Real-time data about various traffic events and conditions-offences, accidents, dangerous driving, or dangerous road conditions-is crucial for safe and efficient transportation. Unlike roadside ...infrastructure data which are often limited in scope and quantity, crowdsensing approaches promise much broader and comprehensive coverage of traffic events. However, to ensure safe and efficient traffic operation, assessing trustworthiness of crowdsourced data is of crucial importance; this also includes detection of intentional or unintentional manipulation, deception, and spamming. In this paper, we design and demonstrate a road traffic event detection and source reputation assessment system for unreliable data sources. Special care is taken to adapt the system for operation in decentralized mode, using smart contracts on a Turing-complete blockchain platform, eliminating single authority over such systems and increasing resilience to institutional data manipulation. The proposed solution was evaluated using both a synthetic traffic event dataset and a dataset gathered from real users, using a traffic event reporting mobile application in a professional driving simulator used for driver training. The results show the proposed system can accurately detect a range of manipulative and misreporting behaviors, and quickly converges to the final trust score even in a resource-constrained environment of a blockchain platform virtual machine.
Diabetes mellitus has high prevalence in the ageing population and is often accompanied by other comorbidities, such as Alzheimer’s disease, and general disabilities, such as poor eyesight. These ...comorbidities have redefined ways in which patients use mHealth apps, including diabetes apps. The latter have proven benefits for monitoring blood glucose levels and insulin tracking in the general population. In this paper, we analyse a diabetes monitoring app DeStress Assistant (DeSA), which was developed as a part of an EU project and tested in a hospital setting. Due to the increasing number of older adults, we wanted to ensure the app was suitable for that demographic. Based on a number of supervised tests, we show that the app, which was developed with the help of workshops and feedback from tech-savvy patients and clinicians, is difficult to use by elderly users. We demonstrate that with a small number of changes it is possible to raise the usability of the app in a number of categories. We summarise the lessons learned in the discussion. Our findings demonstrate that special care needs to be taken when developing mHealth apps for the elderly population.
Cybersecurity research demands continuous monitoring of the dynamic threat landscape to detect novel attacks. Researchers and security professionals often deploy honeypot networks to intercept and ...examine real attack data. However, due to the volume and variety of the collected data, it is very challenging for security analysts to investigate the attacks, compare their characteristics and infer their potential connections. To this end, we propose a novel graph-based cyberattack model for storing, analyzing, and visualizing honeynet-captured attacks as the main contribution of our work. Our model enables attack graph analysis and presents the attack data analogous to the Cyber Kill Chain framework to enable intuitive visualizations. We construct the attack graph by decomposing the intercepted attacks into a set of unique entities (represented as nodes) and actions (represented as edges) and merge them into a global attack graph. We develop a user-centric, interactive attack analysis and visualization tool that leverages the proposed model to aid the heuristic cyberattack investigation. We describe the design and technical implementation of the developed model and visual-interactive tool in detail. Finally, we demonstrate the developed tools and validate the model in an analysis of real-world attack data captured on our own distributed honeypot platform. We use the attack model and (sub)graph visualizations to depict attack topologies, identify recurring attackers, and quantify detected malware types. We also leverage graph data science algorithms to uncover and rank malware distribution networks, reveal hidden links between the attackers, and cluster the attack entities to identify potential botnets.
In today's hyper-connected world, rich social data feeds can be obtained from various sources, including the data exhaust of many commonly used systems. In this paper, we analyze the social pulse, ...obtained from viewer activity in an IPTV network-we attempt to validate a framework for determining public opinion and public interest through implicit feedback of IPTV viewers. First, we address the hypothesis that implicit viewer feedback in the form of channel change events, paired with the content metadata, can be used to model viewers' opinion and interest. For this, we design a controlled experiment to collect explicit feedback by rating a set of general-interest news clips. In addition to collecting demographic information, we also survey viewers' opinion, interest, and the probability of channel change during each clip. Furthermore, we extract weighted feature vectors from the closed captions of the video; this data, combined with the reported probability of channel change, is used to build a model that classifies opinion in five categories based on the probability of channel change and content. Next, we build a simplified model that classifies opinion in five categories based on the interest, which shows a linear relationship, but further consideration of content, in this case, provides better accuracy and possibility to analyze anomalous cases. Finally, we discuss and analyze the applications of such models in large systems and the necessary modifications to scale the system and to ensure the adequate performance on massive IPTV event data streams.
Information and communication technologies have become the foundation of modem life due to their numerous advantages. However, their rapid introduction with an insufficient emphasis on security and ...protection unnecessarily exposes them to potential risks. in the paper, we focus on cybersecurity from the perspective of the growing amount of threats in modern networks. We describe the concept, operation, and purpose of a network telescope, i.e., a system that records unsolicited traffic to dark internet protocol addresses. We present the architecture of the system developed at the Faculty of Electrical Engineering, University of Ljubljana, and analyze the data collected in more than ten years of its operation. More than 2 billion events collected from 2011 onwards, exhibit an exponential trend of growth. Only five years ago, a vast majority of incoming packets was targeting ports of popular server management services (e.g., Telnet, SSH), while today the distribution is much more long-tailed and responds quickly to emerging vulnerabilities. We examine the nature of the collected data, describe the possible use cases, and present some data visualizations. Informacijsko-komunikacijske tehnologije so zaradi številnih prednosti postale temelj sodobnega življenja, vendar pa njihovo naglo uvajanje z nezadostnim poudarkom na zaščiti in varovanju po nepotrebnem izpostavlja sisteme potencialnim tveganjem. V tem članku se dotaknemo kibernetske varnosti z vidika naraščajoče količine groženj v internetnih omrežjih. Opišemo koncept, delovanje in namene uporabe omrežnega teleskopa, tj. sistema, ki beleži nepovabljen promet do temnih naslovov internetnega protokola. predstavimo arhitekturo sistema, razvitega na Fakulteti za elektrotehniko, ter analiziramo podatke, zbrane v več kot 10 letih njegovega delovanja. Več kot 2 milijardi zbranih dogodkov od leta 2011 prikazuje eksponenten trend rasti. Še pred 5 leti je večina dohodnih paketov targetirala storitve za upravljanje strežnikov (npr. Telnet, SSH), danes pa je porazdelitev protokolov mnogo bolj uravnotežena in se hitro odziva na aktualne ranljivosti. V prispevku opišemo naravo zbranih podatkov in možne načine njihove uporabe ter podamo nekaj vizualizacij.
This paper presents a case study on security and privacy implications on the design of a mobile application in digital health, the DeStress Assistant (DeSA) app, which utilizes sensing technologies ...and capabilities of the Internet of Things (IoT). An analysis of the applicable legislative framework is provided and selected challenges encountered during the app design are discussed, which are related with the practical implications of provisions of the international and national legislation for software applications in general as well as medical devices and handling of sensitive data in particular. We provide insights into design choices, including different possible scenarios for classification of a mobile app as a medical device and the pertaining legal risks the app developer is faced with as a consequence of possible legal obligations, and different possibilities of specifying the intended use. Also, we propose two designs of a mechanism that enables secure sharing of the patient’s health-related observations from the DeSA app with a medical professional within a treatment context. The first mechanism provides secure submission of health-related observations into a hospital information system, whereas the second mechanism enables secure short-term sharing of observations without storage.
We present a novel approach for providing a comprehensive operational picture of heterogeneous networks by collecting system information from physical, data-link, network and application layers using ...extended methods and mechanisms for OAM, which take into account particularities of persistent access heterogeneity and IoT. A heterogeneous OAM (H-OAM) framework is proposed with a toolset for streamlined failure detection and isolation, and automated performance measurement and monitoring. The framework combines extended standardized OAM toolsets for physical and data-link layers with multiple well-defined and recognized IP network layer toolsets, which introduces possibilities for a tactical view of the monitored system and quick root cause analysis with unified interpretation and cross-correlation of horizontal and vertical levels. A practical deployment of an H-OAM system is presented and its use is demonstrated in a live mobile IoT testbed environment where performance is a function of a wide variety of physical layer parameters that need to be tuned and monitored by the operator. Results of two concrete usage scenarios performed in cooperation with two largest Slovenian mobile operators demonstrate how continuity check and connectivity verification, and performance diagnostics are conducted for Web-based IoT applications and network services of a live operational environment.
We present our experience with design, development, deployment, and operation of a nation-wide network of mobile Internet measurement probes. Mobile internet is becoming increasingly important, with ...new technologies being deployed on a regular basis. In the last decade we have seen a transition over a multitude of data transmission technologies, from EDGE, UMTS, and HSPA to LTE, with 5G already on the horizon. This presents an extremely heterogeneous environment where problems are difficult to pinpoint, because of either the fast changing radio channel conditions, daily mobility of the user base, or a number of fallback technologies that are available at a specific location and chosen by the terminal itself. To quantify these conditions, we have developed a mobile internet measurement probe called QMON, which can be either statically deployed or used in drive measurements and is able to collect hundreds of key performance indicators on physical, network, and application layers of the network stack, acting at the same time as an event-driven real-time sensor network and a batch-mode detailed data collection device. In this paper we expose some of the design considerations and pitfalls; among them are the problems of managing and monitoring the remote probes that measure the same communication channel that is also used for their control.
We present a specification and a nationwide pilot implementation of a future public safety communication system. We propose a novel approach to survivable heterogeneous emergency communication ...systems, merging professional and commercial off-the-shelf (COTS) equipment, communicating over state-of-the-art mobile and satellite links. We explain the architecture and functional outline of an Advanced Emergency Response Communications System (A-ERCS), which was developed and integrated with professional, commercial, and ad hoc networks to provide survivable communications services and sensor-based applications to support public safety agencies in their day-to-day operation and disaster relief missions. Further, we present the results of a real-world pilot implementation, customized for fire fighter services in Slovenia, and discuss the outcomes of performance tests, showing how the proposed solution can be applied in public safety practice and how COTS technologies can be efficiently and reliably reused in this specific domain.
The assurance of quality of experience (QoE) and provisioning of high throughput of the system represent the main goals of future wireless and mobile networks. This paper presents novel and practical ...cross-layer QoE-aware radio resource allocation (RRA) algorithms for the downlink of a heterogeneous orthogonal frequency division multiple access (OFDMA) system. The objective of the proposed algorithms is to assure the appropriate level of QoE for each user of the system by incorporating application-layer parameters and subjective human perception of quality into the RRA process. We propose two user-oriented joint subcarrier and power allocation algorithms with low complexity for real-time and interactive services. The first algorithm dynamically allocates resources by assuring the same level of QoE to all users of the system, whereas the second algorithm introduces the efficient trade-off between the user's QoE and the spectral efficiency of the system. By considering application-layer parameters and user's perception of quality, high users' QoE and explicit control of data rates can be achieved. The numerical results show that the proposed algorithms achieve significant increase in the level of QoE compared to previous works, a fair distribution of capacity among users and near to optimal solution of QoE for the OFDMA system.
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