Privacy-preserving security of IoT networks: A comparative analysis of methods and applications
The Internet of Things (IoT) connects devices to enhance efficiency, productivity, and quality of life. However, deploying IoT networks introduces critical privacy and security challenges, including resource constraints, scalability issues, interoperability gaps, and risks to data privacy. Addressin...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-12-01
|
| Series: | Cyber Security and Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772918425000013 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841545527698653184 |
|---|---|
| author | Abubakar Wakili Sara Bakkali |
| author_facet | Abubakar Wakili Sara Bakkali |
| author_sort | Abubakar Wakili |
| collection | DOAJ |
| description | The Internet of Things (IoT) connects devices to enhance efficiency, productivity, and quality of life. However, deploying IoT networks introduces critical privacy and security challenges, including resource constraints, scalability issues, interoperability gaps, and risks to data privacy. Addressing these challenges is vital to ensure the reliability and trustworthiness of IoT applications. This study provides a comprehensive analysis of privacy-preserving security methods, evaluating cryptography, blockchain, machine learning, and fog/edge computing against performance indicators such as scalability, efficiency, robustness, and usability. Through a structured literature review and thorough data analysis, the study reveals that while cryptography offers high security, it faces scalability challenges; blockchain excels in decentralization but struggles with efficiency; machine learning provides adaptive intelligence but raises privacy concerns; and fog/edge computing delivers low-latency processing yet encounters operational complexities. The findings highlight the importance of adopting a hybrid approach that combines the strengths of various methods to overcome their limitations. This study serves as a valuable resource for academia, industry professionals, and policymakers, providing guidance to strengthen IoT infrastructures and influence the direction of future research. |
| format | Article |
| id | doaj-art-aa0ec78d4eba44109e51eb57b648f6e0 |
| institution | Kabale University |
| issn | 2772-9184 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Cyber Security and Applications |
| spelling | doaj-art-aa0ec78d4eba44109e51eb57b648f6e02025-01-12T05:26:20ZengKeAi Communications Co., Ltd.Cyber Security and Applications2772-91842025-12-013100084Privacy-preserving security of IoT networks: A comparative analysis of methods and applicationsAbubakar Wakili0Sara Bakkali1Corresponding author.; Euromed University of Fez, MoroccoEuromed University of Fez, MoroccoThe Internet of Things (IoT) connects devices to enhance efficiency, productivity, and quality of life. However, deploying IoT networks introduces critical privacy and security challenges, including resource constraints, scalability issues, interoperability gaps, and risks to data privacy. Addressing these challenges is vital to ensure the reliability and trustworthiness of IoT applications. This study provides a comprehensive analysis of privacy-preserving security methods, evaluating cryptography, blockchain, machine learning, and fog/edge computing against performance indicators such as scalability, efficiency, robustness, and usability. Through a structured literature review and thorough data analysis, the study reveals that while cryptography offers high security, it faces scalability challenges; blockchain excels in decentralization but struggles with efficiency; machine learning provides adaptive intelligence but raises privacy concerns; and fog/edge computing delivers low-latency processing yet encounters operational complexities. The findings highlight the importance of adopting a hybrid approach that combines the strengths of various methods to overcome their limitations. This study serves as a valuable resource for academia, industry professionals, and policymakers, providing guidance to strengthen IoT infrastructures and influence the direction of future research.http://www.sciencedirect.com/science/article/pii/S2772918425000013Privacy-preserving securityInternet of Things (IoT) networksCryptographyBlockchainMachine learningFog/edge computing |
| spellingShingle | Abubakar Wakili Sara Bakkali Privacy-preserving security of IoT networks: A comparative analysis of methods and applications Cyber Security and Applications Privacy-preserving security Internet of Things (IoT) networks Cryptography Blockchain Machine learning Fog/edge computing |
| title | Privacy-preserving security of IoT networks: A comparative analysis of methods and applications |
| title_full | Privacy-preserving security of IoT networks: A comparative analysis of methods and applications |
| title_fullStr | Privacy-preserving security of IoT networks: A comparative analysis of methods and applications |
| title_full_unstemmed | Privacy-preserving security of IoT networks: A comparative analysis of methods and applications |
| title_short | Privacy-preserving security of IoT networks: A comparative analysis of methods and applications |
| title_sort | privacy preserving security of iot networks a comparative analysis of methods and applications |
| topic | Privacy-preserving security Internet of Things (IoT) networks Cryptography Blockchain Machine learning Fog/edge computing |
| url | http://www.sciencedirect.com/science/article/pii/S2772918425000013 |
| work_keys_str_mv | AT abubakarwakili privacypreservingsecurityofiotnetworksacomparativeanalysisofmethodsandapplications AT sarabakkali privacypreservingsecurityofiotnetworksacomparativeanalysisofmethodsandapplications |