arXiv subjects

Martino Trevisan

Publications and source records attributed to Martino Trevisan.

22 records · Page 2Linked to original sources

arXiv2019

Uncovering the Flop of the EU Cookie Law

In 2002, the European Union (EU) introduced the ePrivacy Directive to regulate the usage of online tracking technologies. Its aim is to make tracking mechanisms explicit while increasing privacy awareness in users. It mandates websites to ask for explicit consent before using any kind of profiling methodology, e.g., cookies. Starting from 2013 the Directive is mandatory, and now most of European websites embed a "Cookie Bar" to explicitly ask user's consent. To the best of our knowledge, no study focused in checking whether a website respects the Directive. For this, we engineer CookieCheck, a simple tool that makes this check automatic. We use it to run a measurement campaign on more than 35,000 websites. Results depict a dramatic picture: 65% of websites do not respect the Directive and install tracking cookies before the user is even offered the accept button. In few words, we testify the failure of the ePrivacy Directive. Among motivations, we identify the absence of rules enabling systematic auditing procedures, the lack of tools to verify its implementation by the deputed agencies, and the technical difficulties of webmasters in implementing it.

cs.CY↗

arXiv2019

Big Data for Traffic Monitoring and Management

The last two decades witnessed tremendous advances in the Information and Communications Technologies. Beside improvements in computational power and storage capacity, communication networks carry nowadays an amount of data which was not envisaged only few years ago. Together with their pervasiveness, network complexity increased at the same pace, leaving operators and researchers with few instruments to understand what happens in the networks, and, on the global scale, on the Internet. Fortunately, recent advances in data science and machine learning come to the rescue of network analysts, and allow analyses with a level of complexity and spatial/temporal scope not possible only 10 years ago. In my thesis, I take the perspective of an Internet Service Provider (ISP), and illustrate challenges and possibilities of analyzing the traffic coming from modern operational networks. I make use of big data and machine learning algorithms, and apply them to datasets coming from passive measurements of ISP and University Campus networks. The marriage between data science and network measurements is complicated by the complexity of machine learning algorithms, and by the intrinsic multi-dimensionality and variability of this kind of data. As such, my work proposes and evaluates novel techniques, inspired from popular machine learning approaches, but carefully tailored to operate with network traffic.

cs.NI↗

arXiv2017

Re-designing Dynamic Content Delivery in the Light of a Virtualized Infrastructure

We explore the opportunities and design options enabled by novel SDN and NFV technologies, by re-designing a dynamic Content Delivery Network (CDN) service. Our system, named MOSTO, provides performance levels comparable to that of a regular CDN, but does not require the deployment of a large distributed infrastructure. In the process of designing the system, we identify relevant functions that could be integrated in the future Internet infrastructure. Such functions greatly simplify the design and effectiveness of services such as MOSTO. We demonstrate our system using a mixture of simulation, emulation, testbed experiments and by realizing a proof-of-concept deployment in a planet-wide commercial cloud system.

cs.NI↗

arXiv2017

Ethical issues of ISPs in the modern web

In recent years, ethical issues in the networking field are getting moreimportant. In particular, there is a consistent debate about how Internet Service Providers (ISPs) should collect and treat network measurements. This kind of information, such as flow records, carry interesting knowledge from multiple points of view: research, traffic engineering and e-commerce can benefit from measurements retrievable through inspection of network traffic. Nevertheless, in some cases they can carry personal information about the users exposed to monitoring, and so generates several ethical issues. Modern web is very different from the one we could experience few years ago; web services converged to few protocols (i.e., HyperText Transfer Protocol (HTTP) and HTTPS) and always bigger share of encrypted traffic. The aim of this work is to provide an insight about which information is still visible to ISPs in the modern web and to what extent it carries personal information. We show ethical issues deriving by this new situation and provide general guidelines and best-practices to cope with the collection of network traffic measurements.

cs.CY↗