145 citations · 543 across the 25 of their papers we have counts for
6 papers · 1 filter
Securing Federated Learning against Overwhelming Collusive Attackers
Priyesh Ranjan, Ashish Gupta, Federico Corò +1
In the era of a data-driven society with the ubiquity of Internet of Things (IoT) devices storing large amounts of data localized at different places, distributed learning has gain…
Suppressing Noise from Built Environment Datasets to Reduce Communication Rounds for Convergence of Federated Learning
Rahul Mishra, Hari Prabhat Gupta, Tanima Dutta +1
Smart sensing provides an easier and convenient data-driven mechanism for monitoring and control in the built environment. Data generated in the built environment are privacy sensi…
Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning
Ashish Gupta, Tie Luo, Mao V. Ngo +1
Federated learning offers a framework of training a machine learning model in a distributed fashion while preserving privacy of the participants. As the server cannot govern the cl…
Accurate and Efficient Modeling of 802.15.4 Unslotted CSMA/CA through Event Chains Computation
Domenico De Guglielmo, Francesco Restuccia, Giuseppe Anastasi +2
Many analytical models have been proposed for evaluating the performance of event-driven 802.15.4 Wireless Sensor Networks (WSNs), in Non-Beacon Enabled (NBE) mode. However, existi…
The Internet of People (IoP): A New Wave in Pervasive Mobile Computing
Marco Conti, Andrea Passarella, Sajal K. Das
Cyber-Physical convergence, the fast expansion of the Internet at its edge, and tighter interactions between human users and their personal mobile devices push towards an Internet…
Service Provisioning in Mobile Environments through Opportunistic Computing
Davide Mascitti, Marco Conti, Andrea Passarella +2
Opportunistic computing is a paradigm for completely self-organised pervasive networks. Instead of relying only on fixed infrastructures as the cloud, users' devices act as service…