
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
|
Initial Amendment Date: | August 25, 2015 |
Latest Amendment Date: | September 15, 2016 |
Award Number: | 1505799 |
Award Instrument: | Continuing Grant |
Program Manager: |
David Corman
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | September 1, 2015 |
End Date: | August 31, 2019 (Estimated) |
Total Intended Award Amount: | $1,125,000.00 |
Total Awarded Amount to Date: | $1,125,000.00 |
Funds Obligated to Date: |
FY 2016 = $375,000.00 |
History of Investigator: |
|
Recipient Sponsored Research Office: |
3451 WALNUT ST STE 440A PHILADELPHIA PA US 19104-6205 (215)898-7293 |
Sponsor Congressional District: |
|
Primary Place of Performance: |
3451 Walnut Street P-221 FB Philadelphia PA US 19104-6205 |
Primary Place of
Performance Congressional District: |
|
Unique Entity Identifier (UEI): |
|
Parent UEI: |
|
NSF Program(s): | Information Technology Researc |
Primary Program Source: |
01001617DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
|
Program Element Code(s): |
|
Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public. However, much of the recent and on-going efforts concentrate on security of general-purpose computation and on privacy in communication and social interactions. The advent of cyber-physical systems (e.g., safety-critical IoT), which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new horizons for intelligent systems with advanced capabilities. These systems may reduce number of accidents and increase throughput of transportation networks, improve patient safety, mitigate caregiver errors, enable personalized treatments, and allow older adults to age in their places. At the same time, cyber-physical systems introduce new challenges and concerns about safety, security, and privacy. The proposed project will lead to safer, more secure and privacy preserving CPS. As our lives depend more and more on these systems, specifically in automotive, medical, and Internet-of-Things domains, results obtained in this project will have a direct impact on the society at large. The study of emerging legal and ethical aspects of large-scale CPS deployments will inform future policy decision-making. The educational and outreach aspects of this project will help us build a workforce that is better prepared to address the security and privacy needs of the ever-more connected and technologically oriented society.
Cyber-physical systems (CPS) involve tight integration of computational nodes, connected by one or more communication networks, the physical environment of these nodes, and human users of the system, who interact with both the computational part of the system and the physical environment. Attacks on a CPS system may affect all of its components: computational nodes and communication networks are subject to malicious intrusions, and physical environment may be maliciously altered. CPS-specific security challenges arise from two perspectives. On the one hand, conventional information security approaches can be used to prevent intrusions, but attackers can still affect the system via the physical environment. Resource constraints, inherent in many CPS domains, may prevent heavy-duty security approaches from being deployed. This proposal will develop a framework in which the mix of prevention, detection and recovery, and robust techniques work together to improve the security and privacy of CPS. Specific research products will include techniques providing: 1) accountability-based detection and bounded-time recovery from malicious attacks to CPS, complemented by novel preventive techniques based on lightweight cryptography; 2) security-aware control design based on attack resilient state estimator and sensor fusions; 3) privacy of data collected and used by CPS based on differential privacy; and, 4) evidence-based framework for CPS security and privacy assurance, taking into account the operating context of the system and human factors. Case studies will be performed in applications with autonomous features of vehicles, internal and external vehicle networks, medical device interoperability, and smart connected medical home.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
According to a NIST definition, a cyber-physical system (CPS) is comprised of interacting digital, analog, physical, and human components engineered for function through integrated physics and logic. Examples of CPS include autonomous vehicles and smart electrical grid. CPSs promise to bring unprecedented advantages to many aspects of modern society, such as emergency response, traffic management, healthcare, etc. At the same time, the tight coupling between physical processes and computer control creates new security and privacy threats which, left unchecked, can lead to tremendous harm and loss of life. The primary goals of this project were to form a comprehensive understanding of these new CPS-specific threats and develop new technologies to protect our critical infrastructure from these threats.
The project has substantially increased our understanding of cyber-physical security and yielded several new techniques to design CPS with proven security and privacy guarantees.
One focus area of the project was protection against sensor attacks. This problem is of particular importance to autonomous systems such as self-driving cars, which rely on multiple sensors to determine the state of the vehicle and made control decisions. Some commonly used sensors, in particular GPS, can be spoofed in a stealthy way that can lead the vehicle off track and crash. We have developed techniques to exploit redundancy in sensor readings to accurately estimate the state of the vehicle and detect and isolate failed or compromised sensors. We have also developed techniques to recover the state of an autonomous control system after an attack by periodically checkpointing known good states and rolling forward the checkpointed value using partial knowledge of physical dynamics of the vehicle.
Another focus area addresses privacy concerns in CPS. Autonomous CPS rely on vast amount of data to perform their functions, but much of this data may reveal sensitive information about the system or its users. We studied ways to protect this data from malicious observers without interfering with the system operation. An important outcome of this effort is a set coding schemes for protecting sensitive information about the system state or a planned system trajectory against eavesdropping attacks. The coding schemes guarantee that an eavesdropper trying to estimate the state of the system will experience a large estimation error, while the error of the legitimate user will remain small.
Project outcomes have been disseminated to the CPS research community through publications in leading research conferences and archival journals. Results from this project have been incorporated into several graduate courses at the University of Pennsylvania, taught at the departments of Computer and Information Sciences and Electrical and Systems Engineering. Five graduate students and post-doctoral associates working on the project have secured faculty positions at research universities in the U.S. and U.K.
Last Modified: 12/30/2019
Modified by: Oleg Sokolsky
Please report errors in award information by writing to: awardsearch@nsf.gov.