Title : The Dynamics of Innocent Flesh on the Bone: Code Reuse Ten Years Later
| Presenter | Manolis Stamatogiannakis |
| Abstract | In 2007, Shacham published a seminal paper on Return-Oriented Programming (ROP), the first systematic formulation of code reuse. The paper has been highly influential, profoundly shaping the way we still think about code reuse today: an attacker analyzes the “geometry” of victim binary code to locate gadgets and chains these to craft an exploit. We challenge this perception and show that an attacker going beyond “geometry” (static analysis) and considering the “dynamics” (dynamic analysis) of a victim program can easily find function call gadgets even in the presence of state-of-the-art code-reuse defenses. |
Title : Using Recurrent Neural Networks to Predict Colorectal Cancer among Patients
| Presenter | Mark Hoogendoorn |
| Abstract | Development of predictive models from Electronic Medical Records (EMRs) is a far from trivial task. Especially the temporal nature of health records is an aspect that is often ignored yet of utmost importance. Additionally, data is extremely sparse. Previous research has shown that the identification of temporal patterns from EMR data can be highly beneficial in the prediction of colorectal cancer (CRC). In this presentation, I will talk about the application of recurrent neural networks to this problem, and more specifically Long Short Term Memory (LSTM) networks and Gated Recurrent Units (GRUs) to see whether these networks could learn such valuable temporal patterns themselves and generate accurate predictive models for CRC. Results show that we attain performance on par with state-of-the-art algorithms (while being outperformed by one). The eventual Area under the ROC Curve (AUC) obtained is 0.811. |