Tallis, Tim Hollebeek, Alexander Egyed
Abstract:
The Infrastructure of modern society is controlled by software systems that are vulnerable to attacks. Many such attacks, launched by "recreational hackers" have already led to severe disruptions and significant cost. It, therefore, is critical that we find ways to protect such systems and to enable them to continue functioning even after a successful attack. This paper describes AWDRAT, a middleware system for providing survivability to both new and legacy applications. AWDRAT stands for Architectural-differencing, Wrappers, Diagnosis, Recovery, Adaptive software, and Trust-modeling. AWDRAT uses these techniques to gain visibility into the execution of an application system and to compare the application's actual behavior to that which is expected. In the case of a deviation, AWDRAT conducts a diagnosis that figures out which computational resources are likely to have been compromised and then adds these assessments to its trust-model. The trust model in turn guides the recovery process, particularly by guiding the system in its choice among functionally equivalent methods and resources. AWDRAT has been used on an example application system, a graphical editor for constructing mission plans. We present data showing the effectiveness of AWDRAT in detecting a variety of compromises to the application system.
Reference:
AWDRAT: A Cognitive Middleware System for Information Survivability. (Howard E. Shrobe, Robert Laddaga, Robert Balzer, Neil M. Goldman, David S. Wile, Marcelo Tallis, Tim Hollebeek, Alexander Egyed), In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI 2006) and the 18th Innovative Applications of Artificial Intelligence Conference (IAAI 2006), Boston, USA, AAAI Press, 2006.
Bibtex Entry:
@Conference{DBLP:conf/aaai/ShrobeLBGWTHE06,
  author    = {Howard E. Shrobe and Robert Laddaga and Robert Balzer and Neil M. Goldman and David S. Wile and Marcelo Tallis and Tim Hollebeek and Alexander Egyed},
  title     = {AWDRAT: A Cognitive Middleware System for Information Survivability.},
  booktitle = {Proceedings of the 21st National Conference on Artificial Intelligence (AAAI 2006) and the 18th Innovative Applications of Artificial Intelligence Conference (IAAI 2006), Boston, USA},
  year      = {2006},
  pages     = {1836-1843},
  publisher = {AAAI Press},
  abstract  = {The Infrastructure of modern society is controlled by software systems
	that are vulnerable to attacks. Many such attacks, launched by "recreational
	hackers" have already led to severe disruptions and significant cost.
	It, therefore, is critical that we find ways to protect such systems
	and to enable them to continue functioning even after a successful
	attack. This paper describes AWDRAT, a middleware system for providing
	survivability to both new and legacy applications. AWDRAT stands
	for Architectural-differencing, Wrappers, Diagnosis, Recovery, Adaptive
	software, and Trust-modeling. AWDRAT uses these techniques to gain
	visibility into the execution of an application system and to compare
	the application's actual behavior to that which is expected. In the
	case of a deviation, AWDRAT conducts a diagnosis that figures out
	which computational resources are likely to have been compromised
	and then adds these assessments to its trust-model. The trust model
	in turn guides the recovery process, particularly by guiding the
	system in its choice among functionally equivalent methods and resources.
	AWDRAT has been used on an example application system, a graphical
	editor for constructing mission plans. We present data showing the
	effectiveness of AWDRAT in detecting a variety of compromises to
	the application system.},
  file      = {:Conferences\\AAAI 2006 - AWDRAT - A Cognitive Middleware System for Information Survivability\\AWDRAT - A Cognitive Middleware System for Information Survivability-preprint.pdf:PDF},
  keywords  = {},
  url       = {http://www.aaai.org/Library/AAAI/2006/aaai06-303.php},
}
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