SBIR-STTR Award

Securing Industrial Control Networks with Network Forecasting
Award last edited on: 3/30/2022

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,539,888
Award Phase
2
Solicitation Topic Code
-----

Principal Investigator
Michael Schultz

Company Information

Observable Networks LLC

230 South Bemiston Avenue Suite 420
St Louis, MO 63105
   (314) 899-9284
   info@bservable.net
   www.observable.net
Location: Single
Congr. District: 02
County: St. Louis

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2012
Phase I Amount
$180,000
The innovation of network forecasting is a new approach to securing industrial control networks that is based upon 1) discovering, monitoring, and modeling all devices on a network, 2) using these models to predict future device behavior, 3) evaluating past predictions with current observations of networked device behavior, and 4) investigating prediction-observation discrepancies to discover misbehaving devices. The intellectual merit of the innovation lies in its departure from traditional network security paradigms. Traditional approaches, such as signature-based anti-virus and intrusion prevention systems, detect misbehaviors by recognizing repeats of past behaviors; these approaches necessarily overlook one-of-a-kind or zero-day misbehaviors. In contrast, network forecasting incorporates an understanding of correct and expected network behavior so that aberrant behavior can be identified even if it has not been seen before. The approach will be built upon the foundation of Continuous Device Profiling (CDP), which concretely models and monitors the active roles that devices assume on the network. Network forecasting will predict near-future CDP characteristics of devices; when predictions fail to match reality on the network, network operators can respond without needing to fully understand the details of the threat that caused the disturbance. The broader/commercial impact of this innovation is substantial because critical infrastructure represents both a significant investment and a substantive risk in modern society. While recent cyber attacks may have heightened public awareness of these threats, such infrastructure has been the object of sustained concern from government and private-sector groups for many years. However, as our need for increased security in critical infrastructure has grown, the effectiveness of network security methods has diminished; the pace of effective cyber attacks and network breaches is increasing, not decreasing, as time passes. If successful, network forecasting has the potential to transform the security and monitoring practices in nearly all domains of critical infrastructure, far beyond the power plant demonstration this proposed effort will undertake. The stakes are high: future cost savings, technological advances and economic prosperity all presume the existence of secure, networked critical infrastructure. Substantial advances in the security of such infrastructure, such as that promised by network forecasting, can help protect that future.

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2014
(last award dollars: 2015)
Phase II Amount
$1,359,888

This Small Business Innovation Research Phase II project is focused on network forecasting, a new approach to securing industrial control networks. In essence, network forecasting involves monitoring all devices on a network, and for each device using past behavior to predict near-term future behavior. Deviation from predicted behavior then signals a potential issue. The intellectual merit of the innovation lies in its departure from traditional network security paradigms. Traditional approaches, such as signature-based anti-virus and intrusion prevention systems, detect misbehaviors by recognizing repeats of past behaviors. These approaches necessarily overlook one-of-a-kind or zero-day misbehaviors. In contrast, network forecasting incorporates an understanding of correct and expected network behavior so that aberrant behavior can be identified even if it has not been seen before. The approach builds on the company's previous work in understanding the active roles that devices assume on a network. When predicted network device behavior fails to match reality on the network, network operators can respond without needing to fully understand the details of the threat that caused the disturbance. The broader impact/commercial potential of this project is substantial because critical infrastructure - such as a power generation and distribution grid - represents both a significant investment and a substantive vulnerability in modern society. While recent cyber-attacks may have heightened public awareness of the threats to critical infrastructure, such infrastructure has been the object of sustained concern from government and private-sector groups for many years. However, while the need for increased security in critical infrastructure has grown over time, the effectiveness of network security methods has not kept pace with the sophistication and impact of cyber-attacks. If successful, network forecasting has the potential to transform the security and monitoring practices in nearly all domains of critical infrastructure. Continued technological advances and economic growth presume the existence of secure, networked critical infrastructure. Substantial advances in the security of such infrastructure, such as that promised by the technology being developed in this project, can help protect the future of our society.