Learning to Automate Social Engineering Resistance (LASER)

Abstract

Project LASER explores and creates a suite of technologies that can radically harden enterprise security by the large scale automation of active social engineering defenses. The proposed LASER system is able to efficiently process large volume of messages, accurately detecting the attacks and the attack motives, and actively responding back to the attacker to obtain more information through well-formed high-quality response. The proposed work will shield both individuals and organization from social engineering attacks.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 2020
Accession Number
AD1123569

Entities

People

  • Ben Y. Zhao
  • Bo Li
  • Christopher Ré
  • Dawn Song
  • Le Song
  • Percy Liang

Organizations

  • Georgia Tech
  • Stanford University
  • University of California, Berkeley
  • University of Chicago
  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Languages
  • Computer Programming
  • Computers
  • Deep Learning
  • Detection
  • Electronic Mail
  • Engineering
  • Graphical User Interface
  • Information Science
  • Jet Propulsion
  • Machine Learning
  • Motor Skills
  • Natural Language Processing
  • Network Protocols
  • Neural Networks
  • Text Messaging
  • User Interface

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Distributed Systems and Data Platform Development

Technology Areas

  • Directed Energy