Collective Attention Threats: Models and Deterrence

Abstract

This project investigates threats to collective attention and develops both models of these phenomena as well as methods to deter their impact and reach. These collective attention threats manipulate opinion, rapidly spread malware, and disseminate misinformation, all amplified by collective attention. Unlike traditional threats, users themselves are unwitting accomplices to the spread, infection rate, and success of these new threats. This project aims to develop new models, algorithms, and systems for defending against emergent collective attention threats in large-scale systems.

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Document Details

Document Type
Technical Report
Publication Date
Jul 17, 2018
Accession Number
AD1060776

Entities

People

  • Anna Squicciarini
  • James Caverlee

Organizations

  • Pennsylvania State University
  • Texas Engineering Experiment Station

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Availability
  • Classification
  • Computer Science
  • Contracts
  • Control
  • Crowdsourcing
  • Data Mining
  • Department Of Defense
  • Deterrence
  • Engineering
  • Infection
  • Information Science
  • Law
  • Monitoring
  • National Security
  • Quality Control
  • Scientific Research
  • Security
  • Social Media
  • Social Networks
  • Standards
  • Universities
  • Wound Infections

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Strategic Security Studies

Technology Areas

  • Cyber