Our work on multi-probabilistic decision assessment for Android Malware detection has been accepted at 9th ACM Workshop on Artificial Intelligence and Security (AISec 2016). The paper is titled “Prescience: Probabilistic Guidance on the Retraining Conundrum for Malware Detection”.
We will be presenting a poster on our Android detection and classification framework titled “Barometer: Sizing Up Android Applications Through Statistical Evaluation” at S&P 2016. The differentiating factor of our work compared to run-of-the-mill classifiers would be that we assess each decision by the classifier statistically and use fitting measures to improve our classification model over time.
Our work on dynamic analysis of Android malware for classification of malware has been accepted at Mobile Security Technologies (MoST’ 2016).
I attended the INVEST workshop at Imperial College on 29th November and had a great time chatting with researchers from the software verification and testing community in the UK including Professor Phillipa Gardner, Dr. Cristian Cadar and Dr. Alastair Donaldson. Attended presentations on some very interesting projects on the application of formal methods and symbolic execution to software verification and testing.