# Spam and Phishing Detection

{
  "id": "T11644",
  "title": "Spam and Phishing Detection",
  "url": "/topics/T11644",
  "kind": "topic-directory",
  "aeo_cohort": "topic-directory",
  "provider": "openalex",
  "revision": "0af5b7515984386d",
  "catalogue_revision": "f050b5d4780b1289",
  "numeric_address": "36183039105748051",
  "address_version": "morton4x16-v1",
  "coordinates": [
    3,
    17,
    1710,
    11644
  ],
  "answer_status": "Directory metadata; local answer requires separate source review",
  "truth_status": "Subject descriptor, not a factual answer or a demonstrated knowledge gap"
}

This cluster of papers focuses on the detection and prevention of phishing attacks, including techniques such as spam detection, machine learning, bot detection, review spam analysis, URL filtering, and defense against Sybil attacks in social networks. The research also explores behavioral analysis for identifying suspicious activities and emphasizes the importance of security education in mitigating phishing threats.

Directory metadata is not a factual answer or evidence of a global knowledge gap.

Source: https://openalex.org/T11644

No owner-reviewed local answer yet.