Letizia Clementi, Autore presso NECSTLab

21Nov 2018 by Letizia Clementi

NECSTLab 2018-2019, NECSTCamp, Innovative Teaching and NGCX: a new exciting year

The new academic year has started and at NECSTLab we are already working hard on both new and old projects. First of all, the NECSTCamp - our holistic approach towards students personal development as both persons and future engineers - is renovated. During the last months, we devoted a special attention to understand how the project could become scalable,while not losing the focus on students’ individual needs. By Sara Notargiacomo and Marco D. Santambrogio, respectively Technology Trasfer Manager and RADRL @NECSTLab, Politecnico di Milano Goal Definition Starting from this year, we are devoting a special attention to help students defining research, teaching and soft skills development goals. For this reason each students is mentored individually at least four times per academic year. This is a crucial part of their…

21Jun 2018 by Letizia Clementi

Who Said Academic Research Can’t Go to Market? Studying and Improving Technology Transfer Processes

Scientific research and industry are often perceived as a dichotomy, two inconciliable world dumb to never understand each other. However, when scientific research is not successfully transferred to the market, it does not fully leverage its innovation potential and does not impact on people’s lives. By Sara Notargiacomo Technology Transfer Manager @NECSTLab, Politecnico di Milano The main reason of such a gap can be found in their different time frame and incentive system. Indeed, the long period perspective of academic research is unsuitable to match with companies short-term necessities and go-to-market strategies. Furthermore, researchers do not always foresee the true potential of their research projects because they lack of business and commercialization skills. Moreover, they are often asked to postpone the publication of their work in order to comply with…

29Mar 2018 by Letizia Clementi

CONDOR: Convolutional Neural Networks Dataflow Optimization Using Reconfigurable Hardware

Condor is an end-to-end framework to implement Convolutional Neural Networks on FPGA, that does not require the user to have experience in FPGA programming. The framework is able to interpret models from the well-known deep learning engine Caffe. By Giuseppe Natale PhD student @Politecnico di Milano The recent years have seen a rapid diffusion of deep learning algorithms as Convolutional Neural Networks (CNNs) and, as a consequence, an intensification of industrial and academic research focused on optimizing their implementation. Different computing architectures have been explored and, among all of them, Field Programmable Gate Arrays (FPGAs) seem to be a very attractive choice, since they can deliver sustained performances with high power efficiency, as CNNs can be directly mapped onto hardware and still offer flexibility thanks to their programmability. Nevertheless, the…

22Mar 2018 by Letizia Clementi

I’m not malicious, detection of evasive Android malware

The increasing popularity of the smartphones attracted lots “bad actors” that wants to spread malicious software into the ecosystem for profit. To avoid being detected and maximize profit, malware uses evasive techniques. We propose an approach to combat evasive malware. By Chengyu Zheng PhD student @Politecnico di Milano How to avoid being detected With over 500 million devices and an estimated 84% market share, Android-based devices are the main target for cyber-criminals. In addition to the alarming amount of malware families and samples, evasive techniques used by malwares are becoming more and more sophisticated. With the high amount of new applications being released every month, “app store” maintainer are struggling to find a reliable solutions to analyze apps in order to recognize and isolate malicious ones. Techniques used to analyze…

08Mar 2018 by Letizia Clementi

FROST: a common backend to accelerate Domain Specific Languages on FPGA

Domain Specific Languages are gaining more and more interest thanks to the significant level of performance they can reach on different architectures. FROST is a common backend able to accelerate on FPGA applications developed in different DSLs. By Emanuele Del Sozzo Ph.D. student @ Politecnico di Milano Due to the reaching of the end of Dennard scaling and Moore’s law, we are experiencing a growing interest towards Heterogeneous System Architectures (HSAs) as a promising solution to boost performance and, at the same time, reduce power consumption. The combination of different hardware accelerators, like GPUs, FPGAs, and ASICs, along with CPUs, allows to choose the most suitable architecture for a specific task, and, for this reason, many high-performance systems are currently taking advantage of heterogeneity. [caption id="attachment_506" align="aligncenter" width="300"] Example…

01Mar 2018 by Letizia Clementi

Breaking… the laws of robotics: attacking industrial robots

Industrial robots are everywhere: what happens if they get compromised? Is this hard? Are they attractive for attackers? How can we improve their security? To answer these questions, last year we studied the security landscape of an industrial robot and we analysed (and compromised) a widespread robot. By Marcello Pogliani PhD student at the NECSTLab, working on Systems Security Industrial robots are drastically evolving: on one side, “caged” giant robots are being complemented by smaller, “collaborative” models designed to share the workspace with human workers; on the other side, they are more “intelligent”, for example, by means of an improved interconnection for tasks such as remote maintenance, and integration with information systems. This means that robots, once “air-gapped”, are now exposed to hostile avenues. What happens (Skynet aside) if…