Dionysios Kehagias

• PhD, Electrical and Computer Engineer
• Principal Researcher at Centre for Research and Technology Hellas

Compliance with international security standards is essential for ensuring the security of information systems, and thereby their dependability and trustworthiness. Compliance evaluation is performed by experts who check whether critical security requirements (i.e., criteria), which have been extracted from standard documents, are met by the system...

The rise of Large Language Models (LLMs) has provided new directions not just for natural language understanding and text generation but also for addressing downstream tasks, such as text classification. A downstream text classification task is vulnerability prediction, where segments of the source code are classified as vulnerable or not. Several...

Vulnerability prediction is an important mechanism for secure software development, as it enables the early identification and mitigation of software vulnerabilities. Vulnerability prediction models (VPMs) are machine learning (ML) models able to detect potentially vulnerable software components based on information retrieved from their source code...

The advent of Industry 5.0 as a defining concept for the future, which advocates a human-centric coalescence of humans and technology or software, renders the skilled workforce the most important asset in any organization or business. The society is 'forced' to adapt itself to technological change and progress for setting the necessary skillsets fo...

In recent years, we have witnessed an important increase in research focusing on how machine learning (ML) techniques can be used for software quality assessment and improvement. However, the derived methodologies and tools lack transparency, due to the black-box nature of the employed machine learning models, leading to decreased trust in their re...

Automated classification of software requirements is valuable for software engineering. Recently, Natural Language Processing (NLP) and Machine Learning (ML) techniques have been utilized as an alternative to manual classification of requirements. In this study, we conduct a thorough empirical evaluation of several NLP methods utilized for efficien...

Developing embedded software applications is a challenging task, chiefly due to the limitations that are imposed by the hardware devices or platforms on which they operate, as well as due to the heterogeneous non-functional requirements that they need to exhibit. Modern embedded systems need to be energy efficient and dependable, whereas their main...

Effective assignment of delivery task to multiple drivers is crucial for enabling smooth operation and maximizing end-user satisfaction. This paper focuses on batch assignment, i.e., the allocation of tasks among multiple drivers, starting from the same depot, while taking into account a variety of factors like load balancing delivery time, distanc...

Virtual reality (VR) became, in the last few years, an important pillar for promoting cultural heritage (CH) through serious games or virtual guided tours. A lot of museums, institutes, and galleries tend to integrate new technologies like VR for promotion purposes. The major objective of this research is to analyze the Activator project through th...

Today, we are, more than ever, in a necessity for fast and accurate transfer of goods fulfilling every person's needs. In order to achieve fast and accurate last-mile delivery of goods, along with cost reduction, accurate real-time traffic prediction mechanisms play a significant role, as they can feed vehicle route optimization algorithms, which l...

Monitoring Technical Debt (TD) is considered highly important for software companies , as it provides valuable information on the effort required to repay TD and in turn maintain the system. When it comes to TD repayment however, developers are often overwhelmed with a large volume of TD liabilities that they need to fix, rendering the procedure ef...

In recent years, a lot of progress has been reported in the field of energy disaggregation, also referred to as Non-Intrusive Load Monitoring (NILM). Despite the fact that there are many studies focusing on the residential sector, there is considerably less research interest for the industrial sector. In this paper, we present a deep neural network...

A Systematic Mapping Study for Software Vulnerability Prediction. Vulnerability prediction-related research focus mainly on predicting vulnerable software components and also on discovering the number of vulnerabilities in time. A systematic mapping study is conducted to provide a comprehensive description of the software vulnerability prediction...

The devastating consequences of successful security breaches that have been observed recently have forced more and more software development enterprises to shift their focus towards building software products that are highly secure (i.e., vulnerability-free) from the ground up. In order to produce secure software applications, appropriate mechanism...

Nowadays, the increasing flourishing of the language models provides a new direction not only for the task of text generation, which is their actual goal, but also for dealing with downstream tasks, such as text classification. Vulnerability prediction is a task that has been heavily connected with text mining techniques, since many studies in the...

Delivery-service enterprises need to achieve high quality of service and at the same time keep their operational costs affordable. The fulfillment of the customer demands depends on various aspects, e.g., timely pickup and delivery of goods, delivery fees, customer support, etc. As a result, the idea of a unified platform for both the deliverers an...

The cultural heritage sector increasingly integrates augmented and virtual reality (VR) solutions to meet dissemination and interpretation needs for its collections. As research in the field grows, the required entertainment and learning impacts of such applications are rising. This study presents a VR museum that aims to facilitate an understandin...

Given the concentration of the majority of population in urban areas and the lack of available public space, car parking has evolved as a major problem for big cities in recent years. To address the issue, several approaches have been proposed including incentivization mechanisms for increasing the use of public transport, carpooling for reducing t...

Given the concentration of the majority of population in urban areas and the lack of available public space, car parking has evolved as a major problem for big cities in recent years. To address the issue, several approaches have been proposed including incentivisation mechanisms for increasing the use of public transport, carpooling for reducing t...

Technical Debt (TD) is a successful metaphor in conveying the consequences of software inefficiencies and their elimination to both technical and non-technical stakeholders, primarily due to its monetary nature. The identification and quantification of TD rely heavily on the use of a small handful of sophisticated tools that check for violations of...

In recent years, the exhibition of digitized Cultural Heritage in Virtual Museums has increased, while Cultural Heritage institutions are trying to align with current trends regarding their communication with the audience. In VMs created with 360° panoramas; web 3D VMs and 3D virtual exhibitions created with authoring tools, the visitor-exhibit int...

Tourism demand forecasting comprises an important task within the overall tourism demand management process since it enables informed decision making that may increase revenue for hotels. In recent years, the extensive availability of big data in tourism allowed for the development of novel approaches based on the use of deep learning techniques. H...

Software security is a critical aspect of modern software products. The vulnerabilities that reside in their source code could become a major weakness for enterprises that build or utilize these products, as their exploitation could lead to devastating financial consequences. Therefore, the development of mechanisms capable of identifying and disco...

Technical debt (TD) is a successful and widely used metaphor that expresses the quality compromises that can yield short-term benefits but may negatively affect the overall quality of a software product in the long run. There is a vast variety of techniques and methodologies that have been proposed over the past years to enable the identification a...

Within the scope of the project ActiVatoR, which reconstructed some major events in Ancient Greek history, the collaboration of CERTH\ITI and Noesis Museum of Ancient technology reconstructed the settlement of Akrotiri in Thira. The final product is a Virtual Reality serious game, which depicts the Akrotiri settlement during the bronze age of Greec...

Software security is a very important aspect for software development organizations who wish to provide high-quality and dependable software to their consumers. A crucial part of software security is the early detection of software vulnerabilities. Vulnerability prediction is a mechanism that facilitates the identification (and, in turn, the mitiga...

A hybrid algorithm is proposed, comprising Simulated Annealing, an NLP algorithm (IPOPT) and a continuation method (PITCON) for simultaneous process design and controllability assessment. The algorithm integrates the approximate computing techniques of memoization, task dropping and loop perforation. SA and process model calculations are paralleliz...

Software security is a critical consideration for software development companies that want to provide their customers with high-quality and dependable software. The automated detection of software vulnerabilities is a critical aspect in software security. Vulnerability prediction is a mechanism that enables the detection and mitigation of software...

Context The definition and assessment of software quality have not converged to a single specification. Each team may formulate its own notion of quality and tools and methodologies for measuring it. Software quality can be improved via code changes, most often as part of a software maintenance loop. Objective This manuscript contributes towards p...

To date, the identification and quantification of Technical Debt (TD) rely heavily on a few sophisticated tools that check for violations of certain predefined rules, usually through static analysis. Different tools result in divergent TD estimates calling into question the reliability of findings derived by a single tool. To alleviate this issue,...

Critical everyday activities handled by modern IoT Systems imply that security is of major concern both for the end-users and the industry. Securing the IoT System Architecture is commonly used to strengthen its resilience to malicious attacks. However, the security of software running on the IoT must be considered as well, since the exploitation o...

Developing modern secure and low-energy applications in a short time imposes new challenges and creates the need of designing new software tools to assist developers in all phases of application development. The design of such tools cannot be considered a trivial task, as they should be able to provide optimization of multiple quality requirements....

In recent years, the exhibition of digitized Cultural Heritage in Virtual Museums has increased, while Cultural Heritage institutions are trying to align with current trends regarding their communication with the audience. In VMs created with 360 o panoramas; web 3D VMs and 3D virtual exhibitions created with authoring tools, the visitor-exhibit in...

Software security is a critical consideration for software development companies that want to provide their customers with high-quality and dependable software. The automated detection of software vulnerabilities is a critical aspect in software security. Vulnerability prediction is a mechanism that enables the detection and mitigation of software...

Technical debt (TD) is a metaphor commonly used to reflect the consequences of quality compromises that can derive short-term benefits but may result in quality decay of software products in the long run. While a broad variety of methods and tools have been proposed over the years for the identification and quantification of TD during the software...

Despite the acknowledged ability of automated static analysis to detect software vulnerabilities, its adoption in practice is limited, mainly due to the large number of false alerts (i.e., false positives) that it generates. Although several machine learning-based techniques for assessing the actionability of the produced alerts and for filtering o...

Programming upcoming exascale computing systems is expected to be a major challenge. New programming models are required to improve programmability, by hiding the complexity of these systems from application developers. The EXA2PRO programming framework aims at improving developers productivity for applications that target heterogeneous computing s...

Residential load forecasting is one of the most important tasks of the overall supply management process in electrical grids, since it enables smart grid services such as demand response (DR). Hence, several approaches for accurate residential load forecasting have been proposed in the relevant literature. However, most of the existing methods focu...

Residential load forecasting is one of the most important tasks of the overall supply management process in electrical grids, since it enables smart grid services such as demand response (DR). Hence, several approaches for accurate residential load forecasting have been proposed in the relevant literature. However, most of the existing methods focu...

Despite the acknowledged importance of quantitative security assessment in secure software development, current literature still lacks an efficient model for measuring internal software security risk. To this end, in this paper, we introduce a hierarchical security assessment model (SAM), able to assess the internal security level of software produ...

Technical debt (TD) describes quality compromises that can yield short-term benefits but may negatively affect the quality of software products in the long run. A wide range of tools and techniques have been introduced over the years in order for the developers to be able to determine and manage TD. However, being able to also predict its future ev...

The Conference on Energy Consumption, Quality of Service, Reliability, Security, and Maintainability of Computer Systems and Networks (EQSEM) was held as a virtual conference on October 20–21, 2020. This paper summarises the objectives and proceedings of this conference. It then briefly presents the keynotes and other papers which were presented. T...

Indoor navigation is a very interesting scientific domain due to its potential use compared with the GPS signals, which are restricted to outdoor environments. This paper describes commonly used methods of Indoor navigation, positioning, and mapping systems using Augmented Reality (AR) techniques. An Indoor navigation system, which is based on an A...

Accurately forecasting power generation in photovoltaic (PV) installations is a challenging task, due to the volatile and highly intermittent nature of solar-based renewable energy sources. In recent years, several PV power generation forecasting models have been proposed in the relevant literature. However, there is no consensus regarding which mo...

Vulnerability prediction constitutes a mechanism that enables the identification and mitigation of software vulnerabilities early enough in the development cycle, improving the security of software products, which is an important quality attribute according to ISO/IEC 25010. Although existing vulnerability prediction models have demonstrated suffic...

Vulnerability prediction facilitates the development of secure software , as it enables the identification and mitigation of security risks early enough in the software development lifecycle. Although several factors have been studied for their ability to indicate software security risk, very limited attention has been given to technical debt (TD),...

Technical debt (TD) describes quality compromises that can yield short-term benefits but may negatively affect the quality of software products in the long run. A wide range of tools and techniques have been introduced over the years in order for the developers to be able to determine and manage TD. However, being able to also predict its future ev...

Maintaining high level of quality with respect to important quality attributes is critical for the success of modern software applications. Hence, appropriate tooling is required to help developers and project managers monitor and optimize software quality throughout the overall Software Development Lifecycle (SDLC). Moreover, embedded software eng...

Technical debt (TD) is commonly used to indicate additional costs caused by quality compromises that can yield short-term benefits in the software development process, but may negatively affect the long-term quality of software products. Predicting the future value of TD could facilitate decision-making tasks regarding software maintenance and assi...

Technical debt (TD) is commonly used to indicate additional costs caused by quality compromises that can yield short-term benefits in the software development process, but may negatively affect the long-term quality of software products. Predicting the future value of TD could facilitate decision-making tasks regarding software maintenance and assi...

Vulnerability prediction constitutes a mechanism that enables the identification and mitigation of software vulnerabilities early enough in the development cycle, improving the security of software products, which is an important quality attribute according to ISO/IEC 25010. Although existing vulnerability prediction models have demonstrated suffic...

The provision of efficient, sustainable, and personalized mobility services that combine a broad range of transport modes (e.g., public transportation, electric vehicles (EVs), vehicle sharing) constitutes a fundamental challenge in urban environments. This chapter reports on the key results and contributions of the EU-funded research project MOVES...

With the rapid growth of the global population and its concentration in large urban centres, the need for smart and sustainable mobility solutions has become more imperative than ever. Among the mobility paradigms advocating the shift from vehicle ownership to vehicle usership, the Mobility as a Service (MaaS) paradigm, namely the mobility system t...

While necessary for the successful embedded software development and maintenance, software quality optimization is a complex activity with immense issues. Various design and run-time qualities should be continuously monitored and optimized during the whole Software Development Life Cycle (SDLC). Moreover, embedded software engineers and developers...

Over the recent years, the vast variety of widely accessible cloud computing services along with the need to combine transportation services either from public or private providers, have led to the rise of the Mobility as a Service (MaaS) concept. The main feature of MaaS is that it gives users access to a set of heterogeneous transportation servic...

Mitigating software vulnerabilities typically requires source code refactorings for implementing necessary security mechanisms. These mechanisms, although they enhance software security, they usually execute a large number of instructions, adding a performance/energy penalty to the overall application. Conversely, source code transformations are ex...

Technical debt (TD) is commonly used to indicate additional costs caused by quality compromises that can yield short-term benefits in the software development process, but may negatively affect the long-term quality of software products. Predicting the future value of TD could facilitate decision-making tasks regarding software maintenance and assi...

Refactoring is a prevalent technique that can be applied for improving software structural quality. Refactorings can be applied at different levels of granularity to resolve ‘bad smells’ that can be identified in various artifacts (e.g., methods, classes, packages). A fundamental software engineering principle that can be applied at various levels...

Technical Debt (TD) is commonly used in practice as a measure of software quality. Due to the potential overlap between software quality and software security, an interesting topic is to investigate whether TD can be used as a software security indicator as well. However, although some software-related factors (e.g. software metrics) have been stud...

Several studies have highlighted the ability of software metrics to predict vulnerabilities. However, limited attention has been given on the capacity of software metrics to discriminate between different types of vulnerabilities, while the existence of potential interdependencies among different vulnerability types has not been studied yet. For th...

One way to ensure sustainable and environmental friendly mobility is the use of less vehicles for carrying more passengers, and carpooling is a means to achieve this goal. One major concern in carpooling services is related to trust, as carpooling users need to either share their vehicles, if they act as drivers, or travel with strangers if they ac...

Technical debt (TD), a metaphor inspired by the financial debt of economic theory, indicates quality compromises that can yield short-term benefits in the software development process, but may negatively affect the long-term quality of software products. Numerous techniques, methods, and tools have been proposed over the years for estimating and ma...

The EXA2PRO programming environment will integrate a set of tools and methodologies that will allow to systematically address many exascale computing challenges, including performance, performance portability, programmability, abstraction and reusability, fault tolerance and technical debt. The EXA2PRO tool-chain will enable the efficient deploymen...

Software security is a matter of major concern for software development enterprises that wish to deliver highly secure software products to their customers. Static analysis is considered one of the most effective mechanisms for adding security to software products. The multitude of static analysis tools that are available provide a large number of...

Road traffic prediction for the efficient traffic control has lately been in the focus of the research community, as it can solve significant urban issues, such as city evacuation plans, increased concentration of CO2 emissions and delays caused by extended traffic jams. The current paper proposes a novel approach for multi-variate data mining from...

Purpose Semantic categorization of Web services comprises a fundamental requirement for enabling more efficient and accurate search and discovery of services in the semantic Web era. However, to efficiently deal with the growing presence of Web services, more automated mechanisms are required. This paper aims to introduce an automatic Web service c...

Software security is a matter of major concern for software development enterprises that wish to deliver highly secure software prod- ucts to their customers. Static analysis is considered one of the most effective mechanisms for adding security to software products. The mul- titude of static analysis tools that are available provide a large number...

In this paper we propose a model for accurate traffic prediction under both normal and abnormal conditions. The model is based on the identification of the traffic patterns shown under both normal and abnormal conditions using the density-based clustering algorithm DBSCAN, and the use of different prediction models for each separate cluster that re...

Several studies have highlighted the ability of software metrics to predict vulnerabilities. However, limited attention has been given on the capacity of software metrics to discriminate between different types of vulnerabilities, while the existence of potential interdependencies among different vulnerability types has not been studied yet. For th...

Accurate power output forecasting is a critical credibility factor for both conventional and renewable modern power systems. Renewable power systems, like photovoltaic (PV) systems, could be severely affected by alternating weather conditions, and this is an important issue relative to accurate fore-casts. In this paper a comparative analysis betwe...

The reduction of road congestion requires intuitive urban congestion-control platforms that can facilitate transport stakeholders in decision making. Interactive ITS visual analytics tools can be of significant assistance, through their real-time interactive visualizations, supported by advanced data analysis algorithms. In this paper, an interacti...

One of the most challenging goals of the modern Intelligent Transportation Systems comprises the accurate and real-time short-term traffic prediction. The achievement of this goal becomes even more critical when the presence of atypical traffic conditions is concerned. In this paper, we propose a novel hybrid technique for short-term traffic predic...

Incidents produce heavy congestion in large urban traffic networks and therefore real time information about them (e.g. location, timestamp, type) can be very useful for the drivers. An efficient way of gathering this type of information is through a crowd sourcing reporting system that multimodal travellers may utilise for providing information ab...

Short-term traffic prediction is a crucial task for every modern Intelligent Transportation System (ITS), especially under the presence of atypical traffic conditions. We present a novel regime-switching model for short-term traffic prediction under both typical and atypical traffic conditions. Preliminary results indicate the superiority of the pr...

In this paper we propose a model for accurate traffic prediction under both normal and abnormal conditions. The model is based on the identification of the traffic patterns shown under both normal and abnormal conditions using the density-based clustering algorithm DBSCAN, and the use of different prediction models for each separate cluster that re...

Incidents produce heavy congestion in large urban traffic networks and therefore real time information about them (e.g. location, timestamp, type) can be very useful for the drivers. An efficient way of gathering this type of information is through a crowd sourcing reporting system that multimodal travellers may utilise for providing information ab...

The exploration of the potential correlations of traffic conditions between roads in large urban networks, which is of profound importance for achieving accurate traffic prediction, often implies high computational complexity due to the implicated network topology. Hence, focal methods are required for dealing with the urban network complexity, red...

This study introduces a new short-term traffic forecasting technique, based on the dynamic features of traffic data derived from vehicles moving in urban networks. The authors goal is to forecast the values of appropriate traffic status indicators such as average travel time or speed, for one or more time steps in the future until the next half hou...

Tackling urban road congestion by means of ITS technologies, involves a number of key challenges. One such challenge is related to the accurate detection of traffic incidents in urban networks for more efficient traffic management. This paper introduces a classification approach that achieves accurate detection of road traffic incidents, based on d...