Robust and Efficient Anti-Phishing Techniques

Abstract

The OSD needs high-accuracy and low-latency automatic identification and mitigation techniques to detect and stop phishing attacks. This project researched and developed socio-linguistic indicators that can be used to support more fine-grained, accurate detection of phishing emails. The indicators address several different types of phishing emails, including social malware emails, and demonstrate the feasibility and desirability of adding socio-linguistic attributes to phishing detection signatures. The project focused on : feasibility study of socio-linguistic attributes as indicators of phishing; development of socio-linguistic features for detection of phishing emails; development of a prototype for collecting socio-linguistic features from phishing emails.

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Document Details

Document Type
Technical Report
Publication Date
Aug 27, 2012
Accession Number
ADA586670

Entities

People

  • John F. Buford
  • Nina Kohli-laven

Tags

Communities of Interest

  • Biomedical
  • Cyber
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Commerce
  • Computer Network Security
  • Computer Programs
  • Data Sets
  • Electronic Mail
  • Identification
  • Internet
  • Language
  • Linguistics
  • Mobile Phones
  • Operating Systems
  • Smartphones
  • Social Media
  • Social Networking Services
  • Test Sets
  • Text Messaging
  • Websites

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Distributed Systems and Data Platform Development

Technology Areas

  • Cyber