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Firooz B. Saghezchi

Researcher at University of Aveiro

Publications -  34
Citations -  751

Firooz B. Saghezchi is an academic researcher from University of Aveiro. The author has contributed to research in topics: Energy consumption & Efficient energy use. The author has an hindex of 12, co-authored 31 publications receiving 466 citations.

Papers
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Journal ArticleDOI

A Lightweight Authentication Mechanism for M2M Communications in Industrial IoT Environment

TL;DR: A lightweight authentication mechanism, based only on hash and XOR operations, for M2M communications in IIoT environment is proposed, characterized by low computational cost, communication, and storage overhead, while achieving mutual authentication, session key agreement, device’s identity confidentiality, and resistance against the following attacks.
Journal ArticleDOI

Coalition formation game toward green mobile terminals in heterogeneous wireless networks

TL;DR: Simulation results validate that the proposed approach can effectively double the battery lifetimes of MTs, while successfully eliminating selfish players from cooperative groups.
Journal ArticleDOI

An autonomous privacy-preserving authentication scheme for intelligent transportation systems

TL;DR: This paper proposes an autonomous privacy-preserving authentication scheme, where vehicles only need to contact the TA once; afterward, they can renew their pseudonyms by themselves without communicating with the TA.
Book ChapterDOI

Cooperative Strategies for Power Saving in Multi-standard Wireless Devices

TL;DR: In this article, cognitive radio and cooperative communication can be integrated in 4G networks to conduct wireless devices to either perform vertical handover or execute relaying by exploiting their available short range interfaces (e.g., WiMedia, Bluetooth, etc).
Journal ArticleDOI

HIDROID: Prototyping a Behavioral Host-Based Intrusion Detection and Prevention System for Android

TL;DR: This paper develops a novel Host-based IDPS for Android (HIDROID), which runs completely on a mobile device, with a minimal computation burden, and is well able to learn and discriminate normal from malicious behavior.