Timo Hämäläinen
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ORCID link: http://orcid.org/0000-0002-4168-9102
Active JYU affiliations
Previous or other affiliations
- Timo Hämäläinen, Faculty of Information Technology (University of Jyväskylä), Professor
Research interests
My research develops methods for managing networks and resources (QoS), in particular improving the network security. The importance of information security and network reliability increases as the digitalization will be everywhere. We need new and more effective ways to manage the network resources
Projects as Principal investigator
- AI-driven Malware-Tolerant Network for IoT
- Business Finland
- Business Growth from IoT
- Council of Tampere Region
- CIMO Fellowship/ Biying Wang
- Finnish National Agency for Education
- Ecological, intelligent and secured IoT services
- Council of Tampere Region
- Improving crisis and situation information in Central Finland.
- Regional Council of Central Finland
- IZI - Intelligent Zero-Trust Network for IoT
- European Commission
- Perusteollisuuden parhaat IoT-ratkaisut
- Regional Council of Central Finland
Projects as Team Member
- Cyber Trust
- Neittaanmäki, Pekka
- TEKES
Publications
- Factors affecting Nigerian teacher educators’ technology integration : Considering characteristics, knowledge constructs, ICT practices and beliefs (2020) Ifinedo, Eloho; et al.; A1; OA
- Incentive Mechanism for Resource Allocation in Wireless Virtualized Networks with Multiple Infrastructure Providers (2020) Chang, Zheng; et al.; A1; OA;
- ISAdetect : Usable Automated Detection of CPU Architecture and Endianness for Executable Binary Files and Object Code (2020) Kairajärvi, Sami; et al.; A4; OA
- Leveraging the benefits of big data with fast data for effective and efficient cybersecurity analytics systems : A robust optimisation approach (2020) Rathod, Paresh; et al.; A4; OA
- Linear Approximation Based Compression Algorithms Efficiency to Compress Environmental Data Sets (2020) Väänänen, Olli; et al.; A4; 978-3-030-44038-1
- Reinforcement Learning for Attack Mitigation in SDN-enabled Networks (2020) Zolotukhin, Mikhail; et al.; A4; 978-1-7281-5684-2
- Analysing the Nigerian Teacher’s Readiness for Technology Integration (2019) Ifinedo, Eloho; et al.; A1; OA
- A Novel Deep Learning Stack for APT Detection (2019) Bodström, Tero; et al.; A1; OA
- Assessment of Deep Learning Methodology for Self-Organizing 5G Networks (2019) Asghar, Muhammad Zeeshan; et al.; A1; OA
- Compression methods for microclimate data based on linear approximation of sensor data (2019) Väänänen, Olli; et al.; A4; OA; 978-3-030-30859-9
- Cyber security exercise : Literature review to pedagogical methodology (2019) Hautamäki, J.; et al.; B3; OA
- Deep in the Dark : A Novel Threat Detection System using Darknet Traffic (2019) Kumar, Sanjay; et al.; A4; 978-1-7281-0858-2
- Network anomaly detection in wireless sensor networks : a review (2019) Leppänen, Rony Franca; et al.; A4; 978-3-030-30859-9
- Predictive pumping based on sensor data and weather forecast (2019) Väänänen, Olli; et al.; A4; OA
- A contract-based resource allocation mechanism in wireless virtualized network (2018) Zhang, Di; et al.; A4
- A Network-Based Framework for Mobile Threat Detection (2018) Kumar, Sanjay; et al.; A4; OA
- A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory (2018) Bodström, Tero; et al.; A4; OA
- Automatic Taxonomy Induction based on Word-embedding of Neural Nets (2018) Zafar, Bushra; et al.; A1; OA
- Data stream clustering for application-layer DDoS detection in encrypted traffic (2018) Zolotukhin, Mikhail; et al.; A3
- FRUCT : Proceedings of the 22nd Conference of Open Innovations Association FRUCT, Jyväskylä, Finland, 15-18 May 2018 (2018) Balandin, Sergey; et al.; C2; OA