Leading the team that keeps the Gmail inbox safe from spam, phishing & malware.

Build the vision and team for the research function at McAfee’s Data & Insights Group (previously McAfee Labs), driving research & development of McAfee’s future products, projects & programs.Projects:- Drive the effort for improving detection effectiveness of McAfee’s machine learning based anti-malware engine expanding coverage to new threats and greater predictive prowess.- Design & develop the next-generation analytics platform utilizing multi-enterprise product telemetry to identify and detect emerging threat patterns for timely protection.

Led the industry-leading research at McAfee for signature-less identification of malicious programs using Machine Learning which resulted in substantial improvement in zero-day detection efficacy of McAfee’s products, also allowing reduction in disk footprint leading to customer delight and retention. This is a key product component called Advanced Threat Protection which since 2017 is a highlighting part of McAfee’s both enterprise and consumer products. My contributions to the solution:- Method for Featurization of Behavioral Events of Programs.- Method for Incremental Clustering for Identification of Malware Variants in real-time.- Method for Signature-less Classification of Programs using Regression & Support Vector Machines.- Method for Profiling of Malicious Processes using Decision Trees (USPatent# 9323928)- Method for Identifying Malicious Programs based on Icon Similarity in Portable Executables.Led design and development of multiple high-impact endpoint & cloud projects at McAfee.Real Protect: Novel and industry-leading cloud-based Anti-Malware Solution for classification of objects using behavior-based and static features. Success of this system led to increased revenue and McAfee’s step into cloud-based products. Major contributions included:- Key Architect & Developer for scalable backend cloud in AWS for providing real-time classification to clients. Designed using the micro-service architecture allowing cost-effective independent scaling of components capable of handling throughputs of over 10,000 queries per second.- Collaborating with multiple-geo cross-functional teams including executives and product managers ensuring quality and timely delivery of the product.- Developer for classification & featurization modules in the endpoint client.

My work was to research and develop a prototype for detecting malicious processes using behavioral and static attributes of any process.It involved usage of Machine Learning techniques like Decision Tree and Support Vector Machines to generate rules for classification.