Posted on

UBITECH kicks off the CyberSANE Innovation Action on cybersecurity incident handling, warning and response

UBITECH is participating at the kick-off meeting, in Heraklion, Greece (September 10-11, 2019), of the CyberSANE Innovation Action, officially started on September 1st, 2019. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 833683) and spans on the period September 2019 – August 2022. The CyberSANE project intends to improve the detection and analysis of cyber-attacks and threats on Critical Information Infrastructures (CIIs), increases the knowledge on the current cyber threat landscape and supports human operators (such as Incident Response professionals) to dynamically increase preparedness, improve cooperation amongst CIIs operators, and adopt appropriate steps to manage security risks, report and handle security incidents. Moreover, CyberSANE is fully in-line with relevant regulations (such as the GDPR and NIS directive), which requires organizations to increase their preparedness, improve their cooperation with each other, and adopt appropriate steps to manage security risks, report and handle security incidents.

In particular, CyberSANE will develop a system that addresses both technical and congitive challenges related to identification, prevention and protection against attacks. At technical level, the CyberSANE system will collect, compile, process and fuse attack related data from multiple perspective, through its main four components: The Live Security Monitoring and Analysis (LiveNet) component, the Deep and Dark Web mining and Intelligence (DarkNet) component, the Data Fusion, Risk Evaluation and Event Management (HybridNet) component and the Intelligent and Information Sharing and Dissemination (ShareNet) component. From a cognitive perspective, the system will enable decision makers (e.g. incident response professionals) to better understand understand the technical aspects of an attack and draw conclusions on how to respond.

Continue reading UBITECH kicks off the CyberSANE Innovation Action on cybersecurity incident handling, warning and response

Posted on

A successful final review for the BigDataOcean H2020 project in Luxembourg

The second and final contractual review meeting for the BigDataOcean H2020 co-funded research project (http://www.bigdataocean.eu/site/) took place in Luxembourg on July 23, 2019. The BigDataOcean consortium successfully presented the results of the work of the project during the last 15 months of project (from M16 up until M30). UBITECH, as the leader of WP5 entitled BigDataOcean Web Platform Implementation, presented the updates in the technical architecture and the technical highlights of the BigDataOcean platform. UBITECH also supported ANEK and FOINIKAS in the presentation of the dedicated technical solutions that UBITECH implemented for them in the context of the project, namely the Fuel Consumption Reduction Investigation Application and the Fault Detection and Predictive Maintenance Application for ANEK and FOINIKAS respectively.

Posted on

UBITECH undertakes the technical management of the SPIDER Innovation Action on 5G cyber range

UBITECH is participating at the kick-off meeting, in Genova, Italy (July 23-24, 2019), of the SPIDER Innovation Action, officially started on July 1st, 2019. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 833685) and spans on the period July 2019 – June 2022. The SPIDER project intends to deliver an innovative Cyber Range as a Service (CRaaS) platform that extends and combines the capabilities of existing telecommunication testbeds and cyber ranges with the most recent advances in telecommunications management and emulation, gamification and serious games training as well as economics of cybersecurity, and uniquely virtualises them to become available as a single and easily accessible solution. The proposed SPIDER cyber range platform rests on three major pillars: (1) cybersecurity testing and assessment, with emphasis on new security technologies; (2) cybersecurity training in defending against advanced cyber-attacks; and (3) cybersecurity investment decision support.

In particular, the vision of SPIDER is to deliver a next-generation, extensive, and replicable cyber range platform for the telecommunications domain and its fifth generation (5G), offering cybersecurity emulation, training and investment decision support. Towards this vision, it features integrated tools for cyber testing including advanced emulation tools, novel training methods based on active learning as well as econometric models based on real-time emulation of modern cyber-attacks. SPIDER supports both self-paced and team-based exercising and acts as a serious gaming repository for multiple stakeholders to share training material and maximise efficiency in delivering complex cyber exercises.

Continue reading UBITECH undertakes the technical management of the SPIDER Innovation Action on 5G cyber range

Posted on

A successful final review for the AEGIS H2020 project in Luxembourg

The second and final contractual review meeting for the AEGIS H2020 co-funded research project (https://www.aegis-bigdata.eu/) took place in Luxembourg on July 18, 2019. The AEGIS consortium successfully presented the results of the work of the project during the last 12 months of project (from M19 up until M30). UBITECH, as the leader of WP3 entitled System Requirements, User stories, Architecture and Micro-Services, presented the updates in the technical architecture and the final technical highlights of the AEGIS platform, as well as the enhanced functionalities of the Smart Home and Assisted Living demonstrator which was co-designed and developed with Suite5 and KONKAT.

Posted on

A successful review for the BigDataStack H2020 project in Luxembourg with UBITECH’s live demonstration of the integrated PaaS platform

The first contractual review meeting for the BigDataStack H2020 funded research project, under Grant Agreement No 779747, took place in Luxembourg on July 16, 2019. The BigDataStack project delivers an infrastructure management system for the holistic management of computing, storage and networking resources, encompassing techniques for runtime adaptations of all BigDataStack operations and realizing Data as a Service through seamless data functions across the complete data path and lifecycle. BigDataStack incorporates approaches that range from data-focused application analysis and dimensioning, process modelling, cluster resources / nodes characterization, management and runtime optimization, to information-driven networking.

The BigDataStack consortium successfully presented the results of the technical, coordination, dissemination and communication work performed during the first 18 months of the project. UBITECH, as the infrastructure provider, presented a live end-to-end demonstration of the integrated BigDataStack platform by coupling the infrastructure, the data services and the applications in a adaptable and seamless manner.

Continue reading A successful review for the BigDataStack H2020 project in Luxembourg with UBITECH’s live demonstration of the integrated PaaS platform

Posted on

New manuscript on data sources reliability and quality has been accepted for publication at the Computer Methods and Programs in Biomedicine Journal

Following a peer-review process, Computer Methods and Programs in Biomedicine Journal published by Elsevier has accepted to publish a scientific manuscript entitled “Analyzing data and data sources towards a unified approach for ensuring end-to-end data and data sources quality in healthcare 4.0”, co-authored by UBITECH and UPRC. In this paper, Konstantinos Perakis, Dimitris Miltiadou, Stamatis Pitsios and their co-authors demonstrate an innovative mechanism for assessing the quality of various datasets in correlation with the quality of the corresponding data sources. For that purpose, the mechanism follows a 5-stepped approach through which the available data sources are detected, identified and connected to health platforms, where finally their data is gathered. Once the data is obtained, the mechanism cleans it and correlates it with the quality measurements that are captured from each different data source, in order to finally decide whether these data sources are being characterized as qualitative or not, and thus their data is kept for further analysis. https://doi.org/10.1016/j.cmpb.2019.06.026

Posted on

UBITECH presents a scientific paper on secure edge computing at SecSoft Workshop, co-hosted at IEEE NetSoft 2019, in Paris, France

A scientific paper entitled “Secure Edge Computing with Lightweight Control-Flow Property-based Attestation” has been co-authored by UBITECH and is presented at the 1st International Workshop on Cyber-Security Threats, Trust and Privacy Management in Software-defined and Virtualized Infrastructures (SecSoft), co-hosted at 5th IEEE International Conference on Network Softwarization (NetSoft 2019), between June 24-28, 2019 in Paris, France. In this paper, Sofianna Menesidou, Panagiotis Gouvas, and their co-authors propose a lightweight dynamic control-flow property-based attestation architecture (CFPA) that can be applied on both resource-constrained edge and cloud devices and services.

Continue reading UBITECH presents a scientific paper on secure edge computing at SecSoft Workshop, co-hosted at IEEE NetSoft 2019, in Paris, France

Posted on

UBITECH kicks off the SDN-microSENSE Innovation Action on Electrical Energy Systems cybersecurity management and resilience

UBITECH is participating at the kick-off meeting, in Seville, Spain (June 4-5, 2019), of the SDN-microSENSE Innovation Action, officially started on May 1st, 2019. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 833955) and spans on the period May 2019 – April 2022. The SDN-microSENSE project intends to provide a set of secure, privacy-enabled and resilient to cyberattacks tools, thus ensuring the normal operation of Electrical Power and Energy Systems (EPES) as well as the integrity and the confidentiality of communications.

In particular, adopting an SDN-based technology, SDN-microSENSE will develop a three-layer security architecture, by deploying and implementing risk assessment processes, self-healing capabilities, large-scale distributed detection and prevention mechanisms, as well as an overlay privacy protection framework. Firstly, the risk assessment framework will identify the risk level of each component of EPES, identifying the possible threats and vulnerabilities. Accordingly, in the context of self-healing, islanding schemes and energy management processes will be deployed, isolating the critical parts of the network in the case of emergency. Furthermore, collaborative intrusion detection tools will be capable of detecting and preventing possible threats and anomalies timely. Finally, the overlay privacy protection framework will focus on the privacy issues, including homomorphic encryption and anonymity processes.

Continue reading UBITECH kicks off the SDN-microSENSE Innovation Action on Electrical Energy Systems cybersecurity management and resilience

Posted on

UBITECH presents a scientific paper on predictive maintenance for digital factories at IoTI4 2019 in Santorini, Greece

A scientific paper entitled “Unveiling Trends and Predictions in Digital Factories” has been authored by UBITECH and is presented at the International Workshop on IoT Applications and Industry 4.0 (IoTI4 2019) that is part of the annual International Conference on Distributed Computing in Sensor Systems (DCOSS 2019), hosted between May 29-31, 2019 in Santorini, Greece. In this paper, Karagiorgou Sophia, Vafeiadis Georgios, Ntalaperas Dimitrios, Lykousas Nikolaos, Vergeti Danae and Alexandrou Dimitrios propose a failure prediction system for complex IT systems in the steel industry. The novelty of their work lies in the exploitation of Deep Learning techniques from streaming operational sensor data, enabling earlier failure predictions through a Neural Networks approach [in particular, through Long Short-Term Memory Networks (LSTM) that is a Recurrent Neural Network (RNN) architecture]. This predictive maintenance framework consists of three components: the Sense Module, the Detect Module and the Predict Module. To evaluate the proposed framework, real-life data are collected and analyzed based on daily operational and maintenance activities within the production line. They further demonstrate the framework’s potential by presenting some early results in modeling and predicting the complex and dynamic behavior in the manufacturing settings.

Continue reading UBITECH presents a scientific paper on predictive maintenance for digital factories at IoTI4 2019 in Santorini, Greece

Posted on

UBITECH presents a scientific paper on personalised monitoring and recommendation services for at risk individuals at IEEE EMB BHI 2019 in Chicago, IL, USA

A scientific paper entitled “Personalised Monitoring and Recommendation Services for At-Risk Individuals Employing Machine-Learning and Decision Support” has been co-authored by UBITECH and is presented at the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), the flagship conference of IEEE Engineering in Medicine and Biology Society (IEEE-EMBS) on the topics of informatics and computing in healthcare and life sciences, hosted between May 19-22, 2019 in Chicago, IL, USA. In this paper, Perakis Konstantinos, Pitsios Stamatis, Miltiadou Dimitrios, and their co-authors propose a technological solution, facilitating the provision of personalised health related services exploiting Big Data analytics, aiming to improve the everyday living and enhance the wellbeing of vulnerable individuals such as chronic disease patients, focusing mainly on patients suffering from COPD and/or CVD.

Continue reading UBITECH presents a scientific paper on personalised monitoring and recommendation services for at risk individuals at IEEE EMB BHI 2019 in Chicago, IL, USA