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

Bullying02:04

Bullying

9.0K
A modern form of aggression is bullying. As you learn in your study of child development, socializing and playing with other children is beneficial for children’s psychological development. However, as you may have experienced as a child, not all play behavior has positive outcomes. Some children are aggressive and want to play roughly. Other children are selfish and do not want to share toys. One form of negative social interactions among children that has become a national concern is...
9.0K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

731
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
731
Random Error01:04

Random Error

10.1K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
10.1K
Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

63
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable...
63
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

129
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
129

You might also read

Related Articles

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

Sort by
Same author

A spatiotemporal cell theory for cooperative pattern formation in reinforcement learning-driven evolutionary games.

Chaos (Woodbury, N.Y.)·2026
Same author

System-level reconfiguration of the aging brain: Linking dynamics, morphology and micro-architectures.

NeuroImage·2026
Same author

Multi-neurotransmitter synergistically regulated basal ganglia reinforcement learning model.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Unsupervised Joint Alignment Framework for Cross-Site Depression Classification Using fMRI.

IEEE journal of biomedical and health informatics·2026
Same author

Optimizing disorder with machine learning to harness phase synchronization.

Chaos (Woodbury, N.Y.)·2026
Same author

Controlling severe atopic dermatitis dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Videos

Spatiotemporal patterns and predictability of cyberattacks.

Yu-Zhong Chen1, Zi-Gang Huang2, Shouhuai Xu3

  • 1School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA.

Plos One
|May 21, 2015
PubMed
Summary
This summary is machine-generated.

Cyberattacks exhibit predictable spatiotemporal patterns, contrary to common belief. Identifying these intrinsic patterns in IP address space allows for better anticipation and mitigation of cyber threats.

Related Experiment Videos

Area of Science:

  • Cybersecurity Science and Engineering
  • Network Security Analysis

Background:

  • Conventional cybersecurity wisdom posits the absence of intrinsic attack patterns due to cyberspace complexity.
  • The existence of inherent cyberattack patterns remains an underexplored area.

Purpose of the Study:

  • To investigate and uncover intrinsic spatiotemporal patterns in cyberattacks.
  • To analyze macroscopic properties of cyberattack traffic flows.

Main Methods:

  • Analysis of an extensive dataset recording time-dependent attack frequencies across consecutive IP addresses.
  • Application of quantitative measures including flux-fluctuation law and Markov state transition probability matrix.
  • Characterization of attack patterns using predictability measures.

Main Results:

  • Discovery of two distinct intrinsic spatiotemporal attack patterns: deterministic and stochastic.
  • Identification of a small number of major attackers responsible for the majority of attacks.
  • Demonstration of unique spatiotemporal characteristics linked to specific IP regions and attacker behaviors.

Conclusions:

  • Cyberattack patterns possess a high degree of predictability.
  • Understanding these macroscopic patterns can enable anticipation and mitigation of large-scale cyberattacks.
  • The findings suggest a shift towards proactive cybersecurity strategies based on pattern recognition.