Phishing Detection and Response Platform
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Phishing Detection and Response Platforms (PDRs) utilize a mixture of crowd-sourced intelligence and automation technology to prevent phishing attacks. These tools provide a variety of benefits to businesses, such as reducing phishing attacks, minimizing the number of false reports that administrators face, and automating threat response processes.[1]
Background[edit]
As phishing techniques, such as ransomware and Business Email Compromise (BEC), continued to grow in commonality, it became evident that Secure Email Gateways (SEGs) were missing phishing emails.[2] With security threat trends indicating that phishing attacks were becoming more intuitive and bypassing SEGs, it became obvious that additional protection was necessary.[3] This led to the first PDR’s inception in 2020.[4]
Operation[edit]
With increasing phishing intelligence, PDRs seek to prevent malicious attacks. This is achieved through use of both AI and human intelligence.[1] The AI aspects of PDRs typically utilize deep learning and machine learning tactics in order to be effective.[5] However, PDRs cannot rely solely on technology in order to prevent phishing attacks. This is why human reporting is also a crucial aspect of Phishing Detection and Response.
References[edit]
- ↑ 1.0 1.1 "Phishing Detection and Response Software". TrustRadius. Unknown parameter
|url-status=ignored (help) - ↑ Harris, Mark; Firstbrook, Peter; Chugh, Ravisha (8 September 2020). "Market Guide for Email Security". Gartner. Unknown parameter
|url-status=ignored (help) - ↑ Watts, John (17 June 2020). "How to Respond to the 2020 Threat Landscape". Gartner. Unknown parameter
|url-status=ignored (help) - ↑ "PDR Industry Changing Phishing Detection & Response Platform". Cofense. Retrieved 2021-06-15.
- ↑ Basit, Abdul; Zafar, Maham; Liu, Xuan; Javed, Abdul Rehman; Jalil, Zunera; Kifayat, Kashif (2021-01-01). "A comprehensive survey of AI-enabled phishing attacks detection techniques". Telecommunication Systems. 76 (1): 139–154. doi:10.1007/s11235-020-00733-2. ISSN 1572-9451. PMC 7581503 Check
|pmc=value (help). PMID 33110340 Check|pmid=value (help).
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