On the Personalization of Personal Networks - Service Provision Based on User Profiles

In this paper, we present a user profile definition scheme featuring context awareness. Though the scheme has been designed to meet the needs of web applications deployed over heterogeneous devices, emphasis is given in the deployment of the profile scheme over Personal Networks (PNs), as the personalization of the deployed applications and services in PN environments is of great importance. The proposed scheme is presented as part of an integrated framework for user profile management that takes into account (and is therefore compliant to) the existing standardization attempts. The overall architecture and description of the profile management framework, taking into account security issues inside Personal Networks, is presented. The paper concludes by showcasing how user profiles have been incorporated in a selected pilot service of the EU IST research project MAGNET Beyond

An evaluation study of clustering algorithms in the scope of user communities assessment

AbstractIn this paper, we provide the results of ongoing work in Magnet Beyond project, regarding social networking services. We introduce an integrated social networking framework through the definition or the appropriate notions and metrics. This allows one to run an evaluation study of three widely used clustering methods (k-means, hierarchical and spectral clustering) in the scope of social groups assessment and in regard to the cardinality of the profile used to assess users’ preferences. Such an evaluation study is performed in the context of our service requirements (i.e. on the basis of equal-sized group formation and of maximization of interests’ commonalities between users within each social group). The experimental results indicate that spectral clustering, due to the optimization it offers in terms of normalized cut minimization, is applicable within the context of Magnet Beyond socialization services. Regarding profile’s cardinality impact on the system performance, this is shown to be highly dependent on the underlying distribution that characterizes the frequency of user preferences appearance. Our work also incorporates the introduction of a heuristic algorithm that assigns new users that join the service into appropriate social groups, once the service has been initialized and the groups have been assessed using spectral clustering. The results clearly show that our approach is able to adhere to the service requirements as new users join the system, without the need of an iterative spectral clustering application that is computationally demanding

Performance of Secure Boot in Embedded Systems

With the proliferation of the Internet of Things (IoT), the need to prioritize the overall system security is more imperative than ever. The IoT will profoundly change the established usage patterns of embedded systems, where devices traditionally operate in relative isolation.Internet connectivity brought by the IoT exposes such previously isolated internal device structures to cyber-attacks through the Internet, which opens new attack vectors and vulnerabilities. For example, a malicious user can modify the firmware or operating system by using a remote connection, aiming to deactivate standard defenses against malware. The criticality of applications, for example, in the Industrial IoT (IIoT) further underlines the need to ensure the integrity of the embedded software. One common approach to ensure system integrity is to verify the operating system and application software during the boot process. However, safety-critical IoT devices have constrained boot-up times, and home IoT devices should become available quickly after being turned on. Therefore, the boot-time can affect the usability of a device.This paper analyses performance trade-offs of secure boot for medium-scale embedded systems, such as Beaglebone and Raspberry Pi. We evaluate two secure boot techniques, one is only software-based, and the second is supported by a hardware-based cryptographic storage unit.For the software-based method, we show that secure boot merely increases the overall boot time by 4 %.Moreover, the additional cryptographic hardware storage increases the boot-up time by 36 %

Developing a Guideline of Unmanned Aerial Vehicle’s Acquisition Geometry for Landslide Mapping and Monitoring

Remote sensing data and techniques are widely used for monitoring and managing natural or man-made disasters, due to their timeliness and their satisfactory accuracy. A key stage in disaster research is the detailed and precise mapping of an affected area. The current work examines the relationship that may exist between the acquisition geometry of Unmanned Aerial Vehicle (UAV) campaigns and the topographic characteristics of an investigated area, toward landslide mapping and monitoring that is as accurate as possible. In fact, this work, concerning the systematic research of the acquisition geometry of UAV flights over multiple active landslides, is conducted for the first time and is focused on creating a guideline for any researcher trying to follow the UAV photogrammetric survey during landslide mapping and monitoring. In particular, UAV flights were executed over landslide areas with different characteristics (land cover, slope, etc.) and the collected data from each area were classified into three groups depending on UAV acquisition geometry, i.e., nadir imagery, oblique imagery, and an integration of nadir and oblique imagery. High-resolution orthophotos and Digital Surface Models (DSMs) emerged from the processing of the UAV imagery of each group through structure-from-motion photogrammetry (SfM). Accuracy assessment was carried out using quantitative and qualitative comparative approaches, such as root mean square error calculation, length comparison, and mean center estimation. The evaluation of the results revealed that there is a strong relationship between UAV acquisition geometry and landslide characteristics, which is evident in the accuracy of the generated photogrammetric products (orthophotos, DSMs). In addition, it was proved that the synergistic processing of nadir and oblique imagery increased overall centimeter accuracy

Timely and Low-Cost Remote Sensing Practices for the Assessment of Landslide Activity in the Service of Hazard Management

Landslides are among the most dangerous and catastrophic events in the world. The increasing progress in remote sensing technology made landslide observations timely, systematic and less costly. In this context, we collected multi-dated data obtained by Unmanned Aerial Vehicle (UAV) campaigns and Terrestrial Laser Scanning (TLS) surveys for the accurate and immediate monitoring of a landslide located in a steep and v-shaped valley, in order to provide operational information concerning the stability of the area to the local authorities. The derived data were processed appropriately, and UAV-based as well as TLS point clouds were generated. The monitoring and assessment of the evolution of the landslide were based on the identification of instability phenomena between the multi-dated UAV and TLS point clouds using the direct cloud-to-cloud comparison and the estimation of the deviation between surface sections. The overall evaluation of the results revealed that the landslide remains active for three years but is progressing particularly slowly. Moreover, point clouds arising from a UAV or a TLS sensor can be effectively utilized for landslide monitoring with comparable accuracies. Nevertheless, TLS point clouds proved to be denser and more appropriate in terms of enhancing the accuracy of the monitoring process. The outcomes were validated using measurements, acquired by the Global Navigation Satellite System (GNSS)

Timely and Low-Cost Remote Sensing Practices for the Assessment of Landslide Activity in the Service of Hazard Management

Landslides are among the most dangerous and catastrophic events in the world. The increasing progress in remote sensing technology made landslide observations timely, systematic and less costly. In this context, we collected multi-dated data obtained by Unmanned Aerial Vehicle (UAV) campaigns and Terrestrial Laser Scanning (TLS) surveys for the accurate and immediate monitoring of a landslide located in a steep and v-shaped valley, in order to provide operational information concerning the stability of the area to the local authorities. The derived data were processed appropriately, and UAV-based as well as TLS point clouds were generated. The monitoring and assessment of the evolution of the landslide were based on the identification of instability phenomena between the multi-dated UAV and TLS point clouds using the direct cloud-to-cloud comparison and the estimation of the deviation between surface sections. The overall evaluation of the results revealed that the landslide remains active for three years but is progressing particularly slowly. Moreover, point clouds arising from a UAV or a TLS sensor can be effectively utilized for landslide monitoring with comparable accuracies. Nevertheless, TLS point clouds proved to be denser and more appropriate in terms of enhancing the accuracy of the monitoring process. The outcomes were validated using measurements, acquired by the Global Navigation Satellite System (GNSS)

Developing a Guideline of Unmanned Aerial Vehicle’s Acquisition Geometry for Landslide Mapping and Monitoring

Remote sensing data and techniques are widely used for monitoring and managing natural or man-made disasters, due to their timeliness and their satisfactory accuracy. A key stage in disaster research is the detailed and precise mapping of an affected area. The current work examines the relationship that may exist between the acquisition geometry of Unmanned Aerial Vehicle (UAV) campaigns and the topographic characteristics of an investigated area, toward landslide mapping and monitoring that is as accurate as possible. In fact, this work, concerning the systematic research of the acquisition geometry of UAV flights over multiple active landslides, is conducted for the first time and is focused on creating a guideline for any researcher trying to follow the UAV photogrammetric survey during landslide mapping and monitoring. In particular, UAV flights were executed over landslide areas with different characteristics (land cover, slope, etc.) and the collected data from each area were classified into three groups depending on UAV acquisition geometry, i.e., nadir imagery, oblique imagery, and an integration of nadir and oblique imagery. High-resolution orthophotos and Digital Surface Models (DSMs) emerged from the processing of the UAV imagery of each group through structure-from-motion photogrammetry (SfM). Accuracy assessment was carried out using quantitative and qualitative comparative approaches, such as root mean square error calculation, length comparison, and mean center estimation. The evaluation of the results revealed that there is a strong relationship between UAV acquisition geometry and landslide characteristics, which is evident in the accuracy of the generated photogrammetric products (orthophotos, DSMs). In addition, it was proved that the synergistic processing of nadir and oblique imagery increased overall centimeter accuracy

The Influence of the DSM Spatial Resolution in Rockfall Simulation and Validation with In Situ Data

Remote sensing constitutes an advantageous tool towards the landslide/rockfall susceptibility mapping by incorporating optical satellite or radar data and photogrammetric data in Geographical Information System environment. A plethora of rockfall data can be derived by gigital surface models (DSMs). This article focuses on the effect of the spatial resolution of DSMs in rockfall investigations solely. DSMs with pixel size ranging from 5 cm to 90 m were taken into account for the study of three different rockfall events occurring in Western Greece, namely, at Moira, Myloi and Platiana settlements. Elevation profiles along the rockfall bodies were created from the diverse DSMs in GIS environment. Then, these profiles were implemented into the RocFall software for 2D rockfall simulations. The produced simulations were evaluated against their spatial resolution of DSMs and were confirmed with field observations and measurements. The ultimate scope of this paper is to conclude to the most appropriate DSM for rockfall simulations via RocFall software. It is observed that DSMs with high spatial resolution depicted a detailed and realistic topography, while DSMs with coarse/low resolution flattened the surface roughness. As rockfall simulations are linked to slope profile, this observation has an impact on RocFall outcomes. According to this study the most appropriate DSM, pertaining to this type of research, is the UAV, which produces the more accurate and realistic results. These results were assessed through the use of in situ measurements taken by the real rockfall events

An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece

Assessment of landslide hazard across mountains is imperative for public safety. Pre- and post-earthquake landslide mapping envisage that landslides show significant size changes during earthquake activity. One of the purposes of earthquake-induced landslide investigation is to determine the landslide state and geometry and draw conclusions on their mobility. This study was based on remote sensing data that covered 72 years, and focused on the west slopes of the Skolis Mountains, in the northwest Peloponnese. On 8 June 2008, during the strong Movri Mountain earthquake (Mw = 6.4), we mapped the extremely abundant landslide occurrence. Historical seismicity and remote sensing data indicate that the Skolis Mountain west slope is repeatedly affected by landslides. The impact of the earthquakes was based on the estimation of Arias intensity in the study area. We recognized that 89 landslides developed over the last 72 years. These landslides increased their width (W), called herein as inflation or their length (L), termed as enlargement. Length and width changes were used to describe their aspect ratio (L/W). Based on the aspect ratio, the 89 landslides were classified into three types: I, J, and Δ. Taluses, developed at the base of the slope and belonging to the J- and Δ-landslide types, are supplied by narrow or irregular channels. During the earthquakes, the landslide channels migrated upward and downward, outlining the mobility of the earthquake-induced landslides. Landslide mobility was defined by the reach angle. The reach angle is the arctangent of the landslide’s height to length ratio. Furthermore, we analyzed the present slope stability across the Skolis Mountain by using the landslide density (LD), landslide area percentage (LAP), and landslide frequency (LF). All these parameters were used to evaluate the spatial and temporal landslide distribution and evolution with the earthquake activity. These results can be considered as a powerful tool for earthquake-induced landslide disaster mitigatio