Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Manipulation and Analysis01:21

Manipulation and Analysis

28
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
28
Thematic Layering in GIS01:30

Thematic Layering in GIS

40
In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
40
Introduction to GIS01:28

Introduction to GIS

71
Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
71
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

28
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
28

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Maintaining Cyber Resilience in the Reconfigurable Networks with Immunization and Improved Network Game Methods.

Sensors (Basel, Switzerland)·2024
Same author

Syntactic-Semantic Detection of Clone-Caused Vulnerabilities in the IoT Devices.

Sensors (Basel, Switzerland)·2024
See all related articles

Related Experiment Video

Updated: Jul 11, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

590

A Graph-Based Technique for Securing the Distributed Cyber-Physical System Infrastructure.

Maxim Kalinin1, Evgenii Zavadskii1, Alexey Busygin1

  • 1Institute of Computer Sciences and Cybersecurity, Peter the Great St. Petersburg Polytechnic University, 29 Polytekhnicheskaya ul., 195251 St. Petersburg, Russia.

Sensors (Basel, Switzerland)
|November 14, 2023
PubMed
Summary

This study introduces a graph-based technique for detecting compromised nodes in cyber-physical systems. It effectively identifies intrusions like advanced persistent threats and ransomware in dynamic environments.

Keywords:
adaptationattack graphcyber-physical systemfunctional dependencies graphfunctional infrastructuresecurityvirtual isolated network

More Related Videos

A Simple Protocol for Mapping the Plant Root System Architecture Traits
11:09

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Published on: February 10, 2023

2.9K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

Related Experiment Videos

Last Updated: Jul 11, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

590
A Simple Protocol for Mapping the Plant Root System Architecture Traits
11:09

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Published on: February 10, 2023

2.9K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

Area of Science:

  • Computer Science
  • Cybersecurity
  • Systems Engineering

Background:

  • Increasing digitalization and autonomy in cyber-physical systems (CPS) introduce significant security vulnerabilities.
  • Adversarial actions in networked systems can lead to severe negative consequences.

Purpose of the Study:

  • To propose a comprehensive technique for enhancing the security of distributed functional cyber-physical systems.
  • To enable dynamic detection and adaptation to rolling intrusions within CPS infrastructure.

Main Methods:

  • Representing the CPS infrastructure using two types of graphs: a functional dependencies graph and a potential attacks graph.
  • Utilizing graph-based analysis for dynamic detection of compromised nodes.
  • Conducting experimental modeling to validate the technique's effectiveness.

Main Results:

  • The proposed technique demonstrated effectiveness in identifying multiple compromised nodes within the functional infrastructure.
  • The graph-based approach allows for adaptation to evolving and rolling intrusions.
  • Experimental validation confirmed efficacy against advanced persistent threats and ransomware scenarios.

Conclusions:

  • The developed graph-based technique offers a robust method for securing cyber-physical systems against sophisticated cyber threats.
  • Dynamic detection and adaptive capabilities are crucial for resilient CPS infrastructure in the face of evolving adversaries.