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A Privacy-Preserving Framework for IoT Using Behavior Obfuscation and Differential Privacy in Blockchain–Cloud Architectures

Journal of Robotics and Control (JRC) · Vol. 6 No. 6 (2025) · hlm. 2613–2627

DOI
10.18196/jrc.v6i6.27593
ISSN
2715-5072, 2715-5056
Terbit
2025-11-07
Penerbit
Universitas Muhammadiyah Yogyakarta
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Rapidly growing Internet of Things (IoT) networks pose many fundamentally important privacy challenges, particularly when combined with transparent technologies such as the blockchain. Although blockchain provides distributed trust and auditability, its immutable logs can inadvertently leak user behavior. In this paper, we take on this problem by presenting a privacy-preserving approach for IoT systems, which is informed by the confluence of behavior obfuscation and differential privacy technology, run atop a hybrid blockchain-cloud infrastructure. The research result is a five-phase model which makes devices’ behaviors look like exactly-anonymous devices at the edge and is based on formal privacy guarantees by employing differential privacy in the cloud. To achieve this, we propose a framework that consists of light-weight obfuscation operators—timestamp perturbation, dummy event injection, and activity reordering—that, when synergistically used with the state-of-the-art, media-centric, differentially private solutions in the cloud, offer justifiable privacy against analytical and knowledge-based attacks. Cleaned–up summaries are tentatively submitted to blockchain in a safe way through smart contracts, facilitating traceable, tamper–evident logging without revealing raw behavioral information obtained from the data owner. Experimental results based on a Raspberry Pi-based IoT testbed and Ethereum-compatible blockchain show that the proposed system keeps low latency ( 2.8 s), over 400 events/min throughput, blockchain storage overhead and privacy leakage. Modular, auditable, and real-time-capable approach for secure data sharing in adversarial IoT environments (Applied to healthcare, smart homes, and industrial monitoring).

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  • University of Basrah
  • Southern Technical University
  • Universiti Sains Malaysia
  • Shatt Al-Arab University College
  • University of Kirkuk
  • University of Kerbala
  • University of Jordan
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Rekan penulisOrganisasiArtikel bersama
Mohammed Amin AlmaiahUniversity of Jordan16
Jalal Mohammed Hachim AltmemiSouthern Technical University9
Faris K. AL-ShammriUniversity of Warith Al-Anbiyaa8
Murtaja Ali SaareUniversity of Basrah6
Md Asri NgadiUniversity of Technology Malaysia6
Abdulaziz Zaid A. AljarwanUniversity of Ha'il6
Mansour ObeidatAfiliasi tidak diketahui5
Abdulnasser AbdulJabbar AbboodAfiliasi tidak diketahui5
Ali A. AlaidanyShatt Al-Arab University College5
Selvakumar ManickamUniversiti Sains Malaysia4
Shankar KaruppayahUniversiti Sains Malaysia4
Ghazi Jalal KasheshUniversity of Kerbala4
Rommel Mahmoud AlAliKing Faisal University3
May Adnan FalehSouthern Technical University3
Ali M. AbdulsadaUniversity of Warith Al-Anbiyaa3
Mohamed Abdulrahman AbdulhamedUniversity of Basrah3
Mustafa Moosa QasimUniversity of Basrah3
Akram Hussain Abd AliUniversity of Basrah3
Bushra Abdullah ShtaytSouthern Technical University3
Karrar Ali AbdullahShatt Al-Arab University College3
Ali Adil YassinUniversity of Basrah2
Devamekalai NagasundaramUniversiti Sains Malaysia2
Sababathy PalanisamyUniversiti Sains Malaysia2
Erum AshrafBahria University2
Marwa K. FarhanMinistry of Higher Education and Scientific Research2
Rommel Al AliAfiliasi tidak diketahui2
Saadaldeen Rashid AhmedAl-Ayen Iraqi University2
Nada Mohammed MuradMinistry of Higher Education and Scientific Research2
Mohammed Thakir MahmoodAfiliasi tidak diketahui1
Wassan Adnan HashimAl-Qalam University1
Saadaldeen Rashid AhmedBayan University1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.umy.ac.id/index.php/jrc/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">A Privacy-Preserving Framework for IoT Using Behavior Obfuscation and Differential Privacy in Blockchain–Cloud Architectures</dc:title>
	<dc:creator>Ali, Hussein Ahmed</dc:creator>
	<dc:creator>Khalaf,  Midhat Hussein Ibrahim</dc:creator>
	<dc:creator>Fadek, Samider Abdulabbas</dc:creator>
	<dc:creator>Alsayednoor, Huda Mohammed</dc:creator>
	<dc:creator>Kaishesh, Abbas Jalal</dc:creator>
	<dc:creator>Alzamili, Zainab Marid</dc:creator>
	<dc:creator>Al-Shareeda‬‏, ‪Mahmood A.</dc:creator>
	<dc:creator>Almaiah, Mohammed Amin</dc:creator>
	<dc:creator>Shehab, Rami</dc:creator>
	<dc:subject xml:lang="en-US">Internet of Things (IoT)</dc:subject>
	<dc:subject xml:lang="en-US">Privacy Preservation</dc:subject>
	<dc:subject xml:lang="en-US">Differential Privacy</dc:subject>
	<dc:subject xml:lang="en-US">Behavior Obfuscation</dc:subject>
	<dc:subject xml:lang="en-US">Blockchain</dc:subject>
	<dc:subject xml:lang="en-US">Cloud Computing</dc:subject>
	<dc:subject xml:lang="en-US">Smart Contracts</dc:subject>
	<dc:subject xml:lang="en-US">Data Anonymization</dc:subject>
	<dc:subject xml:lang="en-US">Edge–Cloud Architecture</dc:subject>
	<dc:subject xml:lang="en-US">Secure Data Aggregation</dc:subject>
	<dc:description xml:lang="en-US">Rapidly growing Internet of Things (IoT) networks pose many fundamentally important privacy challenges, particularly when combined with transparent technologies such as the blockchain. Although blockchain provides distributed trust and auditability, its immutable logs can inadvertently leak user behavior. In this paper, we take on this problem by presenting a privacy-preserving approach for IoT systems, which is informed by the confluence of behavior obfuscation and differential privacy technology, run atop a hybrid blockchain-cloud infrastructure. The research result is a five-phase model which makes devices’ behaviors look like exactly-anonymous devices at the edge and is based on formal privacy guarantees by employing differential privacy in the cloud. To achieve this, we propose a framework that consists of light-weight obfuscation operators—timestamp perturbation, dummy event injection, and activity reordering—that, when synergistically used with the state-of-the-art, media-centric, differentially private solutions in the cloud, offer justifiable privacy against analytical and knowledge-based attacks. Cleaned–up summaries are tentatively submitted to blockchain in a safe way through smart contracts, facilitating traceable, tamper–evident logging without revealing raw behavioral information obtained from the data owner. Experimental results based on a Raspberry Pi-based IoT testbed and Ethereum-compatible blockchain show that the proposed system keeps low latency ( 2.8 s), over 400 events/min throughput, blockchain storage overhead and privacy leakage. Modular, auditable, and real-time-capable approach for secure data sharing in adversarial IoT environments (Applied to healthcare, smart homes, and industrial monitoring).</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Yogyakarta</dc:publisher>
	<dc:date>2025-11-07</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.umy.ac.id/index.php/jrc/article/view/27593</dc:identifier>
	<dc:identifier>10.18196/jrc.v6i6.27593</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Robotics and Control (JRC); Vol. 6 No. 6 (2025); 2613-2627</dc:source>
	<dc:source>2715-5072</dc:source>
	<dc:source>2715-5056</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.umy.ac.id/index.php/jrc/article/view/27593/12006</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Hussein Ahmed Ali,  Midhat Hussein Ibrahim Khalaf, Samider Abdulabbas Fadek, Huda Mohammed Alsayednoor, Abbas Jalal Kaishesh, Zainab Marid Alzamili, ‪Mahmood A. Al-Shareeda‬‏, Mohammed Amin Almaiah, Rami Shehab</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>