Adaptive Activity and Context Recognition using Multimodal Sensors in Smart Devices

in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Mobile Computing, Applications, and Services (2015, November)

The continuous development of new technologies has led to the creation of a wide range of personal devices embedded with an ever increasing number of miniature sensors. With accelerometers and ... [more ▼]

The continuous development of new technologies has led to the creation of a wide range of personal devices embedded with an ever increasing number of miniature sensors. With accelerometers and technologies such as Bluetooth and Wi-Fi, today's smartphones have the potential to monitor and record a complete history of their owners' movements as well as the context in which they occur. In this article, we focus on four complementary aspects related to the understanding of human behaviour. First, the use of smartwatches in combination with smartphones in order to detect different activities and associated physiological patterns. Next, the use of a scalable and energy-efficient data structure that can represent the detected signal shapes. Then, the use of a supervised classifier (i.e. Support Vector Machine) in parallel with a quantitative survey involving a dozen participants to achieve a deeper understanding of the influence of each collected metric and its use in detecting user activities and contexts. Finally, the use of novel representations to visualize the activities and social interactions of all the users, allowing the creation of quick and easy-to-understand comparisons. The tools used in this article are freely available online under a MIT licence. [less ▲]

Changing Mobility Behaviour through Recommendations

in Proceedings of the ACM Recsys CrowdRec Workshop 2015 (2015, September 19)

In this paper, we describe a road traffic behaviour and mobility case study that was implemented in June 2015 in the congested city of Luxembourg. We explain the development and deployment of the Gamified ... [more ▼]

In this paper, we describe a road traffic behaviour and mobility case study that was implemented in June 2015 in the congested city of Luxembourg. We explain the development and deployment of the Gamified mobile application Commutastic that offers users incentives to undertake after work activities. With Commutastic we try to persuade users to change their commuting time so as to avoid the evening peak. Furthermore we investigate the behaviour change with focus groups and questionnaires. The preliminary data indicates that behaviour change is possible and that traffic reduction can happen on a bigger scale. [less ▲]

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

in Ad Hoc Networks (2015)

Text entry on smart glasses A comparison of two input techniques

in 8th International Conference on Human System Interaction (HSI'2015) (2015, June)

This paper presents a comparative pilot usability study of Dasher and an on-screen keyboard on a head-mounted display. Interaction logging data was captured along with subjective responses (via the SUS ... [more ▼]

This paper presents a comparative pilot usability study of Dasher and an on-screen keyboard on a head-mounted display. Interaction logging data was captured along with subjective responses (via the SUS questionnaire). The results indicate that there is a strong need to develop text entry systems for smart glasses rather to simply adopt those that are already available. However, both approaches are useful when there is a need to enter private or sensitive data. [less ▲]

Network troubleshooting with SDN-RADAR (demo paper)

in Proc. of IFIP/IEEE International Symposium on Integrated Network Management (IM) (2015, May)

A Cell Dwell Time Model for Synthetic Population Generation from Call Detail Records

Scientific Conference (2015, April 08)

In this work we propose a novel Cell Dwell Time Model that can be used to generate a synthetic population. We introduce two new metrics to define the attractivity of cell sites based on global and ... [more ▼]

In this work we propose a novel Cell Dwell Time Model that can be used to generate a synthetic population. We introduce two new metrics to define the attractivity of cell sites based on global and individual parameters obtained via the analysis of the Data For Development (D4D) Call Detail Records (CDR). We rely on the shortest path road network to interconnect two distant cell sites. The resulting dwell time model can be used to compute accurate user trajectories even with partial information. This work represents a first step towards the generation of a synthetic population that can be used to perform a wide range of simulative studies to evaluate and optimize transportation networks. [less ▲]

SDN-RADAR: Network troubleshooting combining user experience and SDN capabilities

in Proc. of IEEE Conf. on Network Softwarization (NetSoft) (2015, April)

Towards Reinventing Online Privacy

in Berendt, Bettina; Engel, Thomas; Ikonomou, Demosthenes (Eds.) et al LNCS - Annual Privacy Forum 2015 - Bridging the gap between research and policy (2015)

Hacker’s Toolbox: Detecting Software-Based 802.11 Evil Twin Access Points

in Proceedings of the 12th Annual IEEE Consumer Communications & Networking Conference (CCNC 2015) (2015)

The usage of public Wi-Fi hotspots has become a common routine in our everyday life. They are ubiquitous and offer fast and budget-friendly connectivity for various client devices. However, they are ... [more ▼]

The usage of public Wi-Fi hotspots has become a common routine in our everyday life. They are ubiquitous and offer fast and budget-friendly connectivity for various client devices. However, they are exposed to a severe security threat: since 802.11 identifiers (SSID, BSSID) can be easily faked, an attacker can setup an evil twin, i.e., an access point (AP) that users are unable to distinguish from a legitimate one. Once a user connects to the evil twin, he inadvertently creates a playground for various attacks such as collection of sensitive data (e.g., credit card information, passwords) or man-in-the-middle attacks even on encrypted traffic. It is particularly alarming that this security flaw has led to the development of several tools that are freely available, easy to use and allow mounting the attack from commodity client devices such as laptops, smartphones or tablets without attracting attention. In this paper we provide a detailed overview of tools that have been developed (or can be misused) to set up evil twin APs. We inspect them thoroughly in order to identify characteristics that allow them to be distinguished from legitimate hardware-based access points. Our analysis has discovered three methods for detecting software-based APs. These exploit accuracy flaws due to emulation of hardware behavior or peculiarities of the client Wi-Fi hardware they operate on. Our evaluation with 60 hardware APs and a variety of tools on different platforms reveals enormous potential for reliable detection. Furthermore, our methods can be performed on typical client hardware within a short period of time without even connecting to a potentially untrustworthy access point. [less ▲]

PhishStorm: Detecting Phishing With Streaming Analytics

in IEEE Transactions on Network and Service Management (2014), 11(December), 458-471

Despite the growth of prevention techniques, phishing remains an important threat since the principal countermeasures in use are still based on reactive URL blacklisting. This technique is inefficient due ... [more ▼]

Despite the growth of prevention techniques, phishing remains an important threat since the principal countermeasures in use are still based on reactive URL blacklisting. This technique is inefficient due to the short lifetime of phishing Web sites, making recent approaches relying on real-time or proactive phishing URL detection techniques more appropriate. In this paper, we introduce PhishStorm, an automated phishing detection system that can analyze in real time any URL in order to identify potential phishing sites. PhishStorm can interface with any email server or HTTP proxy. We argue that phishing URLs usually have few relationships between the part of the URL that must be registered (low-level domain) and the remaining part of the URL (upper-level domain, path, query). We show in this paper that experimental evidence supports this observation and can be used to detect phishing sites. For this purpose, we define the new concept of intra-URL relatedness and evaluate it using features extracted from words that compose a URL based on query data from Google and Yahoo search engines. These features are then used in machine-learning-based classification to detect phishing URLs from a real dataset. Our technique is assessed on 96 018 phishing and legitimate URLs that result in a correct classification rate of 94.91% with only 1.44% false positives. An extension for a URL phishingness rating system exhibiting high confidence rate ( $>$ 99%) is proposed. We discuss in this paper efficient implementation patterns that allow real-time analytics using Big Data architectures such as STORM and advanced data structures based on the Bloom filter. [less ▲]