Three ROC master interns will present their work in progress in the frame of their master thesis research, on March 26, 2021, at 14:00. Please drop an email to seccis AT cnam DOT fr if you want to join.

Speaker: Maria Isabella Viola

Title: A Correlation analysis between human mobility and COVID-19 spreading 

Abstract:
Starting from December 2019 the world has faced an unprecedented health crisis caused by the new Coronavirus (COVID-19) due to the SARS-CoV-2 pathogen. Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Within this topic, the aim of our work is to quantify the effect of population mobility habits in the spread of the Coronavirus in France. Correctly modeling and quantifying human mobility is critical or improving epidemic control, but may be hindered by data incompleteness or unavailability. In France, data on excess deaths, an indirect indicator which is generally considered to be less affected by national and regional assumptions, are available at department and municipality level, respectively. Using this information together with anonymised and aggregated mobile phone data, this study aims to find a correlation between Human mobility and COVID-19 transmissions. The most challenging part of this work involves the development of a realistic mobility model. For the first part, a model was created based on simple statistical estimators. Next, a mobility model will be developed through the use of Machine and deep learning techniques. 

Bio:  Maria Isabella Viola  was born in Piacenza, Italy in 1996. She obtained a biomedical engineering bachelor at Politecnico di Milano in 2018, and then enrolled in a master of science in mathematical engineering at Politecnico di Milano, with a specialization in applied statistics, and an expected graduation in 2021. Her current thesis work at Cnam is about qualifying the correlation between COVID-19 spreading and human mobility under the advisory of Françoise Sailhan and Stefano Secci. 


Speaker: Eugenio Cortesi

Title: A new approach for Bitcoin Pool-hopping detection.

Abstract: We conducted an empirical analysis of pool-hopping behavior in 5 mining pools with higher hash rates during the three-month period. Mining pools emerged as key players in ensuring that the Bitcoin system remains secure, viable, and stable. Individual miners join mining pools to benefit from more predictable income. Many questions remain about the pool-hopping phenomenon, particularly about how it can be defined today. The phenomenon itself has changed over time, abandoning the connotation of being opportunistic. Indeed, following the implementation of new reward methods and miner retention policies, miners are not earning more at the expense of their peers. Still it can be defined as strategic behavior influenced by the attractiveness of the pool, but with the sole purpose of receiving the most efficient reward possible. As a result, it now appears tacitly accepted and commonly spread among those who mine. The only actor for whom this phenomenon remains inconvenient are the mining pools themselves, which undergo frequent changes in hash rate. In this paper, we propose a heuristic strategy to analyze the dynamics of the system that consists of several procedures. The first step aims to extract the payout stream from the mining pools and assign the author pool of each reward based on a coin ownership methodology. In the second, we uniquely identify users within the system through the use and adaptation of known heuristics. The third step, focuses on examining the realistic dynamics of miners’ remuneration, which goes beyond reward methods that pay per validated block. To this end, a characterization based on the epochs of work performed by miners over time is introduced.Ultimately, the evaluation leads us to detect the extent to which miners move between pools and apply simultaneous work. Ultimately, the evaluation leads us to detect the extent to which miners move between pools and apply concurrent work. Ultimately, the evaluation leads us to detect the extent to which miners move between pools and apply concurrent work.  In particular, our results aim to show that today’s behavior is harmless, even if driven by the strategy of those who want to make the most of mining.

Bio: Eugenio Cortesi was born in Brescia, Italy in 1995. He obtained his computer engineering bachelor degree in 2018 and is about to get his Master degree in Computer Engineering in April 2021 with a specialization in ICT engineering, businness and innovation. He is currently working at Cnam on his Master thesis on Bitcoin analytics under the advisory of Sami Taktak and Stefano Secci.


Speaker: Mario Patetta

Title: NetFPGA design for on-line anomaly detection in IP traffic streams

Abstract: 
We will present the work in progress in using  P4 programming language to configure a NetFPGA Sume board to run IP anomaly detection algorithms at line-rate as a network switch.

Bio:  Mario Patetta was born in Rome in 1996, and obtained a bachalor in electronic engineering in 2018 from University of Rome II  – Tor Vergata, Italy. He is a master student in Electronic Engineering at the same university and is currently doing a master internship at Cnam on embedded systems for smart-NICs under the advisory of Sami Taktak and Stefano Secci.

Interns seminars on COVID mobility modeling, Bitcoin analytics & Smart-NICs – March 26, 2021
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