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Cyber-Physical Security Assessment (CyPSA) Toolset

CyPSA seeks to organize and gain insight into the diverse sets of data that a critical infrastructure provider must manage. Specifically CyPSA inventories, manages, and analyzes assets and relations among those assets. A variety of interfaces are provided. CyPSA inventories assets (both cyber and physical). This may include the cataloging of assets through a common interface. Data sources used to generate a catalogue of assets include PowerWorld, NPView, NMap Scans, and device configurations. Depending upon the role of the person using the tool the types of assets accessed as well as the data sources through which asset information is accessed may vary. CyPSA allows practitioners to catalogue relations among assets and these may either be manually or programmatically generated. For example, some common relations among assets include the following: Topological Network Data: Which devices and assets are connected and how? Data sources for this kind of information include NMap scans, NPView topologies (via Firewall rule analysis). Security Metrics Outputs: The output of various security metrics such as overall exposure. Configure Assets:CyPSA may eventually include the ability to configure assets including relays and switches. For example, a system administrator would be able to configure and alter the state of a relay via the CyPSA interface. Annotate Assets: CyPSA also allows practitioners to manually and programmatically annotate assets. Sources of information with which to annotate assets include provenance metadata regarding the data source from which the asset was loaded, vulnerability information from vulnerability databases, configuration information, and the output of an analysis in general.

Garcia, Luis↗

Component based approach to modeling for model checking

This paper presents a portion of an overall research project on the generation of a software security assessment instrument to aid developers in assessing and assuring the security of software in the development and maintenance lifecycles.

security toolset model checking security safety fo↗

Reducing Software Security Risk Through an Integrated Approach

This paper discusses new joint work by the California Institute of Technology's Jet Propulsion Laboratory and the University of California at Davis sponsored by the National Aeronautics and Space Administration to develop a security assessment instrument for the software development and maintenance life cycle.

risk matrix↗

Managing information technology security risk

Information Technology (IT) Security Risk Management is a critical task for the organization to protect against the loss of confidentiality, integrity and availability of IT resources. As systems bgecome more complex and diverse and and attacks from intrusions and malicious content increase, it is becoming increasingly difficult to manage IT security risk. This paper describes a two-pronged approach in addressing IT security risk and risk management in the organization: 1) an institutional enterprise appraoch, and 2) a project life cycle approach.

security toolset↗

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

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Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗