@article{jsan14010011,

title = {Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking},

author = {Nikolaos Pavlidis and Andreas Sendros and Theodoros Tsiolakis and Periklis Kostamis and Christos Karasoulas and Eleni Briola and Christos Chrysanthos Nikolaidis and Vasilis Perifanis and George Drosatos and Eleftheria Katsiri and Despoina Elisavet Filippidou and Anastasios Manos and Pavlos Efraimidis},

url = {https://www.mdpi.com/2224-2708/14/1/11},

doi = {10.3390/jsan14010011},

issn = {2224-2708},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Journal of Sensor and Actuator Networks},

volume = {14},

number = {1},

abstract = {In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. Unlike conventional centralized systems, FLORA ensures that sensitive information remains on users’ devices, with predictive algorithms powered by local computations. Blockchain technology provides immutable consent tracking and model update transparency, further improving user trust. In addition, FLORA’s design incentivizes participation through a token-based reward system, fostering collaborative data contributions. This work illustrates how the integration of cutting-edge technologies creates a secure, scalable, and user-centric health application, setting a new standard for privacy-preserving digital health platforms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KOSTAMIS2024193,

title = {Data management in Ethereum DApps: A cost and performance analysis},

author = {Periklis Kostamis and Andreas Sendros and Pavlos Efraimidis},

url = {https://www.sciencedirect.com/science/article/pii/S0167739X23004351},

doi = {https://doi.org/10.1016/j.future.2023.11.026},

issn = {0167-739X},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Future Generation Computer Systems},

volume = {153},

pages = {193-205},

abstract = {The cost of interacting with a blockchain and the time required to search and retrieve information from it are important factors in the design of Decentralized Applications (DApps). The corresponding approaches for data management in Ethereum vary from pure on-chain solutions to hybrid architectures. In this work, we thoroughly examine a wide range of data management methods, including unconventional ones, and evaluate them in terms of storage cost and retrieval latency while considering the impact of recent hard forks. More precisely, we elaborate on the use of Smart Contract (SC) storage as a data store for DApps and in view of the prohibitive cost inherent to this approach, we present and compare methods for low-cost data handling in Ethereum, namely the event-logs, the transaction payload, and the almost surprising exploitation of unused function arguments. In addition, we study hybrid schemes by using IPFS and Swarm as storage platforms and Ethereum as a timestamping proof mechanism. Such schemes are especially effective when large chunks of data have to be managed. The upload and retrieval performance of these platforms and the cost associated with storing (on-chain) the identifiers of the uploaded data are of utmost importance and therefore are investigated in detail.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tsourgiannis2024effectb,

title = {The effect of COVID-19 on tourist behaviour},

author = {Lambros Tsourgiannis and Stavros Valsamidis and Pavlos Efraimidis and George Drosatos},

url = {https://doi.org/10.1504/IJTMKT.2024.135671},

year  = {2024},

date = {2024-04-04},

urldate = {2024-04-04},

journal = {International Journal of Technology Marketing},

volume = {18},

number = {1},

pages = {1-19},

abstract = {This paper investigates the impact of COVID-19 on tourists' attitudes regarding their decision to go on holidays and to classify them into groups based on their attitudes. The study aims to explore the effect of the pandemic on tourists' behaviour in a context where tourism plays a significant role from a cultural and economic perspective. Therefore, a primary survey was undertaken in the summer of 2020 on 1,260 Greek tourists that were selected at random. Principal component analysis was conducted to identify the key dimensions that describe the main attitudes of Greek tourists due to COVID-19, regarding their decision to go on holidays including entertainment out of the hotel, eating inside the hotel and entertainment with not organised activities. All the aforementioned affect the Greek tourists in their decision to go on holidays due to COVID-19 pandemic.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Drosatos_2023,

title = {Federated and Transfer Learning Applications},

author = {George Drosatos and Pavlos Efraimidis and Avi Arampatzis},

url = {http://dx.doi.org/10.3390/app132111722},

doi = {10.3390/app132111722},

issn = {2076-3417},

year  = {2023},

date = {2023-10-01},

urldate = {2023-10-01},

journal = {Applied Sciences},

volume = {13},

number = {21},

pages = {11722},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}