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DistPrivacy: Privacy-Aware Distributed Deep Neural Networks in IoT surveillance systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, ...
Fuzzy Elliptic Curve Cryptography for Authentication in Internet of Things
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The security and privacy of the network in Internet of Things (IoT) systems are becoming more critical as we are still more dependent on smart systems. Considering that packets are exchanged between the end user and the ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
(
IEEE Computer Society
, 2021 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These ...
3-D Stochastic Geometry-based Modeling and Performance Analysis of Efficient Security Enhancement scheme for IoT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Internet of Things (IoT) systems are becoming core building blocks for different services and applications supporting every day’s life. The heterogeneous nature of IoT devices and the complex use scenarios make it ...
Privacy-Preserving Distributed IDS Using Incremental Learning for IoT Health Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Existing techniques for incremental learning are computationally expensive and produce duplicate features leading to higher false positive and true negative rates. We propose a novel privacy-preserving intrusion detection ...
Performance Evaluation of Hyperledger Fabric
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Blockchain is a distributed secure ledger that eliminates the need for centralized authority to store data. The centralized approach has several limitations as it is a Single-Point-of-Failure and a third-party might be ...
Hierarchical Federated Learning for Collaborative IDS in IoT Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart houses, healthcare, and transportation, extremely huge amounts of data are being gathered, shared, and processed. This fact raises ...
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
(
Elsevier B.V.
, 2022 , Article)
Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. It is a promising solution for telemonitoring ...