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Title: Dynamic Attack Surfaces in Nuclear Power Plants.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human Machine Interface Technologies held June 11-15, 2017 in San Fransisco, CA.
Country of Publication:
United States

Citation Formats

Lamb, Christopher, and Dawson, Lon Andrew. Dynamic Attack Surfaces in Nuclear Power Plants.. United States: N. p., 2017. Web.
Lamb, Christopher, & Dawson, Lon Andrew. Dynamic Attack Surfaces in Nuclear Power Plants.. United States.
Lamb, Christopher, and Dawson, Lon Andrew. Wed . "Dynamic Attack Surfaces in Nuclear Power Plants.". United States. doi:.
title = {Dynamic Attack Surfaces in Nuclear Power Plants.},
author = {Lamb, Christopher and Dawson, Lon Andrew},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}

Other availability
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  • The consideration of how one compromised digital equipment can impact neighboring equipment is critical to understanding the progression of cyber attacks. The degree of influence that one component may have on another depends on a variety of factors, including the sharing of resources such as network bandwidth or processing power, the level of trust between components, and the inclusion of segmentation devices such as firewalls. The interactions among components via mechanisms that are unique to the digital world are not usually considered in traditional PRA. This means potential sequences of events that may occur during an attack may be missedmore » if one were to only look at conventional accident sequences. This paper presents a method where, starting from the initial attack vector, the progression of a cyber attack can be modeled. The propagation of the attack is modeled by considering certain attributes of the digital components in the system. These attributes determine the potential vulnerability of a component to a class of attack and the capability gained by the attackers once they are in control of the equipment. The use of attributes allows similar components (components with the same set of attributes) to be modeled in the same way, thereby reducing the computing resources required for analysis of large systems.« less
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