iHub-Data organized a seminar on 11 February to mark International Women in Science and Technology Day. The seminar included two invited lectures by eminent women scientists. 

The first talk was on Attribute-based Access Control Paradigm  by Prof. Vijayalakshmi Atluri, Rutgers University partnered with Dr. Gunjan Batra, Kennesaw State University. 

Summary: Attribute-based Access Control (ABAC) Mining that automatically discovers ABAC policies and incrementally maintains them. The flexibility, scalability, portability, dynamic nature and identity-less features of Attribute Based Access Control (ABAC) make it an attractive choice for enforcing fine-grained access. However, in order to realize the true benefit of ABAC, it is necessary to develop mechanisms to effectively configure, deploy, maintain, and manage it.

The second talk was on Cybersecurity and Machine Learning by Prof. Bhavani Thuraisingham, University of Texas, Dallas. 

Summary: Machine Learning and Security are being integrated to solve security and privacy challenges. For example, machine learning techniques are being applied to solve security problems such as malware analysis and insider threat detection. However, there is also a concern that the machine learning techniques themselves could be attacked. Therefore, the machine learning techniques are being adapted to handle adversarial attacks. Furthermore, due to privacy violations caused by machine learning, privacy enhanced machine learning techniques are being developed. To assess the developments on the integration of Data Science/Machine Learning and Security over the past decade and apply them to the Internet of Things, the first part of the presentation will examine the developments on applying Data Science techniques for detecting cyber security problems such as insider threat detection as well as the handling attacks to machine learning techniques. Some developments on privacy aware and policy-based data management frameworks were also discussed.