0% Complete
صفحه اصلی
/
سی و یکمین کنفرانس بین المللی مهندسی برق
Manifold Learning-Assisted Physical Layer Key Generation for LoRaWAN: an Experimental Study
نویسندگان :
Hossein Aghajari
1
Hamed Bakhtiari babadegani,
2
Mehdi Naderi soorki
3
Sajad Ahmadinabi
4
Seyed mohsen Ahmadi
5
1- دانشگاه شهید چمران اهواز
2- دانشگاه شهید چمران اهواز
3- دانشگاه شهید چمران اهواز
4- دانشگاه شهید چمران اهواز
5- دانشگاه شهید چمران اهواز
کلمات کلیدی :
LoRa technology،Wireless link key،Physical Layer Security،Manifold learning
چکیده :
Long Range Wide Area Network (LoRaWAN) has been widely proposed as one of the main promising access networks for the battery-constrained internet of things (IoT) device. Although LoRaWAN already provides many security features such as data confidentiality and integrity between LoRa end nodes (ENs) and application servers at the core, there is a lack of schemes to manage and distribute secure wireless keys between LoRa ENs and gateways at wireless access. In this paper, an efficient physical layer security-based scheme is proposed which explores the randomness of the received signal strength index (RSSI) of LoRa wireless signals to generate link key. Due to the resource constraints LoRa nodes, manifold learning methods are applied to reduce the dimensionality of measured data of channel vectors for initial key generation. Then, a bit disagreement in the initial keys between LoRa EN and gateway are detected and corrected by means of error correction coding. Finally, to prevent information leakage in the presence of attacked node, the cryptographic hashing algorithm is utilized to generate the final key from the initial keys. To analyze the performance of the proposed manifold learning-assisted physical layer key generation in real world, several experiments for different wireless LoRa links such as line-of-sight (LoS), non-LoS, and tree-covered areas are performed over the campus of Shahid Chamran University of Ahvaz. Our analysis of the experimental measurement shows that even when the attacker node is at 50 cm distance from the LoRa EN to recover the Link key, the bit disagreement rate between legitimate EN and attacker keys is 20% in all measurement scenarios. Moreover, we also find that the local tangent space alignment method for manifold learning leads to better security performance.
لیست مقالات
لیست مقالات بایگانی شده
ارائه ساختار پیشنهادی ترانسفورماتور حالت جامد یک سویه در بهره برداری از شبکه های توزیع
بهنام بهارلوئی - رضا قندهاری - مهدی بابایی - یوسف عطائی
Semi-supervised Deep Reinforcement Learning in Decentralized Multi-Agent Collision Avoidance and Path Planning in a Complex Environment
Marzie Parooei - Mehdi Tale Masouleh - Ahmad Kalhor
Enhanced Optimal Droop Control for Effective Load Sharing in an Islanded Microgrid
Rafi Zahedi - Hassan Rastegar
طراحی کنترلکننده استروباسکوپ زمان واقعی مبتنی بر هوش مصنوعی برای سیستم های دورانی
مهدی مظفری - سعید جعفری نسب - حامد پورکاوه - سعید شمقدری
Integration of Deep Learning Techniques in Stock Market Forecasting: xLSTM-CNN with RevIN and Adaptive Wavelet Denoising
Alireza Mohammadi - Ali Doustmohammadi - Masoud Shafiee
Design and Implementation of a fast flexible and efficient multichannel digital filter for hearing aids
Mohammadsadegh Poushnegar - Mahmoud Tabandeh - Meysam Nesary Moghadam - Farzam Gilani - Ali Aghakasiri
Design an Intelligent Fault Detection System for Spring-Drive Operating Mechanism of SF6 High Voltage Circuit Breaker Using ADAMS
Milad Tahvilzadeh - Mehdi Aliyari Shooredeli - Ali asghar Razi Kazemi
Design of a High-Efficiency RF Energy Harvesting System
Saeed Abbasi FallahPour - Shokrollah Karimian - ٍEsfandiar Mehrshahi
T-type L-2L De-Embedding Method for On-Wafer T-model Transmission Line Network
Milad Seyedi - Nasser Masoumi - Samad Sheikhaei
Design of Dual Frequency Conformal Leaky-wave Holographic Antenna
Mohammad Amin Chaychi zadeh - Nader Komjani
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.5.3