Speaker "Siobhan Mcnamara" Details Back



Classifying spearphising: NLP to distinguish new acquaintances and targeted e-mail attacks


Targeted e-mail attacks have developed in sophistication to become the greatest security threat to organizations. However false positives, e-mails mistakenly blocked is not a price organizations can pay to improve their security. Measuring the interactions between known personnel is possible through historical training data. E-mails from strangers or new acquaintances presents a unique problem. There is no pattern of behavior to define what is normal in this relationship. We are developing models to better capture norms among strangers and distinguish attacks from those. This presentation will focus on the natural language processing component of the cold start problem. It will explore the hierarchical approach we are taking to develop lexicons of language specific to clusters of personnel in organizations that enable us to better classify strangers from attackers.


I am a Data scientist applying machine learning for email security and fraud detection at Agari. My background is in economics and behavioral research with a particular focus on risk perception and the behavioral nuances involved in decision making under risk and uncertainty.