PSL-IoD: PUF-Based Secure Last-Mile Drone Delivery in Supply Chain Management

The conventional supply chain management has undergone major advancements following IoT-enabled revolution. The IoT-enabled drones in particular have ignited much recent attention for package delivery in logistics. The service delivery paradigm in logistics has seen a surge in drone-assisted package deliveries and tracking. There have been a lot of recent research proposals on various aspects of last-mile delivery systems for drones in particular. Although drones have largely changed the logistics landscape, there are many concerns regarding security and privacy posed to drones due to their open and vulnerable nature. The security and privacy of involved stakeholders needs to be preserved across the whole chain of Supply Chain Management (SCM) till delivery. Many earlier studies addressed this concern, however with efficiency limitations. We propose a Physical Uncloneable Function (PUF)-based secure authentication protocol (PSL-IoD) using symmetric key operations for reliable last-mile drone delivery in SCM. PSL-IoD ensures mutual authenticity, forward secrecy, and privacy for the stakeholders. Moreover, it is protected from machine learning attacks and drone-related physical capture threats due to embedded PUF installations along with secure design of the protocol. The PSL-IoD is formally analyzed through rigorous security assessments based on the Real-or-Random (RoR) model. The PSL-IoD supports 26.71% of enhanced security traits compared to other comparative studies. The performance evaluation metrics exhibit convincing findings in terms of efficient computation and communication along with enhanced security features, making it viable for practical implementations.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2025-06-30
DOI
https://doi.org/10.3390/math13132143
Citations
1
Primary Topic
Optimization and Search Problems
Type
article
Field-Weighted Citation Impact
1.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PSL-IoD: PUF-Based Secure Last-Mile Drone Delivery in Supply Chain Management

Azeem Irshad, Shehzad Ashraf Chaudhry, Mohammad D. Alahmadi, Ahmed Alzahrani
1 citations
Mathematics
Optimization and Search Problems
1.49
article

PSL-IoD: PUF-Based Secure Last-Mile Drone Delivery in Supply Chain Management

Azeem Irshad, Shehzad Ashraf Chaudhry, Mohammad D. Alahmadi, Ahmed Alzahrani
article en
1 citations

Abstract

The conventional supply chain management has undergone major advancements following IoT-enabled revolution. The IoT-enabled drones in particular have ignited much recent attention for package delivery in logistics. The service delivery paradigm in logistics has seen a surge in drone-assisted package deliveries and tracking. There have been a lot of recent research proposals on various aspects of last-mile delivery systems for drones in particular. Although drones have largely changed the logistics landscape, there are many concerns regarding security and privacy posed to drones due to their open and vulnerable nature. The security and privacy of involved stakeholders needs to be preserved across the whole chain of Supply Chain Management (SCM) till delivery. Many earlier studies addressed this concern, however with efficiency limitations. We propose a Physical Uncloneable Function (PUF)-based secure authentication protocol (PSL-IoD) using symmetric key operations for reliable last-mile drone delivery in SCM. PSL-IoD ensures mutual authenticity, forward secrecy, and privacy for the stakeholders. Moreover, it is protected from machine learning attacks and drone-related physical capture threats due to embedded PUF installations along with secure design of the protocol. The PSL-IoD is formally analyzed through rigorous security assessments based on the Real-or-Random (RoR) model. The PSL-IoD supports 26.71% of enhanced security traits compared to other comparative studies. The performance evaluation metrics exhibit convincing findings in terms of efficient computation and communication along with enhanced security features, making it viable for practical implementations.

MathematicsVol. 13(13)
Abu Dhabi University (AE), Rawalpindi Medical University (PK), King Abdulaziz University (SA), Jadara University (JO), İstanbul Nişantaşı Üniversitesi (TR), University of Jeddah (SA)
Ministry of Education, India
Openalex Percentile: Top 16%
Optimization and Search Problems
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.