Walter Bronzi

BotCloud: Detecting botnets using MapReduce

Botnets are a major threat of the current Internet. Understanding the novel generation of botnets relying on peer-to-peer networks is crucial for mitigating this threat. Nowadays, botnet traffic is mixed with a huge volume of benign traffic due to almost ubiquitous high speed networks. Such networks can be monitored using IP flow records but their forensic analysis form the major computational bottleneck. We propose in this paper a distributed computing framework that leverages a host dependency model and an adapted PageRank [1] algorithm. We report experimental results from an open-source based Hadoop cluster [2] and highlight the performance benefits when using real network traces from an Internet operator.

Bluetooth Low Energy: An alternative technology for VANET applications

Vehicles are getting increasingly connected. Several technologies have emerged over the last decade that allow cars to communicate with each other and with the Internet. In this paper we propose to use the new Bluetooth Low Energy (BLE) standard as an alternative technology to exchange data between vehicles. By the means of experiments we show that smartphones with BLE radios can be used to send information at low latency from one car to another even while driving. A communication range of up to 100m can be achieved depending on the scenario and environment. Those promising first results are then used as basis for discussion to identify the potential of BLE for different types of vehicular applications.

Bluetooth Low Energy performance and robustness analysis for Inter-Vehicular Communications

Bluetooth Low Energy (BLE) is quickly and steadily gaining importance for a wide range of applications. In this paper we investigate the potential of BLE in a vehicular context. By means of experiments, we first evaluate the characteristics of the wireless channel, then we define a set of driving scenarios to analyse how BLE is affected by varying speed, distance and traffic conditions. We found that the maximum communication range between two devices can go beyond 100?m and that a robust connection, capable of handling sudden signal losses or interferences, can be achieved up to a distance of 50?m even for varying traffic and driving conditions. We then present a proof-of-concept mobile application for off-the-shelf smartphones that can be used to transmit data over multiple hops. Next, we analyse how BLE handles other interferences on the same frequency band by building and validating an interference testbed based on the IEEE 802.11 technology. Finally we discuss the advantages and limitations of BLE for Inter-Vehicular Communications (IVC) and propose potential applications.

Bluetooth low energy for inter-vehicular communications

Bluetooth Low Energy (BLE) is quickly and steadily gaining importance for a wide range of applications. In this paper we investigate the potential of BLE in a vehicular context. By means of experiments, we first evaluate the characteristics of the wireless channel, then we define a set of driving scenarios to analyze how BLE is affected by varying speed, distance and traffic conditions. We found that the maximum communication range between two devices can go beyond 100 meters and that a robust connection can be achieved up to a distance of 50 meters even for varying traffic and driving conditions. Next, we present a proof-of-concept mobile application for off-the-shelf smartphones that can be used to transmit data over multiple hops. Finally we discuss the advantages and limitations of BLE for Inter-Vehicular Communications (IVC) and propose potential applications.

Characterizing User Mobility Using Mobile Sensing Systems

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allows us to assess human behavior and movement at different levels. In this article, extended from previous work, we focus on the concept of human mobility and explore how we can exploit a dataset collected opportunistically from multiple participants. In particular, we study how the different sensor groups present in most commercial smart devices can be used to deliver mobility information and patterns. In addition to traditional motion sensors that are obviously important in this field, we are also exploring data from physiological and environmental sensors, including new ways of displaying, understanding, and analyzing data. Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. We finally offer a mobility assistant that can represent different user characteristics anonymously, based on a combination of Wi-Fi, activity data, and graph theory.

Towards characterizing Bluetooth discovery in a vehicular context

Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables implementing Bluetooth Smart technology (Low Energy) are released everyday. In particular, the ever increasing number of discoverable devices both inside and outside a populated area gives us an encouraging insight on future research directions for this technology. In this paper, based on a sensing system developed as an Android application, we evaluate Bluetooth Classic and Low Energy discovery characteristics from a vehicular perspective. By recording information about devices nearby (e.g. the number of discovered devices, their signal strength, manufacturer information) and the GPS location we can derive interesting information about a drivers situation, as well as his/her environment. Presented results indicate that the amount of discovered devices and signal strengths are dependent on velocity and road category. Finally, future work and discussions address potential use-case applications based only on Bluetooth discovery, such as low energy and privacy friendly road and traffic context awareness. The sensing system used in this article is free online under the MIT License.