Zobrazeno 1 - 10
of 192
pro vyhledávání: '"Miettinen, Markus"'
On the microscopic level, biological signal transmission relies on coordinated structural changes in allosteric proteins that involve sensor and effector modules. The timescales and microscopic details of signal transmission in proteins are often unc
Externí odkaz:
http://arxiv.org/abs/2403.12312
Unleashing IoT Security: Assessing the Effectiveness of Best Practices in Protecting Against Threats
The Internet of Things (IoT) market is rapidly growing and is expected to double from 2020 to 2025. The increasing use of IoT devices, particularly in smart homes, raises crucial concerns about user privacy and security as these devices often handle
Externí odkaz:
http://arxiv.org/abs/2308.12072
Autor:
Rieger, Phillip, Chilese, Marco, Mohamed, Reham, Miettinen, Markus, Fereidooni, Hossein, Sadeghi, Ahmad-Reza
IoT application domains, device diversity and connectivity are rapidly growing. IoT devices control various functions in smart homes and buildings, smart cities, and smart factories, making these devices an attractive target for attackers. On the oth
Externí odkaz:
http://arxiv.org/abs/2302.07589
Autor:
Rieger, Phillip, Krauß, Torsten, Miettinen, Markus, Dmitrienko, Alexandra, Sadeghi, Ahmad-Reza
Federated Learning (FL) is a promising approach enabling multiple clients to train Deep Neural Networks (DNNs) collaboratively without sharing their local training data. However, FL is susceptible to backdoor (or targeted poisoning) attacks. These at
Externí odkaz:
http://arxiv.org/abs/2210.07714
Autor:
Nguyen, Thien Duc, Miettinen, Markus, Dmitrienko, Alexandra, Sadeghi, Ahmad-Reza, Visconti, Ivan
The COVID-19 pandemic has caused many countries to deploy novel digital contact tracing (DCT) systems to boost the efficiency of manual tracing of infection chains. In this paper, we systematically analyze DCT solutions and categorize them based on t
Externí odkaz:
http://arxiv.org/abs/2202.06698
Federated Learning (FL) allows multiple clients to collaboratively train a Neural Network (NN) model on their private data without revealing the data. Recently, several targeted poisoning attacks against FL have been introduced. These attacks inject
Externí odkaz:
http://arxiv.org/abs/2201.00763
Autor:
Miettinen, Markus
During the last decade, two major technological changes have profoundly changed the way in which users consume and interact with on-line services and applications. The first of these has been the success of mobile computing, in particular that of sma
Externí odkaz:
https://tuprints.ulb.tu-darmstadt.de/8374/7/Miettinen-dissertation-context-communication-profiling-iot-security-privacy.pdf
Autor:
Nguyen, Thien Duc, Rieger, Phillip, Chen, Huili, Yalame, Hossein, Möllering, Helen, Fereidooni, Hossein, Marchal, Samuel, Miettinen, Markus, Mirhoseini, Azalia, Zeitouni, Shaza, Koushanfar, Farinaz, Sadeghi, Ahmad-Reza, Schneider, Thomas
Federated Learning (FL) is a collaborative machine learning approach allowing participants to jointly train a model without having to share their private, potentially sensitive local datasets with others. Despite its benefits, FL is vulnerable to bac
Externí odkaz:
http://arxiv.org/abs/2101.02281
Autor:
Antila, Hanne S., Wurl, Anika, Ollila, O. H. Samuli, Miettinen, Markus S., Ferreira, Tiago M.
Cells use homeostatic mechanisms to maintain an optimal composition of distinct types of phospholipids in cellular membranes. The hydrophilic dipolar layer at the membrane interface, composed of phospholipid headgroups, regulates the interactions bet
Externí odkaz:
http://arxiv.org/abs/2009.06774
Manufacturers of smart home Internet of Things (IoT) devices are increasingly adding voice assistant and audio monitoring features to a wide range of devices including smart speakers, televisions, thermostats, security systems, and doorbells. Consequ
Externí odkaz:
http://arxiv.org/abs/2007.00500