
Security needs to move beyond the Fortress Mentality of Firewalls
INVESTIGATORS
Bruce McMillin (PI)
FUNDING SOURCE
National Institute of Standards and Technology
PROJECT DESCRIPTION
Providing Cyber-Physical System (CPS) security goes beyond traditional IT/enterprise cybersecurity and beyond purely physical security to combine both into Cyber-Physical Security. In CPSs, threats can arise through both the cyber and physical aspects, in combination. Moreover, in a CPS, ideas of high and low and inside and outside no longer represent modern systems; security domains can overlap. This proposal extends work in information flow analysis to detect the possibility of confidentiality leakages and integrity attacks, develop tools for assessment, and provide design parameters for reducing risk among security partitions of a CPS. The proposed work will be measured against developed use cases from NIST and the Smart Grid Interoperability Panel.
PUBLICATIONS
Peer-to-Peer Managed Microgrid
INVESTIGATORS
Bruce McMillin (PI), Mariesa Crow, Jonathan Kimball, Mehdi Ferdowsi (co-PIs)
FUNDING SOURCE
NSF
PROJECT DESCRIPTION
The mission of the ERC for FREEDM Systems is to develop the fundamental and enabling technology to foster a revolution in innovation and technology in the electric power and renewable energy industries. For intellectual merit the work has yielded numerous publications, in advancing distributed energy management, system modeling, and security (a selected list is [20],[28],[62]–[68]) and has advanced the electric smart grid effort significantly past its current state. Extensive broader impacts include outreach to industry, consortia, and K-12 science and undergraduate and under-represented group mentoring. Specifically, FREEDM has contributed to the Smart Grid Interoperability Panel and the National Institute of Standards and Technology Cyber-Physical Systems Public Working Group (2014-) and NISTiR 7628, Security and Privacy for the Smart Grid. In particular, the FREEDM project's outreach makes distributed energy management and the advanced smart grid understandable by the general population.
PUBLICATIONS
INVESTIGATORS
Jonathan Kimball (PI), Bruce McMillin (co-PI)
FUNDING SOURCE
NSF
PROJECT DESCRIPTION
The objective of this proposal is to formulate a novel methodology for creating secure algorithms in cyber-physical systems and to develop metrics for evaluating the security of composed systems. Cyber-physical systems are composed of interconnected, semi-autonomous devices. The inherently open nature of a CPS implies a susceptibility to attacks that differ fundamentally from conventional cyber-attacks. CPS-specific attack vectors exist as purely cyber, cyber-enabled physical attacks, and physically enabled cyber-attacks. As such, the endpoints may be fundamentally unsecurable (such as the sensed information from physical resources) or may be compromised (as in computational resources). Creating a secure communications channel between two nodes is inadequate if one of the endpoints of the communication is insecure. Therefore, new methodologies are needed to ensure that the system is protected in the presence of open information flows from physical resources and possibly malicious entities inside the system.
The proposed approach relies on the interconnected nature of the cyber and physical aspects to ensure that information exchanges are trustworthy. Any action taken by any entity in the system should project onto the various subsystems in a consistent way. For example, in a power system, if an entity claims to be generating a certain amount of power (within the cyber realm), then the flows and voltages on the grid (within the physical realm) should reflect that generation level. The projections may be used to evaluate the trustworthiness of each entity.
The first objective is to formulate a methodology that incorporates knowledge from both the cyber and physical domains into a distributed algorithm to ensure the trustworthiness, thus security, of the composed system. The second objective is to derive metrics for security. Both objectives rest on logical invariants that express correctness. The invariants either check the validity of a local action or the accuracy of remote data. They may be used as guards against an action, or may be incorporated into a dynamic reputation-based algorithm. As a testbed, a multilateral energy system on an electrical network will be studied. Preliminary studies of this system have resulted in algorithms that isolate malicious nodes within the context of a single algorithm, using a reputation metric that compares cyber information flows to physically measurable signals. The work will be extended to other algorithms and other related power systems, a generalizable framework will be developed, and more complete metrics will be derived.
PUBLICATIONS

INVESTIGATORS
Steven Corns (PI), cornss@mst.edu, 573-341-6367; Suzanna Long, (Co-PI), longsuz@mst.edu, Mariesa Crow, (Co-PI), crow@mst.edu
FUNDING SOURCE
U.S. Army Corps of Engineers and Department of Engineering Management and Systems Engineering at Missouri S&T.
PROJECT DESCRIPTION
This project provides a holistic approach to base camp layout and design. A framework has been developed to incorporate multiple models and simulations with information sharing between these models. This provides a method to couple the information related to the base camp systems to capture the second, third, and higher order effects brought about by changes in these systems. By accounting for these complex relationships it is possible to create an accurate representation of base camp resource usage. Several tools were developed to create and enable the interfaces both between model types and between models and decision makers/system users.
PUBLICATIONS

INVESTIGATORS
Sajal K. Das (sdas@mst.edu, 573-341-7708)
FUNDING SOURCE
National Science Foundation (Smart and Connected Health Program)
PROJECT DESCRIPTION
The goal of this project is to design, implement, and evaluate in-home techniques for generating reports of activities and social interactions that are useful for monitoring wellbeing and for automating intervention strategies for persons with dementia. The plan is to design machine learning techniques that make effective use of sensor data to perform automated activity monitoring and prompting-based interventions that are beneficial for the residents as well as for their caregivers and family. The environment is human-centric because it learns information about its human residents and uses this information to provide activity-aware monitoring and intervention services. By transforming everyday environments into smart environments, many older adults with cognitive and physical impairment can lead independent lives in their own homes. A key component of this project is an evaluation of the technologies in actual homes with volunteer older adults and thus will assess the technologies for acceptance with the target population.
PUBLICATIONS

INVESTIGATORS
Sajal K. Das (sdas@mst.edu, 573-341-7708), Mariesa Crow and Simone Silvestri
FUNDING SOURCE
National Science Foundation (Cyber-Physical Systems Program)
PROJECT DESCRIPTION
The objective of this collaborative project is to understand, study and analyze in a holistic manner the vulnerabilities of smart grid system due to intricate interactions with the communication networks. Specific goas include: (i) investigating a wide variety of attacks, misconfiguration, malfunctioning, and failure scenarios in the communications networks, and characterizing their impacts on the smart grid; and (ii) designing a multi-level security framework based on robust state estimation and trust model that hardens the grid against malfunctions and attacks from the communications side, thus preventing cascade failures.
PUBLICATIONS
INVESTIGATORS
Sajal K. Das (sdas@mst.edu, 573-341-7708)
FUNDING SOURCE
National Science Foundation
PROJECT DESCRIPTION
Organisms adapt to external perturbations through optimized structure of their gene regulatory networks (GRNs). In the long-term, the state transition network of a GRN converges to a set of attractors that make the organism resilient to removal or functional impairment of genes. In wireless sensor networks (WSNs), such attractors refer to a group of sensors serving as sink nodes for packets sent over multiple hops. This project maps such attractor based genomic robustness onto WSNs to infer optimal topologies and routing strategies that mitigate both sensor failure and a noisy wireless channel. This is being achieved by conducting experiments in silico gene by simulating the functional removal of a gene from sample GRNs, to understand the dynamics of the attractor state space. This information is next used to design WSN topologies and routing protocols that are resilient to network uncertainty, node breakdown and compromise. This project also pursues the design of optimal wiring rules between sensors in a robust WSN that guarantees maximum probability of successful packet transmission under a given routing strategy. Validation and testing are accomplished on real life WSN testbeds.
PUBLICATIONS

INVESTIGATORS
Sajal K. Das (sdas@mst.edu, 573-341-7708)
FUNDING SOURCE
National Science Foundation
PROJECT DESCRIPTION
The goal of this project is to create a novel architecture-independent framework for designing efficient, portable and scalable parallel algorithms for analyzing large-scale dynamic networks, such as social networks, biological networks, and disaster networks. The basic idea is to exploit graph sparsification techniques to divide the network into sparse subgraphs (certificates) that form the leaves of a sparsification tree. This innovative approach leads to the design and analysis of efficient parallel algorithms for updating dynamic networks, and reduction of memory latency associated with parallelizing unstructured data. Specifically, parallel algorithms will be designed for maintaining network topological characteristics and updating influential vertices and communities. The portability and performance of algorithms will be demonstrated via implementation on distributed memory clusters, shared memory multicores, and massively multithreaded parallel computers.
PUBLICATIONS
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