Dove e quando

Speaker: Alessio Merlo Time: 2:30PM Title: Phishing attacks on modern Android Abstract: Modern versions of Android have introduced a number of features in the name of convenience. This talk discusses how two of these features, mobile password managers and Instant Apps, can be abused to make phishing attacks that are significantly more practical than existing ones. We have studied the leading password managers for mobile and we uncovered a number of design issues that leave them open to attacks. For example, we show it is possible to trick password managers into auto-suggesting credentials associated with arbitrary attacker-chosen websites. We then show how an attacker can abuse the recently introduced Instant Apps technology to allow a remote attacker to gain full UI control and, by abusing password managers, to implement an end-to-end phishing attack requiring only few user's clicks. Short bio: Alessio Merlo (MSc. 2005, Ph.D. 2010) is a Senior Assistant Professor (RTD-b) at DIBRIS, University of Genoa. He is the head of the Mobile Security research group, hosted at the Computer Security Lab. His main research interests include the definition of novel methodologies for the static and dynamic analysis of mobile applications, as well as techniques for the security assessment of mobile OSes, with a specific focus on the Android platform. Speaker: Annalisa Barla Time: 3:00PM Title: Python in medicine: signal processing - learning and visualization of temporal data Abstract: The analysis of high dimensional time series is nowadays of wide interest, not only in many fields of science but also for more practical and technical applications in industry. Python represents a convenient and easy way to perform in optimal time mathematical operations, integrate signal processing tools, import external libraries, integrate the whole preprocessing procedure with learning tools, visualize nicely/export through Bokeh for third parts which are not familiar to computers. In this talk I will describe a joint work to make sense out of electroencephalography data for the identification of the epileptogenic area in focal epilepsy patients. Short bio: Annalisa Barla is Associate Professor of Computer Science at the University of Genoa, Italy. She received a master’s degree in Physics (2001) and a PhD in Computer Science (2005), both at the University of Genoa, working on kernel functions engineering for regularization methods in machine learning applied to image content understanding. As a PhD student she also trained in biomedical image analysis during an internship at Siemens Research Corporate (Princeton, USA). Durinf a post-doctoral fellowship at Fondazione Bruno Kessler (Trento, Italy 2005-2007), she started her research in computational biology. She then moved back to the University of Genoa (2007-2011), leading a research team of PhD students and post-doctoral fellows working on machine learning applied to biomedical data. Her main areas of interest are in the field of data science. She has been working in the past decade on machine learning methods for variable selection with sparse regularization and reproducible and robust methods in the small n large p setting. Currently she is expanding her scientific interest towards the understanding and visualization of complex structured data. She is author and co-author of about 50 peer reviewed journal and conference papers.