Security framework for supply chain IoT devices based on dynamic watermarking algorithm

The role of Internet of Things (IoT) devices in the supply chain is becoming increasingly significant, but at the same time, they face escalating security threats. Due to the characteristics of IoT device networks and the evolving attack methods, traditional cybersecurity measures offer limited prot...

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Main Author: Gu, Lei
Other Authors: Chen Songlin
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/172202
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1722022023-12-02T16:51:55Z Security framework for supply chain IoT devices based on dynamic watermarking algorithm Gu, Lei Chen Songlin School of Mechanical and Aerospace Engineering Songlin@ntu.edu.sg Engineering::Industrial engineering The role of Internet of Things (IoT) devices in the supply chain is becoming increasingly significant, but at the same time, they face escalating security threats. Due to the characteristics of IoT device networks and the evolving attack methods, traditional cybersecurity measures offer limited protection for IoT device networks in the supply chain. Therefore, it is necessary to develop a dedicated security framework. This dissertation proposes a security framework that includes the dynamic watermarking system and the anomaly cause analysis system running on the gateways of the IoT device network. The former uses the Long Short-Term Memory (LSTM) method to achieve dynamic watermark encryption and decoding on signal packets, protecting the transferred information from being leaked. It also includes an anomaly detection module to determine the trustworthiness of received signal packets and their corresponding sending devices. The latter builds a game between the IoT device networks and attackers, determining the weak points and root causes of anomalies based on the optimal choices of both players, which helps supply chain managers allocate defense resources rationally and reduce the risk and losses of being attacked. To test the performance of the proposed security framework, we conducted a simulation experiment. The results indicate that the LSTM model training for the dynamic watermarking system performs excellently, with the detection module achieving the required performance metrics in different conditions. The anomaly cause analysis system can provide the system's root anomaly cause and weakest link based on historical data, thereby improving the security level of IoT devices in the simulated supply chain system. Master of Science (Supply Chain and Logistics) 2023-11-29T04:42:54Z 2023-11-29T04:42:54Z 2023 Thesis-Master by Coursework Gu, L. (2023). Security framework for supply chain IoT devices based on dynamic watermarking algorithm. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172202 https://hdl.handle.net/10356/172202 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Industrial engineering
spellingShingle Engineering::Industrial engineering
Gu, Lei
Security framework for supply chain IoT devices based on dynamic watermarking algorithm
description The role of Internet of Things (IoT) devices in the supply chain is becoming increasingly significant, but at the same time, they face escalating security threats. Due to the characteristics of IoT device networks and the evolving attack methods, traditional cybersecurity measures offer limited protection for IoT device networks in the supply chain. Therefore, it is necessary to develop a dedicated security framework. This dissertation proposes a security framework that includes the dynamic watermarking system and the anomaly cause analysis system running on the gateways of the IoT device network. The former uses the Long Short-Term Memory (LSTM) method to achieve dynamic watermark encryption and decoding on signal packets, protecting the transferred information from being leaked. It also includes an anomaly detection module to determine the trustworthiness of received signal packets and their corresponding sending devices. The latter builds a game between the IoT device networks and attackers, determining the weak points and root causes of anomalies based on the optimal choices of both players, which helps supply chain managers allocate defense resources rationally and reduce the risk and losses of being attacked. To test the performance of the proposed security framework, we conducted a simulation experiment. The results indicate that the LSTM model training for the dynamic watermarking system performs excellently, with the detection module achieving the required performance metrics in different conditions. The anomaly cause analysis system can provide the system's root anomaly cause and weakest link based on historical data, thereby improving the security level of IoT devices in the simulated supply chain system.
author2 Chen Songlin
author_facet Chen Songlin
Gu, Lei
format Thesis-Master by Coursework
author Gu, Lei
author_sort Gu, Lei
title Security framework for supply chain IoT devices based on dynamic watermarking algorithm
title_short Security framework for supply chain IoT devices based on dynamic watermarking algorithm
title_full Security framework for supply chain IoT devices based on dynamic watermarking algorithm
title_fullStr Security framework for supply chain IoT devices based on dynamic watermarking algorithm
title_full_unstemmed Security framework for supply chain IoT devices based on dynamic watermarking algorithm
title_sort security framework for supply chain iot devices based on dynamic watermarking algorithm
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/172202
_version_ 1784855581143597056