George Drosatos

Athena-Research and Innovation Center in Information, Communication and Knowledge Technologies · Institute for Language and Speech Processing

The COVID-19 pandemic, a period of great turmoil, was coupled with the emergence of an “infodemic”, a state when the public was bombarded with vast amounts of unverified information from dubious sources that led to a chaotic information landscape. The excessive flow of messages to citizens, combined with the justified fear and uncertainty imposed b...

This paper investigates the impact of COVID-19 on tourists’ attitudes regarding their decision to go on holidays and to classify them into groups based on their attitudes. The study aims to explore the effect of the pandemic on tourists’ behaviour in a context where tourism plays a significant role from a cultural and economic perspective. Therefor...

During the COVID-19 pandemic, social networks were flooded with overwhelming information. This study focused on the interaction between science and society as this took place via Twitter. State of the art algorithmic sentiment analysis was employed to examine the communication between pharmaceutical companies and the public, to analyze the profile...

This paper contributes to a better understanding of a system of pandemic knowledge exchanges. Therefore, three different case studies conducted in Germany, Greece, and Turkiye and executed in multiple countries were analyzed in the context of Mode 3 knowledge production and the Quintuple Helix system. While the Quintuple Helix system describes the...

The classic example of machine learning is based on isolated learning—a single model for each task using a single dataset [...]

Immersive technologies are revolutionary technological advancements that offer users unparalleled experiences of immersion in a virtual or mixed world of virtual and real elements. In such technology, user privacy, security, and anonymity are paramount, as users often share private and sensitive information. Therefore, user authentication is a crit...

The tourism sector, globally, was one of the largest markets of the twenty-first century, until the world faced the COVID-19 pandemic. Regarding the impact of the crisis on the hospitality industry of all countries for the 3rd week of March 2020, compared to the corresponding week in 2019, the number of visitors has decreased significantly by 50% o...

In this work, we present a machine learning approach for predicting early dropouts of an active and healthy ageing app. The presented algorithms have been submitted to the IFMBE Scientific Challenge 2022, part of IUPESM WC 2022. We have processed the given database and generated seven datasets. We used pre-processing techniques to construct classif...

Hyperledger Fabric is an open-source private permissioned blockchain that supports the use of smart contracts (chaincode). It is aimed mainly at private networks of companies. To serve the different needs of each company and to be flexible in customer requirements, it consists of various adaptive components. Although this structure efficiently addr...

Blockchain is a distributed, immutable ledger technology initially developed to secure cryptocurrency transactions. Following its revolutionary use in cryptocurrencies, blockchain solutions are now being proposed to address various problems in different domains, and it is currently one of the most “disruptive” technologies. This paper presents a sc...

The protection of personal data and privacy is a timeless challenge which has intensified in the modern era [...]

Blockchain is a distributed, immutable ledger technology initially developed to secure cryptocurrency transactions. Following its revolutionary use in cryptocurrencies, blockchain solutions are now being proposed to address various problems in different domains and is currently one of the most "disruptive" technologies. This paper presents a scopin...

The COVID-19 pandemic has deeply impacted all aspects of social, professional, and financial life, with concerns and responses being readily published in online social media worldwide. This study employs probabilistic text mining techniques for a large-scale, high-resolution, temporal, and geospatial content analysis of Twitter related discussions....

With the growing number of Location-Based Social Networks, privacy preserving location prediction has become a primary task for helping users discover new points-of-interest (POIs). Traditional systems consider a centralized approach that requires the transmission and collection of users' private data. In this work, we present FedPOIRec, a privacy...

e-Government services have evolved significantly over the last decade, from a paper-based bureaucratic procedure to digital services. Electronically processed transactions require limited physical interaction with the public administration, and provide reduced response times, increased transparency, confidentiality and integrity. Blockchain technol...

This paper describes the participation of the DUTH-ATHENA team of Democritus University of Thrace and Athena Research Center in the eRisk 2021 task, which focuses on measuring the level of depression based on Reddit users' posts. We address this task using both feature-based and fine-tuning strategies for applying BERT-based representations. In the...

Blockchain, a promising technology that has matured and nowadays is widely used in many fields, such as supply chain management, smart grids, agriculture and logistics, has also been proposed for the Internet of Vehicles (IoV) ecosystem to enhance the protection of the data that roadside units and vehicles exchange. Blockchain technology can inhere...

Background: The effectiveness of public health measures depends upon a community’s compliance as well as on its positive or negative emotions. Objective: The purpose of this study was to perform an analysis of the expressed emotions in English tweets by Greek Twitter users during the first phase of the COVID-19 pandemic in Greece. Methods: The...

Location based social networks, such as Foursquare and Yelp, have inspired the development of novel recommendation systems due to the massive volume and multiple types of data that their users generate on a daily basis. More recently, research studies have been focusing on utilizing structural data from these networks that relate the various entiti...

BACKGROUND The effectiveness of public health measures depends upon a community’s compliance as well as on its positive or negative emotions. OBJECTIVE The purpose of this study was to perform an analysis of the expressed emotions in English tweets by Greek Twitter users during the first phase of the COVID-19 pandemic in Greece. METHODS The perio...

Internet of Things (IoT) is a promising, relatively new technology that develops ``smart'' networks with a variety of uses and applications (e.g., smart cities, smart home and autonomous cars). The diversity of protocols, technologies and devices that IoT consists of, even though they add in value and utility, they create major privacy issues that...

News dissemination in the modern world deploys online social networks (OSNs) to instantly and freely convey facts and opinions to Internet users worldwide. Recent research studies the structure of the graph formed by the relationships between news readers and media outlets in OSNs to investigate the profile of the media and derive their political l...

Cancer immunotherapy is a rapidly growing field that is completely transforming oncology care. Mining this knowledge base for biomedically important information is becoming increasingly challenging, due to the expanding number of scientific publications, and the dynamic evolution of this subject with time. In this study, we have employed a literatu...

Topic modeling refers to a suite of probabilistic algorithms for extracting popular topics from a collection of documents. A common approach involves the use of the Latent Dirichlet Allocation (LDA) algorithm, and, although free implementations are available, their deployment in general requires a certain degree of programming expertise. This paper...

Industrial Internet of Things (IIoT) is a relatively new area of research that utilises multidisciplinary and holistic approaches to develop smart solutions for complex problems in industrial environments. Designing applications for the IIoT is a non trivial issue and requires to address, among many others, technology concerns, the protection of pe...

The evolution of the Internet of Things is significantly affected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR). The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed...

Online gambling, as opposed to land-based gambling and other mediums of problematic and addictive behaviours such as alcohol and tobacco, offers unprecedented opportunities for monitoring and understanding users' behaviour in real-time, along with the ability to adapt persuasive messages and interactions that would fit the gamblers usage and person...

In this work, we show that the structural features of the Twitter online social network can divulge valuable information about the political affinity of the participating nodes. More precisely, we show that Twitter followers can be used to predict the political affinity of prominent Nodes of Interest (NOIs) they opt to follow. We utilize a series o...

Android devices contain a vast amount of personal data of their owners. These data are stored on the device and are protected by the Android permission scheme. Android apps can obtain access to specific data items by requesting the appropriate permissions from the user. However, in Android, the access to certain assets is granted by default to the...

In the Internet of Things (IoT) ecosystem, the volume of data generated by devices in the user’s environment is continually increasing and becoming of particular value. In such an environment the average user is bound to face considerable difficulties in understanding the size and scope of his/her collected data. However, the provisions of the Euro...

Introduction: eHealth emerged as an interdisciplinary research area about 70 years ago. This study employs probabilistic techniques to semantically analyse scientific literature related to the field of eHealth in order to identify topics and trends and discuss their comparative evolution. Methods: Authors collected titles and abstracts of publis...

Blockchain is a distributed, immutable ledger technology introduced as the enabling mechanism to support cryptocurrencies. Blockchain solutions are currently being proposed to address diverse problems in different domains. This paper presents a scoping review of the scientific literature to map the current research area of blockchain applications i...

Online gambling, unlike other offline addiction forms, provides unprecedented opportunities for monitoring users’ behaviour in real-time, along with the ability to adapt persuasive interactions and messages that would match the gamblers usage and personal context. Online gambling industry usually offers Application Programming Interfaces (APIs) tha...

In this paper, we focus on privacy leakages about Twitter users and show that simply establishing follower and friend connections in the Twitter network might be enough to reveal sensitive information about the political beliefs of a user. More precisely, we create a Twitter dataset containing the twitter nodes of Greek news media and politicians,...

The value of personal data generated and managed by smart devices which comprise the Internet of Things (IoT) is unquestionable. The EU General Data Protection Regulation (GDPR) that has been recently put in force, sets the cornerstones regarding the collection and processing of personal data, for the benefit of Data Subjects and Controllers. Howev...

Biomedical research and clinical decision depend increasingly on scientific evidence realized by a number of authoritative databases, mostly public and continually enriched via peer scientific contributions. Given the dynamic nature of biomedical evidence data and their usage in the sensitive domain of biomedical science, it is important to ensure...

eHealth is an interdisciplinary research area that fosters application of informatics and communication technologies for the improvement of healthcare delivery. In this paper, we present an overall analysis of eHealth topics and trends in published literature indexed in PubMed (all records till 31 Dec 2016, search on 25 Jan 2017), based on unsuperv...

Topic modeling refers to a suite of probabilistic algorithms for extracting word patterns from a collection of documents aiming for data clustering and detection of research trends. We developed an online service that implements different variations of Latent Dirichlet Allocation (LDA) algorithm. Scientific literature origin from targeted search qu...

Biomedical research and clinical decision depend increasingly on a number of authoritative databases, mostly public and continually enriched via peer scientific contributions. Given the dynamic nature of data and their usage in the sensitive domain of biomedical science, it is important to ensure retrieved data integrity and non-repudiation, that i...

Biosignals recorded using personal health devices and stored in General Data Format (GDF) are vulnerable when the data is transferred, processed and stored to the external servers. The aforementioned vulnerabilities influence data security and user's privacy. In this paper, we propose modifications of GDF format that enables the encryption both-per...

Internet-enabled television systems (SmartTVs) are a development that introduces these devices into the interconnected environment of the Internet of Things. We propose a privacy-preserving application for computing Television Audience Measurement (TAM) ratings. SmartTVs communicate over the Internet to calculate aggregate measurements. Contemporar...

Patient empowerment delivers health and social care services that enable people to gain more control of their healthcare needs. With the advancement of sensor technologies, it is increasingly possible to monitor people’s health with dedicated wearable sensors. The consistent measurements from a variety of wearable sensors imply that a huge amount o...

The assessment of risk in medicine is a crucial task, and depends on scientific knowledge derived by systematic clinical studies on factors affecting health, as well as on particular knowledge about the current status of a particular patient. Existing non-semantic risk prediction tools are typically based on hardcoded scientific knowledge, and only...

We focus on personal data generated by the sensors and through the everyday usage of smart devices and take advantage of these data to build a non-invasive contextual suggestion system for tourism. The system, which we call Pythia, exploits the computational capabilities of modern smart devices to offer high quality personalized POI (point of inter...

Contemporary healthcare delivery is based on state-of-the-art scientific best practices captured in systematically developed formal care plans which include guidelines, clinical protocols, integrated care pathways, etc. Research so far has addressed the computerized execution of formal care plans by developing a number of related representation lan...

Healthcare delivery is largely based on medical best practices as in clinical protocols. Research so far has addressed the computerized execution of clinical protocols by developing a number of related representation languages, execution engines and integrated platforms to support real time execution. However, much less effort has been put into org...

In this report we give an overview of our participation in the TREC 2015 Clinical Decision Support Track. We present two approaches for pre-processing and indexing of the open-access PubMed articles, and four methods for query construction which are applied to the previous two approaches. Regarding pre-processing, our main assumption is that only p...

We consider the problem of privacy leaks suffered by Internet users when they perform web searches, and propose a framework to mitigate them. In brief, given a ‘sensitive’ search query, the objective of our work is to retrieve the target documents from a search engine without disclosing the actual query. Our approach, which builds upon and improves...

Personalizing healthcare applications requires capturing patient specific information, including medical history, health status, and mental aspects such as behaviors, intentions, and attitudes. This paper presents a privacy-friendly system to deduce patient intentions that can be used to personalized eHealth applications. In the proposed approach p...

This paper presents a privacy-preserving system for participatory sensing, which relies on cryptographic techniques and distributed computations in the cloud. Each individual user is represented by a personal software agent, deployed in the cloud, where it collaborates on distributed computations without loss of privacy, including with respect to t...

In this paper, we propose a user-centric software architecture for managing Ubiquitous Health Monitoring Data (UHMD) generated from wearable sensors in a Ubiquitous Health Monitoring System (MINIS), and examine how these data can be used within privacy-preserving distributed statistical analysis. Two are the main goals of our approach. First, to en...

In this work, we define the Nearest Doctor Problem for finding the nearest doctor in case of an emergency and present a privacy-preserving protocol for solving it. The solution is based on cryptographic primitives and makes use of the current location of each participating doctor. The protocol is efficient and protects the privacy of the doctors’ l...

We propose a method for search privacy on the Internet, focusing on enhancing plausible deniability against search engine query-logs. The method approximates the target search results, without submitting the intended query and avoiding other exposing queries, by employing sets of queries representing more general concepts. We model the problem theo...

In this report we give an overview of our participation in the TREC 2013 Contextual Suggestion Track. We present an approach for context processing that comprises a newly designed and fine-tuned POI (Point Of Interest) data collection technique, a crowdsourcing approach to speed up data collection and two radically different approaches for suggesti...

We consider the problem of privacy leaks suffered by Internet users when they perform web searches, and propose a framework to mitigate them. Our approach, which builds upon and improves recent work on search privacy, approximates the target search results by replacing the private user query with a set of blurred or scrambled queries. The results o...

Participatory sensing is a crowd-sourcing technique which relies both on active contribution of citizens and on their location and mobility patterns. As such, it is particularly vulnerable to privacy concerns, which may seriously hamper the large-scale adoption of participatory sensing applications. In this paper, we present a privacy-preserving sy...

Internet-enabled television systems, often referred to as Smart TVs, are a new development in television and home entertain-ment technologies. In this work, we propose a new, privacy-preserving, approach for Television Audience Measurement (TAM), utilizing the ca-pabilities of the Smart TV technologies. We propose a novel application to calculate a...

In this work, we consider ubiquitous health data generated from wearable sensors in a Ubiquitous Health Monitoring System (UHMS) and examine how these data can be used within privacy- preserving distributed statistical analysis. To this end, we propose a secure multi-party computation based on a privacy-preserving cryptographic protocol that accept...

In this paper, we propose a new architecture for managing data in a Ubiquitous Health Monitoring System (UHMS). The purpose of this architecture is to enhance the privacy of patients and furthermore to decongest the Health Monitoring Center (HMC) from the enormous amount of biomedical data generated by the users' wearable sensors. This is achieved...

We propose a method for search privacy on the Internet, focusing on enhancing plausible deniability against search engine query-logs. The method approximates the target search results, without submitting the intended query and avoiding other exposing queries, by employing sets of queries representing more general concepts. We model the problem theo...

In this work, we define the Nearest Doctor Problem (NDP) for finding the closest doctor in case of an emergency and present a secure multi-party computation for solving it. The solution is based on a privacy-preserving cryptographic protocol and makes use of the current location of each participating doctor. The protocol is efficient and protects t...

Purpose In order to enhance privacy protection during electronic transactions, the purpose of this paper is to propose, develop, and evaluate a personal data management framework called Polis that abides by the following principle: every individual has absolute control over his/her personal data that reside only at his/her own side. Design/methodo...

We present a personal data management framework called Polis, which abides by the following principle: Every individual has absolute control over her personal data, which reside only at her own side. Preliminary results indicate that beyond the apparent advantages of such an environment for users’ privacy, everyday transactions remain both feasible...

In this work, we present a case study of a secure mobile database application. In particular, we design, implement and evaluate a mobile database application for an electronic announcement board. We identify a set of security issues and apply appropriate techniques to sat-isfy the corresponding security requirements.