ez itt az index

Business Informatics

Activity of the research group:

Research of Standard integrated enterprise management systems – systems architecture (SOA architecture, microservices, cloud-based enterprise management systems), planning algorithms (production planning and scheduling, demand forecasting, supply), business entity databases (schema matching, semantic data warehouses), operational processes (enterprise and manufacturing process modeling, simulation and optimization) and research on related industrial IT solutions (Industry 4.0, IIoT).

Recent results:

• Design and optimization of Microservices’ architecture
• Creating of multi level production planning algorithm based on mathematical solver
• Optimization of manufacturing processes by appliing artifical intelligence methods

Special infrastructure:

SAP R/3 system and server • SAP Business One system • QAD Enterprise system • ABAS ERP

Recent projects:

FIKP

Software technology

Activity of the research group:

Modelling of distributed large-scale IT systems, research and development of development tools, measurement and verification of software quality parameters. Development of an Immutable metamodelling and translation framework. High level management of distributed IT and Cloud systems using unified frameworks. Well-defined alignment of multiple standards, models, approaches to support software quality, and to investigate and support the specificities of software development in a multimodal (multiple quality approaches simultaneously) environment.

Recent results:

• Industrial cooperation on the use of code generators led by Prolan
• Design, operation and development of the VIK faculty cloud (CIRCLE)
• Participation in an international project to harmonise CMMI V2 and TMMi models (quality management, software process auditing)
• CircleCloud: a much simpler and resource-efficient platform than openstack, open source
• Joker: virtual cluster for high computational power tasks

Special infrastructure:

Superman supercomputer • Batman supercomputer

Recent projects:

IoTAC; Horizon 2020 • Urban Mobility KIC Covid19 call • VKE • EFOP

Industrial partners:

TMMi Foundation • Smartesting Solutions& Services • Pressmen Kft. • Generali Biztosító Zrt. • Prolan Irányítástechikai Zrt.

Software modeling

Activity of the research group:

Creating textual and visual domain-specific languages. Metamodeling and model processing and their validation. Efficient model definition and transformation. Multilevel and multi-layer metamodeling based on the Dynamic Multi-Layer Algebra framework. Model-based software development methodologies. Building compilers and graph transformations.

Recent results:

The research team has been researching mainly in the field of multilevel metamodeling in recent years. In the past, many ideas have been born in this field by other researchers and it has been difficult to compare these ideas. The research team is involved in the process of unifying variants in the field of multilevel metamodeling. In the spring of 2020, we began working with the group on a general approach (Multi-Level Modeling Playground, MLMP) that allows for the emulation and even combination of solutions using a single system. The method has been published in one of the most important journals in the field, and its implementation is in an experimental phase.

Recent projects:

EFOP

International relations:

University of Agder

Critical systems – ftsrg

Activity of the research group:

Our main area is the design of resilient critical systems, processes and platforms, including cyber-physical and distributed ledger systems. Our main competencies are model-based design, analysis and verification.

• Developing critical systems: Methods, techniques and tools to develop model-based critical software and cyber-physical systems and application.
• Verification and testing: Applying formal methods and model-based testing to verify and certify functional, reliability, safety and performance requirements.
• Empirical system design: Empirical analysis, measurement and scaling of performance and reliability requirements based on qualitative models and fault modelling.

Recent results:

• Verification of critical systems: We developed efficient methods and open-source tools to verify the functional correctness of state machine-based models or source code. Industrial case studies include CERN, NASA JPL. See our tools on GitHub.
• Assessing blockchain systems: We benchmarked the performance of distributed ledgers, and developed methods to assess the reliability of blockchain systems using fault injection.
• Scalable graph generation: We created scalable methods and tools to generate diverse, consistent and realistic graph models. The tool can be used to test complex modeling environments or ADAS functions and autonomous vehicles. The method was presented at the ICSE conference, the most prestigious software engineering event.
• Safety and hazard analysis: We designed new algorithms and tools to analyze the safety of vehicle and railway control systems. We regularly perform standard based safety assessment of the development of railway control software.
• International awards: Our publications received the prestigious 10 Year Most Influential Paper Award of the software and systems modeling field in 2021, 2020 and 2014.
• Talent care: Our students perform exceptionally on the National Student Competition; 4 members of the group received the OTDT Master Teacher award; András Pataricza received the highest award of OTDT, the Honoris Causa Pro Scientia.

Recent projects:

EU Digital: EDGE-Skills • EU Digital: SME4DD • EIT Digital: ProtectME • ITEA4 EUREKA: OpenSCALING • H2020 RISE: ADVANCE • VKE: Prolan • MTA Lendület

International relations:

University of Firenze • Univ. Of Coimbra • NASA JPL • McGill University • Linköping University

Industrial partners:

thyssenkrupp • Ericsson • IncQuery Labs • Knorr-Bremse • Prolan

Cognitive computing

Activity of the research group:

The aim of the research group is to develop procedures that rely on wearable physiological measuring instruments, mostly to monitor and make learning more effective. Research and implementation of virtual and augmented reallity applications is also in focus, within industrial application areas.

Recent results:

• Designing a software framework, identifying measurement processes, finding the definitive variables and the relationship between them
• Preprocessing algorithm for uniform classification of fMRI images
• Defining mental states, designing profile curves and classifiers from ECG, EEG and pupil data
• Design and build a software package to validate results

Special infrastructure:

Google Pixel devices • DayDream VR • Samsung Gear VR devices, controllers • Mobil EEG (eMotive) • Hololens

International relations:

Stanford University

Industrial partners:

Audi • Academy of Music

CrySyS Lab

Activity of the research group:

Our research group works in 3 domains within the field of security and privacy:

1. security of cyber-physical systems,
2. security and privacy problems in machine learning-based systems,
3. economics of security and privacy.

In domain (1), we work on the security of industrial automation and control systems, security of modern vehicles and intelligent transport systems, and security of IoT systems and applications. The common in these topics is that attacks originating from cyberspace may have physical consequences, resulting in equipment or environmental damage, or potentially even loss of human life, and therefore, security is an important requirement. In domain (2), we study how machine learning can be used to solve security and privacy problems, and also how machine learning–based systems may be exploited maliciously. More specifically, we focus on the security of federated learning algorithms and the problem of adversarial examples (e.g., in machine learning-based malware detection). In domain (3), we apply game theoretic models to study the incentive structures in different systems, and the cause of security and privacy problems. Besides the domains mentioned above, we have strong competency in applied cryptography, privacy enhancing technologies, malware analysis, reverse engineering, and secure operation of networks and network-based systems, including IT infrastructure automation.

Recent results:

• In the SETIT project, we developed an efficient anti-virus solution for resource constrained IoT devices, which detects malware with more than 90% accuracy.
• We developed many further security enhancing solutions for IoT devices.
• We constructed new attacks on the vehicle CAN bus, and proposed multiple attack detection mechanisms.
• We analyzed what information can be extracted from recorded CAN traffic, and showed that it is possible to identify the driver solely from the raw CAN data.
• We designed and implemented honeypots for ICS/SCADA systems.
• We achieved pioneering results in the field of interdependent privacy, which gave the theoretical explanations for the Cambridge Analytica scandal.
• We proposed new privacy-preserving federated machine learning algorithms.

Special infrastructure:

IoT devices, PLCs, industrial devices, servers • PIRAMID ICS/SCADA security testbed

Recent projects:

PrOTectME (EIT Digital) • H2020 MELLODDY • H2020 SECREDAS • H2020 SETIT

International relations:

NTNU, Trondheim, Norway • KU Leuven, Belgium • INRIA Rhones-Alpes, France • University of California, Irvine, CA • New York Institute of Technology

Industrial partners:

Microsec Zrt. • Tresorit Kft. • Ukatemi Technologies Kft.

Applied IT technology

Activity of the research group:

The Applied Computer Science group’s research interests include software development methods, efficient and maintainable development techniques, and testing. Other research areas include scalable software architectures and environments, and applied artificial intelligence, machine learning and big data, and business intelligence solutions. This is complemented by the area of smart data collection, which is of particular importance for the design and implementation of large-scale systems.

Recent results:

TODO

Recent projects:

MI Nemzeti Labor • Autonóm Nemzeti Labor • TKP

International relations:

University of Dresden • University of Helsinki

Industrial partners:

Sagemcom • Nokia

Algorithm theory

Activity of the research group:

Kombinatorikus algoritmusok. Klasszikus és kvantumalgoritmusok, bonyolultságelméleti és paraméteres bonyolultságos megközelítések. Ezen belül pl. társadalmi választások, fair hozzárendelések, stabil és népszerű párosítások, hálózatok megbízhatóságának vizsgálata kombinatorikus és játékelméleti módszerekkel. Különböző kvantumos megközelítések (algoritmus, QUBO, kvantumbolyongás) vizsgálata. Logikai és deklaratív programozás.

Recent results:

Számos eredményünk született a fair hozzárendelés területén: többek között bizonyítottuk, hogy 3 ágens esetén az irigység-mentes allokáció keresése NP-teljes feladat (ezzel egy 5 évig nyitott kérdést megválaszolva), ugyanakkor arányos allokáció keresése polinom idejű algoritmussal megoldható; ez utóbbi kérdést általános számú ágens esetén is körbejártuk, feltérképeztük annak paraméteres bonyolultságát és approximálhatóságát. Vizsgáltuk a stabil párosítás probléma sok-paraméteres bonyolultságát abban az esetben, ahol bizonyos ágensek fedését írhatjuk elő: öt vizsgált paraméter minden kombinációjára sikerült a probléma bonyolultságát meghatározni. Foglalkoztunk még a népszerű fenyvesek problémájával is, hatékony egzakt és közelítő algoritmusok megadása mellett számos nehézségi eredményt is bizonyítottunk.

Bizonyítottunk egy olyan új eredményt, aminek segítségével a hálózatok megbízhatóságának játékelméleti eszközökkel való mérésére vonatkozó korábban ismert, matroidelméleti módszereket sikerült a greedoidoknak egy, a matroidoknál bővebb osztályára kiterjeszteni.

Kvantumalgoritmusok körében vizsgáltuk a Fourier-transzformáció alkalmazásanak határait bizonyos algebrai feladatokra. Foglalkoztunk a kvantumalgoritmusok egy fajta használatával a gépi tanulásban, megmutatva, hogy egy mások által javasolt módszer nem sok előnyt ad a klasszikus eljárásokhoz képest. Vizsgáljuk, hogyan lehet klasszikus problémákat a D-Wave (korábbi) kvantumszámítógépébe beágyazni, az ott használt QUBO (quantum unconstrained binary optimization) feladatra átfordítani.

Recent projects:

OTKA

International relations:

Hamburg University of Technology • University of Tübingen • Université Paris Diderot – Paris, Centre for Quantum Technologies • University of Singapore