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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

907
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
907
Observational Learning01:12

Observational Learning

722
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
722
Social Cognitive Perspective on Personality01:30

Social Cognitive Perspective on Personality

879
Social cognitive perspectives on personality emphasize the importance of conscious awareness, beliefs, expectations, and goals in shaping behavior. These perspectives incorporate behaviorist principles, such as learning through reinforcement and conditioning, but extend beyond them by highlighting human reasoning and planning. Unlike traditional behaviorist views, social cognitive theory focuses on how individuals reflect on their past experiences and plan for future outcomes by considering...
879
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

2.0K
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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Modeling in Therapy01:26

Modeling in Therapy

306
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
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The Influence of Cognition on Affect01:29

The Influence of Cognition on Affect

132
Cognition plays a pivotal role in shaping emotional experiences, as demonstrated by Schachter and Singer’s two-factor theory of emotion. According to this model, emotion arises from a combination of physiological arousal and cognitive interpretation. The body’s physiological response to stimuli is ambiguous and only gains emotional significance through cognitive labeling. For instance, an increased heart rate and adrenaline surge while standing near an attractive person may be...
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Related Experiment Videos

Cognitive Models in Cybersecurity: Learning From Expert Analysts and Predicting Attacker Behavior.

Vladislav D Veksler1, Norbou Buchler2, Claire G LaFleur2

  • 1DCS Corporation, U.S. Army Data & Analysis Center, Aberdeen Proving Ground, MD, United States.

Frontiers in Psychology
|July 3, 2020
PubMed
Summary
This summary is machine-generated.

Symbolic Deep Learning (SDL) can reduce missed cybersecurity threats by 25%. Model-tracing predicts attacker preferences 40-70% of the time, enhancing cybersecurity strategies.

Keywords:
XAI (eXplainable Artificial Intelligence)behavioral simulationscognitive modelingcyber-securitydecision supportdeep learninghuman-agent teamingreinforcement learning

Related Experiment Videos

Area of Science:

  • Cognitive Science
  • Cybersecurity
  • Artificial Intelligence

Background:

  • Cybersecurity requires predicting attacker and defender behavior.
  • Symbolic Deep Learning (SDL) shows promise for modeling expert defender behavior.
  • Model-tracing with dynamic parameter fitting can model attacker preferences during live attacks.

Purpose of the Study:

  • To evaluate the utility of SDL for defender decision support.
  • To assess model-tracing's effectiveness in predicting attacker preferences.
  • To demonstrate the value of cognitive modeling in cybersecurity.

Main Methods:

  • Two human experiments were conducted.
  • Experiment 1: Participants acted as cyber analysts using SDL for Intrusion Detection System (IDS) alert elevation.
  • Experiment 2: Participants acted as attackers choosing strategies, with model-tracing used for preference prediction.

Main Results:

  • SDL reduced missed threats by 25% in the defender experiment.
  • Model-tracing accurately predicted attacker preferences 40-70% of the time.
  • Both cognitive modeling approaches showed practical value for cybersecurity professionals.

Conclusions:

  • Cognitive models, particularly SDL and model-tracing, offer significant benefits for cybersecurity.
  • These models can enhance defender decision support and enable proactive risk mitigation by predicting attacker behavior.
  • Further research into human cognition is crucial for advancing cybersecurity capabilities.