Automating the Discovery and Investigation of Targeted Attacks with AI and Machine Learning

Alejandro Borgia, VP Product Management, Security Analytics & Research, Symantec

Abstract: 

Targeted attacks represent one of the most dangerous threats to enterprise security today. Yet they are often hidden from view under a mountain of alerts generated by security systems, giving attackers time to gain access to systems and seize valuable data. Symantec’s new Targeted Attack Analytics (TAA) technology leverages advanced machine learning to automate the discovery of targeted attacks, identifying truly targeted activity and prioritizing it in the form of a highly reliable incident report. TAA, which is the result of an internal joint-effort between Symantec’s Attack Investigation Team and a team of Symantec’s top security data scientists on the leading edge of machine learning research, analyzes a broad range of data from one of the largest threat data lakes in the world to automate targeted threat detection.

Alejandro Borgia, VP Product Management, Security Analytics & Research, Symantec

Alejandro Borgia leads Product Management for Symantec’s Security Analytics and Research division, which includes the company’s Security Technology and Response (STAR) organization, the Center for Advanced Machine Learning (CAML), and Shared Engineering Services (SES). STAR delivers the company’s industry-leading threat protection technologies, advanced security analytics, and investigations into new targeted attacks; CAML is Symantec’s center of excellence for advanced machine learning and artificial intelligence; and the Shared Engineering Services organization includes product security, product localization and internationalization, and engineering development tools.

BibTeX
@conference {215315,
author = {Alejandro Borgia},
title = {Automating the Discovery and Investigation of Targeted Attacks with {AI} and Machine Learning},
year = {2018},
address = {Atlanta, GA},
publisher = {{USENIX} Association},
month = may,
}