Five ECE Faculty are 2020 Spring Research Incubation Awardees
By Colbi Edmonds
The Hariri Institute for Computing announced their 2020 Spring Research Incubation Awards to faculty who have the potential to define new areas of research; five ECE faculty members are authors or co-authors of these incubation projects.
Professor David Starobinski is the PI of the Automated Threat Modeling for Connected Vehicles research team, which will investigate challenges surrounding compromised vehicles that may send forged safety messages. This can potentially harm other road participants who are in the vicinity of the vehicle. In order to combat this problem, Starobinski’s team will explore and expand the use of open-source threat modeling methods to detect dangers in the vehicular environment.
Manuel Egele is the PI of the reFuzz: Reusing Fuzzing Results to Improve Security Assessments project. As the cyber-security of products has been a growing concern for manufacturers, various
security assessment and analysis tools have been developed. Premiere among them is fuzzing, a repeated invocation of a Program Under Test (PUT) on random inputs to elicit erroneous program behavior. Egele is working toward fuzzers that will work with leverage security knowledge of previous fuzzing experiments, and will specifically aim to have fuzzers assess newly added codes or modified functionality in a PUT rather than codes that already exist.
Sahar Sharifzadeh and Brian Kulis are co-PIs in the Multi-scale Modeling of Complex Interfaces Aided by Machine Learning team, which will investigate the complex interfaces in material systems. Sharifzadeh and Kulis will work together with PI Emily Ryan to create a multi-scale modeling framework leveraging state-of-the-art machine learning tools to stimulate and understand the fundamental physics at the interface, with the goal of designing improved material systems.
Gianluca Stringhini is a co-PI of the Towards Developing Computational Models to Predict the Spreading of Radicalizing Content on the Web project. As the spread of radicalized content on social media by extremist groups is continuously growing, computational methods are needed to identify such content. The project will seek a solution to this problem by qualitatively labeling the extremist content and quantifying its spread. Stringhini will collaborate with lead PI Jessica Stern from BU’s Pardee School of Global Studies in radical online content case studies, especially to identify influential hotspots in spreading such content.