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A Secure Tracing Method in Fog Computing Network for the IoT Devices

Authors:

Abdulrahman Alamer,

Sultan Basudan,

Patrick C. K. HungAuthors Info & Claims

MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems

Pages 104 - 110

https://doi.org/10.1145/3415958.3433074

Published: 27 November 2020 Publication History

Abstract

This paper proposes a Secure and Privacy-preserving Tracing (SPT) mechanism in the Fog Computing (FC) network. The proposed SPT mechanism employs a Counting Bloom Filter (CBF) method as a tree framework (CBF-tree) to model a secure tracing system in the FC network. With the proposed SPT mechanism, the fog node can trace a particular Internet of Things (IoT) device in a secure manner, which means that the fog node can trace IoT devices in order to provide them with their requested services without revealing their private data such as the device's identities or locations. Analysis shows that the SPT mechanism is both efficient and resilient against tracing attacks. Simulation results are provided to show that the proposed mechanism is beneficial to the FC network.

References

[1]

[n.d.]. CAIDA: The cooperative association for Internet data analysis. In [Online].http://www.caida.org.

[2]

Mohammad Aazam, Marc St-Hilaire, Chung-Horng Lung, and Ioannis Lambadaris. 2016. PRE-Fog: IoT trace based probabilistic resource estimation at Fog. In 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 12--17.

[3]

Nabil Abubaker, Leonard Dervishi, and Erman Ayday. 2017. Privacy-preserving fog computing paradigm. In 2017 IEEE Conference on Communications and Network Security (CNS). IEEE, 502--509.

[4]

Orestis Akrivopoulos, Ioannis Chatzigiannakis, Christos Tselios, and Athanasios Antoniou. 2017. On the deployment of healthcare applications over fog computing infrastructure. In 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), Vol. 2. IEEE, 288--293.

[5]

Abdulrahman Alamer. 2018. A secure and privacy-preserving incentive framework for vehicular cloud. Ph.D. Dissertation. University of Ontario Institute of Technology (Canada).

[6]

Abdulrahman Alamer. 2020. An efficient group signcryption scheme supporting batch verification for securing transmitted data in the Internet of Things. Springer J Ambient Intell Human Comput https://doi.org/10.1007/s12652-020-02076-x (2020).

[7]

Abdulrahman Alamer. 2020. A secure anonymous tracing fog-assisted method for the Internet of Robotic Things. Library Hi Tech (2020).

[8]

Abdulrahman Alamer and Sultan Basudan. 2020. An efficient truthfulness privacy-preserving tendering framework for vehicular fog computing. Engineering Applications of Artificial Intelligence 91 (2020), 103583.

[9]

Abdulrahman Alamer, Sultan Basudan, and Xiaodong Lin. 2018. A Privacy-Preserving Incentive Framework for the Vehicular Cloud. In 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, 435--441.

[10]

Abdulrahman Alamer, Yong Deng, and Xiaodong Lin. 2017. A privacy-preserving and truthful tendering framework for vehicle cloud computing. In 2017 IEEE International Conference on Communications (ICC). IEEE, 1--7.

[11]

Abdulrahman Alamer, Yong Deng, and Xiaodong Lin. 2017. Secure and privacy-preserving task announcement in vehicular cloud. In 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 1--6.

[12]

Abdulrahman Alamer, Yong Deng, Guiyi Wei, and Xiaodong Lin. 2018. Collaborative security in vehicular cloud computing: a game theoretic view. IEEE Network 32, 3 (2018), 72--77.

[13]

Abdulrahman Alamer, Jianbing Ni, Xiaodong Lin, and Xuemin Shen. 2017. Location privacy-aware task recommendation for spatial crowdsourcing. In 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 1--6.

[14]

Abdullah Aljumah and Tariq Ahamed Ahanger. 2018. Fog computing and security issues: A review. In 2018 7th International Conference on Computers Communications and Control (ICCCC). IEEE, 237--239.

[15]

Hamza Baniata, Wesam Almobaideen, and Attila Kertesz. 2020. A Privacy Preserving Model for Fog-enabled MCC systems using 5G Connection. In 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC). IEEE, 223--230.

[16]

Sultan Basudan, Abdulrahman Alamer, Xiaodong Lin, and Karthik Sankaranarayanan. 2018. Efficient deduplicated reporting in fog-assisted vehicular crowd-sensing. In 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, 463--469.

[17]

Sultan Basudan, Xiaodong Lin, and Karthik Sankaranarayanan. 2017. An efficient compromised node revocation scheme in fog-assisted vehicular crowdsensing. In GLOBECOM 2017-2017 IEEE Global Communications Conference. IEEE, 1--6.

[18]

Andrei Broder and Michael Mitzenmacher. 2004. Network applications of bloom filters: A survey. Internet mathematics 1, 4 (2004), 485--509.

[19]

Ning Chen, Yu Chen, Yang You, Haibin Ling, Pengpeng Liang, and Roger Zimmermann. 2016. Dynamic urban surveillance video stream processing using fog computing. In 2016 IEEE second international conference on multimedia big data (BigMM). IEEE, 105--112.

[20]

Ken Christensen, Allen Roginsky, and Miguel Jimeno. 2010. A new analysis of the false positive rate of a bloom filter. Inform. Process. Lett. 110, 21 (2010), 944--949.

Digital Library

[21]

Emiliano De Cristofaro and Claudio Soriente. 2013. Extended capabilities for a privacy-enhanced participatory sensing infrastructure (PEPSI). IEEE Transactions on Information Forensics and Security 8, 12 (2013), 2021--2033.

Digital Library

[22]

Li Fan, Pei Cao, Jussara Almeida, and Andrei Z Broder. 2000. Summary cache: a scalable wide-area web cache sharing protocol. IEEE/ACM transactions on networking 8, 3 (2000), 281--293.

Digital Library

[23]

Shahabeddin Geravand and Mahmood Ahmadi. 2013. Bloom filter applications in network security: A state-of-the-art survey. Computer Networks 57, 18 (2013), 4047--4064.

Digital Library

[24]

Sunghyuck Hong and Kyungil Ko. 2017. MAC address based Sensor Network Authentication: Survey. In Proceedings of the International Conference on Security and Management (SAM). The Steering Committee of The World Congress in Computer Science, Computer âĂę, 18--21.

[25]

Cheng Huang, Rongxing Lu, Hui Zhu, Jun Shao, Abdulrahman Alamer, and Xiaodong Lin. 2016. EPPD: efficient and privacy-preserving proximity testing with differential privacy techniques. In 2016 IEEE International Conference on Communications (ICC). IEEE, 1--6.

[26]

Ketanpreet Kaur and Monika Sachdeva. 2020. Fog Computing in IOT: An Overview of New Opportunities. In Proceedings of ICETIT 2019. Springer, 59--68.

[27]

Saad Khan, Simon Parkinson, and Yongrui Qin. 2017. Fog computing security: a review of current applications and security solutions. Journal of Cloud Computing 6, 1 (2017), 19.

Digital Library

[28]

Qinglei Kong, Rongxing Lu, Hui Zhu, Abdulrahman Alamer, and Xiaodong Lin. 2016. A secure and privacy-preserving incentive framework for vehicular cloud on the road. In 2016 IEEE Global Communications Conference (GLOBECOM). IEEE, 1--6.

[29]

Praveen Kumar, Nabeel Zaidi, and Tanupriya Choudhury. 2016. Fog computing: Common security issues and proposed countermeasures. In 2016 International Conference System Modeling & Advancement in Research Trends (SMART). IEEE, 311--315.

[30]

Xujie Li, Zhennan Zang, Fei Shen, and Ying Sun. 2020. Task Offloading Scheme Based on Improved Contract Net Protocol and Beetle Antennae Search Algorithm in Fog Computing Networks. Mobile Networks and Applications (2020), 1--10.

[31]

Mithun Mukherjee, Rakesh Matam, Lei Shu, Leandros Maglaras, Mohamed Amine Ferrag, Nikumani Choudhury, and Vikas Kumar. 2017. Security and privacy in fog computing: Challenges. IEEE Access 5 (2017), 19293--19304.

[32]

Jianbing Ni, Aiqing Zhang, Xiaodong Lin, and Xuemin Sherman Shen. 2017. Security, privacy, and fairness in fog-based vehicular crowdsensing. IEEE Communications Magazine 55, 6 (2017), 146--152.

[33]

Simone Patonico, An Braeken, and Kris Steenhaut. 2019. Identity-based and anonymous key agreement protocol for fog computing resistant in the Canetti-Krawczyk security model. Wireless Networks (2019), 1--13.

[34]

Colton Powell, Christopher Desiniotis, and Behnam Dezfouli. 2020. The Fog Development Kit: A Platform for the Development and Management of Fog Systems. IEEE Internet of Things Journal (2020).

[35]

Christian Esteve Rothenberg, Petri Jokela, Pekka Nikander, Mikko Sarela, and Jukka Ylitalo. 2009. Self-routing denial-of-service resistant capabilities using inpacket Bloom filters. In 2009 European Conference on Computer Network Defense. IEEE, 46--51.

Digital Library

[36]

Ivan Stojmenovic and Sheng Wen. 2014. The fog computing paradigm: Scenarios and security issues. In 2014 federated conference on computer science and information systems. IEEE, 1--8.

[37]

Sasu Tarkoma, Christian Esteve Rothenberg, and Eemil Lagerspetz. 2011. Theory and practice of bloom filters for distributed systems. IEEE Communications Surveys & Tutorials 14, 1 (2011), 131--155.

[38]

Himani Tyagi and Rajendra Kumar. 2020. Cloud Computing for IoT. In Internet of Things (IoT). Springer, 25--41.

[39]

William Tichaona Vambe, Chii Chang, and Khulumani Sibanda. 2020. A Review of Quality of Service in Fog Computing for the Internet of Things. International Journal of Fog Computing (IJFC) 3, 1 (2020), 22--40.

Digital Library

[40]

Qixu Wang, Dajiang Chen, Ning Zhang, Zhe Ding, and Zhiguang Qin. 2017. PCP: A privacy-preserving content-based publish-subscribe scheme with differential privacy in fog computing. IEEE Access 5 (2017), 17962--17974.

[41]

Jiannan Wei, Xiaojie Wang, Nan Li, Guomin Yang, and Yi Mu. 2018. A privacy-preserving fog computing framework for vehicular crowdsensing networks. IEEE Access 6 (2018), 43776--43784.

[42]

Shanhe Yi, Zhengrui Qin, and Qun Li. 2015. Security and privacy issues of fog computing: A survey. In International conference on wireless algorithms, systems, and applications. Springer, 685--695.

[43]

Myung Keun Yoon, JinWoo Son, and Seon-Ho Shin. 2014. Bloom tree: A search tree based on bloom filters for multiple-set membership testing. In IEEE INFOCOM 2014-IEEE Conference on Computer Communications. IEEE, 1429--1437.

[44]

Jiang Zhu, Douglas S Chan, Mythili Suryanarayana Prabhu, Preethi Natarajan, Hao Hu, and Flavio Bonomi. 2013. Improving web sites performance using edge servers in fog computing architecture. In 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering. IEEE, 320--323.

Digital Library

Cited By

Alamer ABasudan SHung P(2023)A privacy-preserving scheme to support the detection of multiple similar request-real-time services in IoT application systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119005214:COnline publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119005
Dinh NKim Y(2022)An Efficient Distributed Content Store-Based Caching Policy for Information-Centric NetworkingSensors10.3390/s2204157722:4(1577)Online publication date: 17-Feb-2022
https://doi.org/10.3390/s22041577
Alamer ABasudan S(2022)Security and privacy of network transmitted system in the Internet of Robotic ThingsThe Journal of Supercomputing10.1007/s11227-022-04612-278:16(18361-18378)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s11227-022-04612-2
Show More Cited By

Index Terms

A Secure Tracing Method in Fog Computing Network for the IoT Devices
1. Networks
  1. Network properties
    1. Network privacy and anonymity
2. Security and privacy
  1. Security services
    1. Pseudonymity, anonymity and untraceability

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cover image ACM Other conferences

MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems

November 2020

170 pages

ISBN:9781450381154

DOI:10.1145/3415958

General Chairs:
Richard Chbeir
University Pau & Pays de l'Adour, France
,
Yannis Manolopoulos
Open University of Cyprus, Cyprus
,
Ernesto Damiani
Khalifa University of Science and Technology, UAE
,
Djamal Benslimane
Lyon 1 University, France
,
Program Chairs:
Ladjel Bellatreche
LIAS/ISAE-ENSMA, France
,
Tadeusz Morzy
Poznan University of Technology, Poland

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 27 November 2020

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MEDES '20

MEDES '20: 12th International Conference on Management of Digital EcoSystems

November 2 - 4, 2020

Virtual Event, United Arab Emirates

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MEDES '20 Paper Acceptance Rate 19 of 27 submissions, 70%;

Overall Acceptance Rate 267 of 682 submissions, 39%

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Cited By

Alamer ABasudan SHung P(2023)A privacy-preserving scheme to support the detection of multiple similar request-real-time services in IoT application systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119005214:COnline publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119005
Dinh NKim Y(2022)An Efficient Distributed Content Store-Based Caching Policy for Information-Centric NetworkingSensors10.3390/s2204157722:4(1577)Online publication date: 17-Feb-2022
https://doi.org/10.3390/s22041577
Alamer ABasudan S(2022)Security and privacy of network transmitted system in the Internet of Robotic ThingsThe Journal of Supercomputing10.1007/s11227-022-04612-278:16(18361-18378)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s11227-022-04612-2
Alamer ABasudan S(2022)A Security and Privacy-Preserving Accessing Data Protocol in Vehicular Crowdsensing Using BlockchainProceedings of Seventh International Congress on Information and Communication Technology10.1007/978-981-19-1610-6_27(315-327)Online publication date: 27-Jul-2022
https://doi.org/10.1007/978-981-19-1610-6_27
Alamer A(2022)A Proxy Re-signcryption Scheme with Delegation PropertyProceedings of International Conference on Computing and Communication Networks10.1007/978-981-19-0604-6_22(243-259)Online publication date: 9-Jul-2022
https://doi.org/10.1007/978-981-19-0604-6_22
Dinh NKim Y(2021)An Efficient Content Store-Based Forwarding Scheme for Internet of ThingsSensors10.3390/s2122760721:22(7607)Online publication date: 16-Nov-2021
https://doi.org/10.3390/s21227607
Alamer A(2021)Security and Privacy-Awareness in a Software-Defined Fog Computing Network for the Internet of ThingsOptical Switching and Networking10.1016/j.osn.2021.100616(100616)Online publication date: Mar-2021
https://doi.org/10.1016/j.osn.2021.100616

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