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Markus Miettinen
Markus Miettinen
Faculty of Computer Science and Engineering, Frankfurt University of Applied Sciences
Verified email at fb2.fra-uas.de
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Cited by
Cited by
Year
IoT Sentinel: Automated device-type identification for security enforcement in iot
M Miettinen, S Marchal, I Hafeez, N Asokan, AR Sadeghi, S Tarkoma
2017 IEEE 37th international conference on distributed computing systems …, 2017
7932017
DÏoT: A federated self-learning anomaly detection system for IoT
TD Nguyen, S Marchal, M Miettinen, H Fereidooni, N Asokan, AR Sadeghi
2019 IEEE 39th International conference on distributed computing systems …, 2019
6052019
The mobile data challenge: Big data for mobile computing research
JK Laurila, D Gatica-Perez, I Aad, O Bornet, TMT Do, O Dousse, J Eberle, ...
Pervasive computing, 2012
6032012
Peek-a-boo: I see your smart home activities, even encrypted!
A Acar, H Fereidooni, T Abera, AK Sikder, M Miettinen, H Aksu, M Conti, ...
Proceedings of the 13th ACM Conference on Security and Privacy in Wireless …, 2020
3212020
Audi: Toward autonomous IoT device-type identification using periodic communication
S Marchal, M Miettinen, TD Nguyen, AR Sadeghi, N Asokan
IEEE Journal on Selected Areas in Communications 37 (6), 1402-1412, 2019
2052019
Method and apparatus for adjusting context-based factors for selecting a security policy
MJ Miettinen, N Asokan, A Gupta
US Patent 8,898,793, 2014
1762014
FLAME: Taming backdoors in federated learning
TD Nguyen, P Rieger, H Chen, H Yalame, H Möllering, H Fereidooni, ...
31st USENIX Security Symposium (USENIX Security 22), 1415-1432, 2022
1632022
Context-based zero-interaction pairing and key evolution for advanced personal devices
M Miettinen, N Asokan, TD Nguyen, AR Sadeghi, M Sobhani
Proceedings of the 2014 ACM SIGSAC conference on computer and communications …, 2014
1602014
Safelearn: Secure aggregation for private federated learning
H Fereidooni, S Marchal, M Miettinen, A Mirhoseini, H Möllering, ...
2021 IEEE Security and Privacy Workshops (SPW), 56-62, 2021
1482021
Poisoning attacks on federated learning-based IoT intrusion detection system
TD Nguyen, P Rieger, M Miettinen, AR Sadeghi
Proc. Workshop Decentralized IoT Syst. Secur.(DISS) 79, 2020
1302020
From big smartphone data to worldwide research: The mobile data challenge
JK Laurila, D Gatica-Perez, I Aad, J Blom, O Bornet, TMT Do, O Dousse, ...
Pervasive and Mobile Computing 9 (6), 752-771, 2013
1292013
HomeSnitch: behavior transparency and control for smart home IoT devices
TJ OConnor, R Mohamed, M Miettinen, W Enck, B Reaves, AR Sadeghi
Proceedings of the 12th conference on security and privacy in wireless and …, 2019
1262019
Conxsense: automated context classification for context-aware access control
M Miettinen, S Heuser, W Kronz, AR Sadeghi, N Asokan
Proceedings of the 9th ACM symposium on Information, computer and …, 2014
1142014
Host-based intrusion detection for advanced mobile devices
K Hatonen, P Halonen, M Miettinen
20th International Conference on Advanced Information Networking and …, 2006
972006
Method and apparatus for selecting a security policy
MJ Miettinen, N Asokan
US Patent 8,621,656, 2013
962013
Method and apparatus for compressing log record information
K Hätönen, M Miettinen
US Patent 7,778,979, 2010
952010
Mind the gap: Security & privacy risks of contact tracing apps
L Baumgärtner, A Dmitrienko, B Freisleben, A Gruler, J Höchst, ...
2020 IEEE 19th international conference on trust, security and privacy in …, 2020
892020
A probabilistic kernel method for human mobility prediction with smartphones
TMT Do, O Dousse, M Miettinen, D Gatica-Perez
Pervasive and Mobile Computing 20, 13-28, 2015
872015
DÏoT: A self-learning system for detecting compromised IoT devices
TD Nguyen, S Marchal, M Miettinen, N Asokan, A Sadeghi
CoRR, vol. abs/1804.07474, 2018
842018
Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection
P Rieger, TD Nguyen, M Miettinen, AR Sadeghi
arXiv preprint arXiv:2201.00763, 2022
832022
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