survey

A Survey on IoT Profiling, Fingerprinting, and Identification

Authors:

Sajjad Dadkhah,

Farzaneh Shoeleh,

Hassan Mahdikhani,

Heather Molyneaux,

Ali A. GhorbaniAuthors Info & Claims

ACM Transactions on Internet of Things, Volume 3, Issue 4

Article No.: 26, Pages 1 - 39

https://doi.org/10.1145/3539736

Published: 06 September 2022 Publication History

Abstract

The proliferation of heterogeneous Internet of things (IoT) devices connected to the Internet produces several operational and security challenges, such as monitoring, detecting, and recognizing millions of interconnected IoT devices. Network and system administrators must correctly identify which devices are functional, need security updates, or are vulnerable to specific attacks. IoT profiling is an emerging technique to identify and validate the connected devices’ specific behaviour and isolate the suspected and vulnerable devices within the network for further monitoring. This article provides a comprehensive review of various IoT device profiling methods and provides a clear taxonomy for IoT profiling techniques based on different security perspectives. We first investigate several current IoT device profiling techniques and their applications. Next, we analyzed various IoT device vulnerabilities, outlined multiple features, and provided detailed information to implement profiling algorithms’ risk assessment/mitigation stage. By reviewing approaches for profiling IoT devices, we identify various state-of-the-art methods that organizations of different domains can implement to satisfy profiling needs. Furthermore, this article also discusses several machine learning and deep learning algorithms utilized for IoT device profiling. Finally, we discuss challenges and future research possibilities in this domain.

References

[1]

[n.d.]. APIs, sdks, Sandbox, and Community for Cisco Developers. Retrieved from https://developer.cisco.com/docs/mud/#!what-is-mud/what-is-mud.

[2]

[n.d.]. Common Vulnerability Scoring System Calculator. Retrieved January 30, 2021 from https://nvd.nist.gov/vuln-metrics/cvss/v3-calculator.

[3]

[n.d.]. TL-WN722N 150Mbps High Gain Wireless USB Adapter. Retrieved January 30, 2021 from https://www.tp-link.com/ca/home-networking/high-gain-adapter/tl-wn722n/.

[4]

A. R. Abdallah and X. S. Shen. 2014. Lightweight lattice-based homomorphic privacy-preserving aggregation scheme for home area networks. In Proceedings of the 6th International Conference on Wireless Communications and Signal Processing (WCSP’14). 1–6.

[5]

Abbas Acar, Hossein Fereidooni, Tigist Abera, Amit Kumar Sikder, Markus Miettinen, Hidayet Aksu, Mauro Conti, Ahmad-Reza Sadeghi, and Selcuk Uluagac. 2020. Peek-a-Boo: I see your smart home activities, even encrypted! In Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks. 207–218.

Digital Library

[6]

Noura Al Nuaimi, Asma Alshamsi, Nader Mohamed, and Jameela Al-Jaroodi. 2015. e-Health cloud implementation issues and efforts. In Proceedings of the 5th International Conference on Industrial Engineering and Operations Management (IEOM’15).

[7]

Amani Al-Shawabka, Philip Pietraski, Sudhir B. Pattar, Francesco Restuccia, and Tommaso Melodia. 2021. DeepLoRa: Fingerprinting LoRa devices at scale through deep learning and data augmentation. In Proceedings of the 22nd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing. 251–260.

[8]

Amir H. Alavi, Pengcheng Jiao, William G. Buttlar, and Nizar Lajnef. 2018. Internet of things-enabled smart cities: State-of-the-art and future trends. Measurement 129 (2018), 589–606.

[9]

A. AlHammadi, A. AlZaabi, B. AlMarzooqi, S. AlNeyadi, Z. AlHashmi, and M. Shatnawi. 2019. Survey of IoT-based smart home approaches. In Proceedings of the Advances in Science and Engineering Technology International Conferences (ASET’19). 1–6.

[10]

W. Ali, G. Dustgeer, M. Awais, and M. A. Shah. 2017. IoT based smart home: Security challenges, security requirements and solutions. In Proceedings of the 23rd International Conference on Automation and Computing (ICAC’17). 1–6.

[11]

F. Alsubaei, A. Abuhussein, and S. Shiva. 2017. Security and privacy in the internet of medical things: Taxonomy and risk assessment. In Proceedings of the IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops’17). 112–120.

[12]

Nesrine Ammar, Ludovic Noirie, and Sébastien Tixeuil. 2020. Autonomous identification of IoT device types based on a supervised classification. In Proceedings of the IEEE International Conference on Communications (ICC’20). IEEE, 1–6.

[13]

I. Andrea, C. Chrysostomou, and G. Hadjichristofi. 2015. Internet of Things: Security vulnerabilities and challenges. In Proceedings of the IEEE Symposium on Computers and Communication (ISCC’15). 180–187.

[14]

Noah Apthorpe, Dillon Reisman, Srikanth Sundaresan, Arvind Narayanan, and Nick Feamster. 2017. Spying on the smart home: Privacy attacks and defenses on encrypted IoT traffic. arXiv preprint arXiv:1708.05044.

[15]

Sabir Hussain Awan, Sheeraz Ahmed, Nadeem Safwan, Zeeshan Najam, M. Zaheer Hashim, and Tayybah Safdar. 2019. Role of Internet of Things (IoT) with blockchain technology for the development of smart farming. Journal of Mechanics of Continua and Mathematical Sciences 14, 5 (2019), 170–188.

[16]

Lei Bai, Lina Yao, Salil S. Kanhere, Xianzhi Wang, and Zheng Yang. 2018. Automatic device classification from network traffic streams of Internet of Things. In Proceedings of the IEEE 43rd Conference on Local Computer Networks (LCN’18), 1–9.

[17]

S. B. Baker, W. Xiang, and I. Atkinson. 2017. Internet of Things for smart healthcare: Technologies, challenges, and opportunities. IEEE Access 5 (2017), 26521–26544.

[18]

Luís Barreto and António Amaral. 2018. Smart farming: Cyber security challenges. In Proceedings of the International Conference on Intelligent Systems (IS’18). IEEE, 870–876.

[19]

A. Bartoli, J. Hernández-Serrano, M. Soriano, M. Dohler, A. Kountouris, and D. Barthel. 2011. Security and privacy in your smart city. In Proceedings of the Barcelona Smart Cities Congress, Vol. 292. 1–6.

[20]

M. J. Bogaardt, K. J. Poppe, V. Viool, and E. van Zuidam. 2016. Cybersecurity in the Agrifood Sector. Technical Report. Capgemini Consulting.

[21]

Jens-Matthias Bohli, P. Langendorfer, and Antonio F. Skarmeta. 2013. Security and privacy challenge in data aggregation for the iot in smart cities. In Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, 225–244.

[22]

Julie Bort. 2014. Refrigerator Hacked: Here’s The Biggest Problem Facing The Internet Of Things. Retrieved January 30, 2021 from https://www.businessinsider.com.au/hackers-use-a-refridgerator-to-attack-businesses-2014-1.

[23]

Miloš Brajović, Stefan Vujović, and Slobodan Đukanović. 2015. An overview of smart irrigation software. In Proceedings of the 4th Mediterranean Conference on Embedded Computing (MECO’15). IEEE, 353–356.

[24]

Leo Breiman. 2001. Random forests. Mach. Learn. 45, 1 (October 2001), 5–32.

Digital Library

[25]

Bezawada Bruhadeshwar, Maalvika Bachani, Jordan Peterson, Hossein Shirazi, Indrakshi Ray, and Indrajit Ray. 2018. IoTSense: Behavioral fingerprinting of IoT devices. arXiv: 1804.03852. Retrieved from https://arxiv.org/abs/1804.03852.

[26]

A. Bytes, S. Adepu, and J. Zhou. 2019. Towards semantic sensitive feature profiling of IoT devices. IEEE IoT J. 6, 5 (October 2019), 8056–8064.

[27]

Z. Berkay Celik, Robert J. Walls, Patrick McDaniel, and Ananthram Swami. 2015. Malware traffic detection using tamper resistant features. In Proceedings of the IEEE Military Communications Conference (MILCOM’15). IEEE, 330–335.

[28]

B. Charyyev and M. H. Gunes. 2020. Locality-sensitive IoT network traffic fingerprinting for device identification. IEEE IoT J. (2020), 1–1.

[29]

Hongmei Chi, Stephen Welch, Eugene Vasserman, and Ezhil Kalaimannan. 2017. A framework of cybersecurity approaches in precision agriculture. In Proceedings of the 5th International Conference on Management Leadership and Governance (ICMLG’17). Acad. Conf. Publ. Int., Reading, UK, 90–95.

[30]

Cédric Clastres. 2011. Smart grids: Another step towards competition, energy security and climate change objectives. Energy Pol. 39, 9 (2011), 5399–5408.

[31]

R. Dagar, S. Som, and S. K. Khatri. 2018. Smart farming—IoT in agriculture. In Proceedings of the International Conference on Inventive Research in Computing Applications (ICIRCA’18). 1052–1056.

[32]

P. Datta and B. Sharma. 2017. A survey on IoT architectures, protocols, security and smart city based applications. In Proceedings of the 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT’17). 1–5.

[33]

B. D. Davis, J. C. Mason, and M. Anwar. 2020. Vulnerability studies and security postures of IoT devices: A smart home case study. IEEE IoT J. (2020), 1–1.

[34]

Ruizhong Du, Jingze Wang, and Shuang Li. 2022. A lightweight flow feature-based IoT device identification schemeSecurity and Communication Networks.

[35]

Adel S. Elmaghraby and Michael M. Losavio. 2014. Cyber security challenges in Smart Cities: Safety, security and privacy. J. Adv. Res. 5, 4 (2014), 491–497.

[36]

Linna Fan, Shize Zhang, Yichao Wu, Zhiliang Wang, Chenxin Duan, Jia Li, and Jiahai Yang. 2020. An IoT device identification method based on semi-supervised learning. In Proceedings of the 16th International Conference on Network and Service Management (CNSM’20). IEEE, 1–7.

[37]

M. S. Farooq, S. Riaz, A. Abid, K. Abid, and M. A. Naeem. 2019. A survey on the role of IoT in agriculture for the implementation of smart farming. IEEE Access 7 (2019), 156237–156271.

[38]

P. P. Gaikwad, J. P. Gabhane, and S. S. Golait. 2015. A survey based on smart homes system using Internet-of-Things. In Proceedings of the International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC’15). 0330–0335.

[39]

Gartner. 2015. Smart Homes: The Next CPG Battleground? Retrieved January 30 from https://blogs.gartner.com/don-scheibenreif/2015/11/24/smart-homes-the-next-cpg-battleground/.

[40]

D. Geneiatakis, I. Kounelis, R. Neisse, I. Nai-Fovino, G. Steri, and G. Baldini. 2017. Security and privacy issues for an IoT based smart home. In Proceedings of the 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO’17). 1292–1297.

[41]

Dimitris Geneiatakis, Ioannis Kounelis, Ricardo Neisse, Igor Nai Fovino, Gary Steri, and Gianmarco Baldini. 2017. Security and privacy issues for an IoT based smart home.

[42]

Ammar Gharaibeh, Mohammad A. Salahuddin, Sayed Jahed Hussini, Abdallah Khreishah, Issa Khalil, Mohsen Guizani, and Ala Al-Fuqaha. 2017. Smart cities: A survey on data management, security, and enabling technologies. IEEE Commun. Surv. Tutor. 19, 4 (2017), 2456–2501.

[43]

Sanjay Goel. 2015. Anonymity vs. security: The right balance for the smart grid. Commun. Assoc. Inf. Syst. 36, 1 (2015), 2.

[44]

GSMA. 2018. New GSMA Study: Operators Must Look Beyond Connectivity to Increase Share of $1.1 Trillion IoT Revenue Opportunity. Retrieved January 30, 2021 from https://www.gsma.com/newsroom/press-release/new-gsma-study-operators-must-look-beyond-connectivity-to-increase-share/.

[45]

The Guardian. 2016. The Guardian, Why the Internet of Things Is the New Magic Ingredient for Cyber Criminals. Retrieved January 30, 2021 fromhttp://engineering.purdue.edu/mark/puthesis.

[46]

M. Gupta, M. Abdelsalam, S. Khorsandroo, and S. Mittal. 2020. Security and privacy in smart farming: Challenges and opportunities. IEEE Access 8 (2020), 34564–34584.

[47]

Rajesh Gupta, Sudeep Tanwar, Sudhanshu Tyagi, and Neeraj Kumar. 2019. Tactile-internet-based telesurgery system for healthcare 4.0: An architecture, research challenges, and future directions. IEEE Network 33 (2019), 22–29.

Digital Library

[48]

Hamed HaddadPajouh, Ali Dehghantanha, Reza M Parizi, Mohammed Aledhari, and Hadis Karimipour. 2021. A survey on internet of things security: Requirements, challenges, and solutions. Internet of Things 14 (2021), 100129.

[49]

S. A. Hamad, W. E. Zhang, Q. Z. Sheng, and S. Nepal. 2019. IoT device identification via network-flow based fingerprinting and learning. In Proceedings of the 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering (TrustCom/BigDataSE’19). 103–111.

[50]

Jigna J. Hathaliya and Sudeep Tanwar. 2020. An exhaustive survey on security and privacy issues in Healthcare 4.0. Comput. Commun. 153 (2020), 311–335.

Digital Library

[51]

Lars Huning, Jan Bauer, and Nils Aschenbruck. 2017. A privacy preserving mobile crowdsensing architecture for a smart farming application. In Proceedings of the 1st ACM Workshop on Mobile Crowdsensing Systems and Applications. 62–67.

[52]

P. E. Idoga, M. Agoyi, E. Y. Coker-Farrell, and O. L. Ekeoma. 2016. Review of security issues in e-Healthcare and solutions. In Proceedings of the IEEE International Conference on Smart Cities: Imporving Quatlity of LIfe Using ICT&IoT and AI (HONET-ICT’16). 118–121.

[53]

Sidra Ijaz, Munam Ali Shah, Abid Khan, and Mansoor Ahmed. 2016. Smart cities: A survey on security concerns. Int. J. Adv. Comput. Sci. Appl. 7, 2 (2016), 612–625.

[54]

Andreas Jacobsson, Martin Boldt, and Bengt Carlsson. 2016. A risk analysis of a smart home automation system. Fut. Gener. Comput. Syst. 56 (2016), 719–733.

Digital Library

[55]

A. Jacobsson and P. Davidsson. 2015. Towards a model of privacy and security for smart homes. In Proceedings of the IEEE 2nd World Forum on Internet of Things (WF-IoT’15). 727–732.

[56]

Hossein Jafari, Oluwaseyi Omotere, Damilola Adesina, Hsiang-Huang Wu, and Lijun Qian. 2018. Iot devices fingerprinting using deep learning. In Proceedings of the IEEE Military Communications Conference (MILCOM’18). IEEE, 1–9.

[57]

Molly M. Jahn, W. L. Oemichen, G. F. Treverton, et al. 2019. Cyber Risk and Security Implications in Smart Agriculture and Food Systems. Retrieved November 14, 2019. https://jahnresearchgroup.webhosting.cals.wisc.edu/wp-content/uploads/sites/223/2019/01/Agricultural-Cyber-Risk-and-Security.pdf.

[58]

T. Kailath. 1967. The divergence and bhattacharyya distance measures in signal selection. IEEE Trans. Commun. Technol. 15, 1 (1967), 52–60.

[59]

Kai Kang, Zhi bo Pang, and Cong Wang. 2013. Security and privacy mechanism for health internet of things. J. Chin. Univ. Posts Telecommun. 20 (2013), 64–68.

[60]

Ayush Kapoor, Suchetha I. Bhat, Sushila Shidnal, and Akshay Mehra. 2016. Implementation of IoT (Internet of Things) and image processing in smart agriculture. In Proceedings of the International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS’16). IEEE, 21–26.

[61]

Baltej Kaur, Danish Inamdar, Vishal Raut, Akash Patil, and Nayan Patil. 2016. A survey on smart drip irrigation system|. Int. Res. J. Eng. Technol. 3, 02 (2016).

[62]

V. Keerthi and G. N. Kodandaramaiah. 2015. Cloud IoT based greenhouse monitoring system. Int. J. Eng. Res. Appl. 5, 10 (2015), 35–41.

[63]

C. Kempenaar, C. Lokhorst, E. J. B. Bleumer, R. F. Veerkamp, Th Been, F. K. van Evert, M. J. Boogaardt, L. Ge, J. Wolfert, C. N. Verdouw, et al. 2016. Big Data Analysis for Smart Farming: Results of TO2 Project in Theme Food Security. Technical Report. Wageningen University & Research.

[64]

L. U. Khan, I. Yaqoob, N. H. Tran, S. M. A. Kazmi, T. N. Dang, and C. S. Hong. 2020. Edge computing enabled smart cities: A comprehensive survey. IEEE IoT J. (2020), 1–1.

[65]

N. Komninos, E. Philippou, and A. Pitsillides. 2014. Survey in smart grid and smart home security: Issues, challenges and countermeasures. IEEE Commun. Surv. Tutor. 16, 4 (2014), 1933–1954.

[66]

Jaidip Kotak and Yuval Elovici. 2020. IoT device identification using deep learning. arXiv:2002.11686. Retrieved from https://arxiv.org/abs/2002.11686.

[67]

M. Koutli, N. Theologou, A. Tryferidis, D. Tzovaras, A. Kagkini, D. Zandes, K. Karkaletsis, K. Kaggelides, J. Almela Miralles, V. Oravec, and S. Vanya. 2019. Secure IoT e-Health applications using VICINITY framework and GDPR guidelines. In Proceedings of the 15th International Conference on Distributed Computing in Sensor Systems (DCOSS’19). 263–270.

[68]

Denis Kozlov, Jari Veijalainen, and Yasir Ali. 2012. Security and privacy threats in IoT architectures general. In Proceedings of the 7th International Conference on Body Area Networks (BodyNets’12).

[69]

J. Sathish Kumar and Dhiren Patel. 2014. A survey on Internet of Things: Security and privacy issues. Int. J. Comput. Appl. 90 (2 2014).

[70]

Aparna Kumari, Sudeep Tanwar, Sudhanshu Tyagi, Neeraj Kumar, Michele Maasberg, and Kim-Kwang Raymond Choo. 2018. Multimedia big data computing and Internet of Things applications: A taxonomy and process model. J. Netw. Comput. Appl. 124 (2018), 169–195.

[71]

Saba Latif, Hamra Afzaal, and Nazir Ahmad Zafar. 2018. Modelling of graph-based smart parking system using internet of things. In Proceedings of the International Conference on Frontiers of Information Technology (FIT’18). IEEE, 7–12.

[72]

S. Latif and N. A. Zafar. 2017. A survey of security and privacy issues in IoT for smart cities. In Proceeding of the 5th International Conference on Aerospace Science Engineering (ICASE’17). 1–5.

[73]

Changmin Lee, Luca Zappaterra, Kwanghee Choi, and Hyeong-Ah Choi. 2014. Securing smart home: Technologies, security challenges, and security requirements. 67–72.

[74]

Seokcheol Lee, Jongwan Kim, and Taeshik Shon. 2016. User privacy-enhanced security architecture for home area network of smartgrid. Multimedia Tools Appl. 75, 20 (October 2016), 12749–12764.

Digital Library

[75]

T. Li, J. Ren, and X. Tang. 2012. Secure wireless monitoring and control systems for smart grid and smart home. IEEE Wireless Commun. 19, 3 (2012), 66–73.

[76]

Z. Li, S. Lu, S. Myagmar, and Y. Zhou. 2006. CP-Miner: Finding copy-paste and related bugs in large-scale software code. IEEE Trans. Softw. Eng. 32, 3 (2006), 176–192.

Digital Library

[77]

Chiehyeon Lim, Kwang-Jae Kim, and Paul Maglio. 2018. Smart cities with big data: Reference models, challenges, and considerations. Cities 82 (05 2018).

[78]

Jun Lin, Zhiqi Shen, Anting Zhang, and Yueting Chai. 2018. Blockchain and IoT based Food Traceability System. Int. J. Inf. Technol. 24, 1 (2018), 1–16.

[79]

Jie Lin, Wei Yu, Nan Zhang, Xinyu Yang, Hanlin Zhang, and Wei Zhao. 2017. A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications. IEEE IoT J. 4, 5 (2017), 1125–1142.

[80]

Amy Poh Ai Ling and Mukaidono Masao. 2011. Selection of model in developing information security criteria on smart grid security system. In Proceedings of the IEEE 9th International Symposium on Parallel and Distributed Processing with Applications Workshops. IEEE, 91–98.

[81]

Zhao Liqiang, Yin Shouyi, Liu Leibo, Zhang Zhen, and Wei Shaojun. 2011. A crop monitoring system based on wireless sensor network. Proc. Environ. Sci. 11 (2011), 558–565.

[82]

Manuel Lopez-Martin, Belen Carro, Antonio Sanchez-Esguevillas, and Jaime Lloret. 2017. Network traffic classifier with convolutional and recurrent neural networks for Internet of Things. IEEE Access 5 (2017), 18042–18050.

[83]

Gilad David Maayan. 2020. The IoT Rundown For 2020: Stats, Risks, and Solutions. Retrieved January 30, 2021 from https://securitytoday.com/articles/2020/01/13/the-iot-rundown-for-2020.aspx.

[84]

Gilad David Maayan. 2020. Twelve Highlights from Our 2020 Research. Retrieved January 30, 2021 from https://www.mckinsey.com/mgi/overview.

[85]

R. Mahmoud, T. Yousuf, F. Aloul, and I. Zualkernan. 2015. Internet of things (IoT) security: Current status, challenges and prospective measures. In Proceedings of the 10th International Conference for Internet Technology and Secured Transactions (ICITST’15). 336–341.

[86]

T. Mantoro, M. A. Ayu, and S. M. binti Mahmod. 2014. Securing the authentication and message integrity for Smart Home using smart phone. In Proceedings of the International Conference on Multimedia Computing and Systems (ICMCS’14). 985–989.

[87]

Window Marc. 2019. Security in Precision Agriculture: Vulnerabilities and Risks of Agricultural Systems.

[88]

Samuel Marchal, Markus Miettinen, Thien Duc Nguyen, Ahmad-Reza Sadeghi, and N. Asokan. 2019. Audi: Toward autonomous iot device-type identification using periodic communication. IEEE J. Select. Areas Commun. 37, 6 (2019), 1402–1412.

[89]

Antoni Martínez-Ballesté, Pablo A. Pérez-Martínez, and Agusti Solanas. 2013. The pursuit of citizens’ privacy: A privacy-aware smart city is possible. IEEE Commun. Mag. 51, 6 (2013), 136–141.

[90]

Noman Mazhar, Rosli Salleh, Muhammad Zeeshan, and M. Muzaffar Hameed. 2021. Role of device identification and manufacturer usage description in IoT security: A survey. IEEE Access 9 (2021), 41757–41786.

[91]

Yair Meidan, Michael Bohadana, Asaf Shabtai, Juan Guarnizo, Martin Ochoa, Nils Ole Tippenhauer, and Yuval Elovici. 2017. ProfilIoT: A machine learning approach for IoT device identification based on network traffic analysis.

Digital Library

[92]

M. S. Mekala and P. Viswanathan. 2017. A survey: Smart agriculture IoT with cloud computing. In Proceedings of the International Conference on Microelectronic Devices, Circuits and Systems (ICMDCS’17). 1–7.

[93]

Andrew Meola. 2020. How IoT are Creating a More a More Efficient Precision Agriculture Industry. Retrieved January 30, 2021 from https://www.businessinsider.com/smart-farming-iot-agriculture.

[94]

Microchip. [n.d.]. The Guardian, Why the Internet of Things Is the New Magic Ingredient for Cyber Criminals. Retrieved January 30, 2021 from https://www.microchip.com/.

[95]

M. Miettinen, S. Marchal, I. Hafeez, N. Asokan, A. Sadeghi, and S. Tarkoma. 2017. IoT SENTINEL: Automated device-type identification for security enforcement in IoT. In Proceedings of the IEEE 37th International Conference on Distributed Computing Systems (ICDCS’17). 2177–2184.

[96]

Dragos Mocrii, Yuxiang Chen, and Petr Musilek. 2018. IoT-based smart homes: A review of system architecture, software, communications, privacy and security. Internet of Things 1–2 (2018), 81–98.

[97]

Fiona Edwards Murphy, Michele Magno, Padraig Whelan, and Emanuel Popo Vici. 2015. b+ WSN: Smart beehive for agriculture, environmental, and honey bee health monitoring—Preliminary results and analysis. In Proceedings of the IEEE Sensors Applications Symposium (SAS’15). IEEE, 1–6.

[98]

Ammar Awad Mutlag, Mohd Khanapi Abd Ghani, Net al Arunkumar, Mazin Abed Mohammed, and Othman Mohd. 2019. Enabling technologies for fog computing in healthcare IoT systems. Fut. Gener. Comput. Syst. 90 (2019), 62–78.

[99]

Christelle Nader and Elias Bou-Harb. 2021. Revisiting IoT fingerprinting behind a NAT. In Proceedings of the IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom’21). IEEE, 1745–1752.

[100]

Milind Naphade, Guruduth Banavar, Colin Harrison, Jurij Paraszczak, and Robert Morris. 2011. Smarter cities and their innovation challenges. Computer 44, 6 (2011), 32–39.

Digital Library

[101]

T. D. Nguyen, S. Marchal, M. Miettinen, H. Fereidooni, N. Asokan, and A. Sadeghi. 2019. DÏoT: A federated self-learning anomaly detection system for IoT. In Proceedings of the IEEE 39th International Conference on Distributed Computing Systems (ICDCS’19). 756–767.

[102]

Sukhvir Notra, Muhammad Siddiqi, Hassan Habibi Gharakheili, Vijay Sivaraman, and Roksana Boreli. 2014. An experimental study of security and privacy risks with emerging household appliances. In Proceedings of the IEEE Conference on Communications and Network Security, 79–84.

[103]

I. Olaronke and O. Oluwaseun. 2016. Big data in healthcare: Prospects, challenges and resolutions. In Proceedings of the Future Technologies Conference (FTC’16). 1152–1157.

[104]

openwrt. [n.d.]. Welcome to the OpenWrt Project. Retrieved January 30, 2021 from https://openwrt.org/.

[105]

Michael Ossmann. [n.d.]. Project Ubertooth. Retrieved January 30, 2021 from https://github.com/greatscottgadgets/ubertooth.

[106]

R. Pankomera and D. van Greunen. 2016. Privacy and security issues for a patient-centric approach in public healthcare in a resource constrained setting. In Proceedings of the IST-Africa Week Conference. 1–10.

[107]

Nisha Panwar, Shantanu Sharma, Sharad Mehrotra, Lukasz Krzywiecki, and Nalini Venkatasubramanian. 2019. Smart home survey on security and privacy. arXiv:1904.05476. Retrieved from http://arxiv.org/abs/1904.05476.

[108]

Akash Suresh Patil, Bayu Adhi Tama, Youngho Park, and Kyung-Hyune Rhee. 2017. A framework for blockchain based secure smart green house farming. In Advances in Computer Science and Ubiquitous Computing. Springer, 1162–1167.

[109]

R. Priya, S. Sivasankaran, P. Ravisasthiri, and S. Sivachandiran. 2017. A survey on security attacks in electronic healthcare systems. In Proceedings of the International Conference on Communication and Signal Processing (ICCSP’17). 0691–0694.

[110]

P. Rajalakshmi and S. Devi Mahalakshmi. 2016. IOT based crop-field monitoring and irrigation automation. In Proceedings of the 10th International Conference on Intelligent Systems and Control (ISCO’16). IEEE, 1–6.

[111]

Jingjing Ren, Daniel Dubois, David Choffnes, Anna Mandalari, Roman Kolcun, and Hamed Haddadi. 2019. Information exposure from consumer IoT devices: A multidimensional, network-informed measurement approach. In Proceedings of the Internet Measurement Conference (IMC’19), 267–279.

Digital Library

[112]

Grandview Research. [n.d.]. Retrieved January 30, 2021 from https://www.grandviewresearch.com/.

[113]

Jonathan Roux, Eric Alata, Guillaume Auriol, Vincent Nicomette, and Mohamed Kaâniche. 2017. Toward an intrusion detection approach for IoT based on radio communications profiling. In Proceedings of the 13th European Dependable Computing Conference (EDCC’17). IEEE, 147–150.

[114]

Ola Salman, Imad H. Elhajj, Ali Chehab, and Ayman Kayssi. 2019. A machine learning based framework for IoT device identification and abnormal traffic detection. Trans. Emerg. Telecommun. Technol. (2019), e3743.

[115]

Mourjo Sen, Anuvabh Dutt, Shalabh Agarwal, and Asoke Nath. 2013. Issues of privacy and security in the role of software in smart cities. In Proceedings of the International Conference on Communication Systems and Network Technologies. IEEE, 518–523.

[116]

Laxmi S. Shabadi and Hemavati B. Biradar. 2008. Design and implementation of IOT based smart security and monitoring for connected smart farming. Int. J. Comput. Appl. 975 (2008), 8887.

[117]

Mustafizur Rahman Shahid, Gregory Blanc, Zonghua Zhang, and Hervé Debar. 2018. IoT devices recognition through network traffic analysis.

[118]

Yaman Sharaf-Dabbagh and Walid Saad. 2018. Authentication of everything in the Internet of Things: Learning and environmental effects. arXiv:1805.00969. Retrieved from http://arxiv.org/abs/1805.00969.

[119]

N. M. Shrestha, A. Alsadoon, P. W. C. Prasad, L. Hourany, and A. Elchouemi. 2016. Enhanced e-health framework for security and privacy in healthcare system. In Proceedings of the 6th International Conference on Digital Information Processing and Communications (ICDIPC’16). 75–79.

[120]

Sandra Siby, Rajib Maiti, and Nils Ole Tippenhauer. 2017. IoTScanner: Detecting and classifying privacy threats in IoT neighborhoods. arXiv preprint arXiv:1701.05007.

[121]

S. Sicari, A. Rizzardi, L. A. Grieco, and A. Coen-Porisini. 2015. Security, privacy and trust in Internet of Things: The road ahead. Comput. Netw. 76 (2015), 146–164.

Digital Library

[122]

Bhagya Silva, Murad Khan, and Kijun Han. 2018. Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sust. Cit. Soc. 38 (02 2018).

[123]

Arunan Sivanathan, Hassan Habibi Gharakheili, Franco Loi, Adam Radford, Chamith Wijenayake, Arun Vishwanath, and Vijay Sivaraman. 2018. Classifying IoT devices in smart environments using network traffic characteristics. IEEE Trans. Mobile Comput. PP (8 2018), 1–1.

[124]

A. Sivanathan, D. Sherratt, H. H. Gharakheili, A. Radford, C. Wijenayake, A. Vishwanath, and V. Sivaraman. 2017. Characterizing and classifying IoT traffic in smart cities and campuses. In Proceedings of the IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS’17). 559–564.

[125]

V. Sivaraman, H. H. Gharakheili, A. Vishwanath, R. Boreli, and O. Mehani. 2015. Network-level security and privacy control for smart-home IoT devices. In Proceedings of the IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob’15). 163–167.

[126]

S. Srisruthi, N. Swarna, G. M. Susmitha Ros, and Edna Elizabeth. 2016. Sustainable agriculture using eco-friendly and energy efficient sensor technology. In Proceedings of the IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT’16). IEEE, 1442–1446.

[127]

A. Strielkina, O. Illiashenko, M. Zhydenko, and D. Uzun. 2018. Cybersecurity of healthcare IoT-based systems: Regulation and case-oriented assessment. In Proceedings of the IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT’18). 67–73.

[128]

George Suciu, Alexandru Vulpe, Simona Halunga, Octavian Fratu, Gyorgy Todoran, and Victor Suciu. 2013. Smart cities built on resilient cloud computing and secure internet of things. In Proceedings of the 19th International Conference on Control Systems and Computer Science. IEEE, 513–518.

[129]

D. Sun, J. Huai, J. Sun, J. Zhang, and Z. Feng. 2008. A new design of wearable token system for mobile device security. IEEE Trans. Cons. Electr. 54, 4 (2008), 1784–1789.

Digital Library

[130]

Guanglu Sun, Lili Liang, Teng Chen, Feng Xiao, and Fei Lang. 2018. Network traffic classification based on transfer learning. Comput. Electr. Eng. 69 (2018), 920–927.

[131]

V. Thangavelu, D. M. Divakaran, R. Sairam, S. S. Bhunia, and M. Gurusamy. 2019. DEFT: A distributed IoT fingerprinting technique. IEEE IoT J. 6, 1 (2019), 940–952.

[132]

Jay Thom, Nathan Thom, Shamik Sengupta, and Emily Hand. 2022. Smart recon: Network traffic fingerprinting for IoT device identification. In Proceedings of the IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC’22). IEEE, 0072–0079.

[133]

Stephen Ugwuanyi and James Irvine. 2020. Security analysis of IoT networks and platforms. In Proceedings of the International Symposium on Networks, Computers and Communications (ISNCC’20). 1–6.

[134]

Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, and Jan S. Rellermeyer. 2020. A survey on distributed machine learning. ACM Comput. Surv. 53, 2, Article 30 (March 2020), 33 pages.

Digital Library

[135]

Wei Wang, Ming Zhu, Xuewen Zeng, Xiaozhou Ye, and Yiqiang Sheng. 2017. Malware traffic classification using convolutional neural network for representation learning. In Proceedings of the International Conference on Information Networking (ICOIN’17). IEEE, 712–717.

[136]

Zhanyi Wang. 2015. The applications of deep learning on traffic identification. BlackHat USA 24, 11 (2015), 1–10.

[137]

Mi Wen, Jingsheng Lei, and Zhongqin Bi. 2013. Sse: A secure searchable encryption scheme for urban sensing and querying. Int. J. Distrib. Sens. Netw. 9, 12 (2013), 302147.

[138]

Jason West. 2018. A prediction model framework for cyber-attacks to precision agriculture technologies. J. Agric. Food Inf. 19, 4 (2018), 307–330.

[139]

Wikipedia. [n.d.]. Precision Agriculture. Retrieved January 30, 2021 from https://en.wikipedia.org/wiki/Precision_agriculture.

[140]

Charlie Wilson, Tom Hargreaves, and Richard Hauxwell-Baldwin. 2014. Smart homes and their users: A systematic analysis and key challenges. Pers. Ubiq. Comput. 19 (02 2014), 463–476.

Digital Library

[141]

Kuai Xu, Yinxin Wan, Guoliang Xue, and Feng Wang. 2019. Multidimensional behavioral profiling of internet-of-things in edge networks. In Proceedings of the IEEE/ACM International Symposium on Quality of Service (IWQoS’19).

[142]

L. D. Xu, W. He, and S. Li. 2014. Internet of Things in industries: A survey. IEEE Trans. Industr. Inf. 10, 4 (2014), 2233–2243.

[143]

Poonam Yadav, Angelo Feraudo, Budi Arief, Siamak F. Shahandashti, and Vassilios G. Vassilakis. 2020. Position paper: A systematic framework for categorising IoT device fingerprinting mechanisms. In Proceedings of the 2nd International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things. 62–68.

Digital Library

[144]

Y. Yang, L. Wu, G. Yin, L. Li, and H. Zhao. 2017. A survey on security and privacy issues in Internet-of-Things. IEEE IoT J. 4, 5 (2017), 1250–1258.

[145]

Feihong Yin, Li Yang, Jianfeng Ma, Yasheng Zhou, Yuchen Wang, and Jiahao Dai. 2021. Identifying IoT devices based on spatial and temporal features from network traffic. Secur. Commun. Netw. (2021).

[146]

Yawei Yue, Shancang Li, Phil Legg, and Fuzhong Li. 2021. Deep learning-based security behaviour analysis in IoT environments: A survey. Secur. Commun. Netw. (2021).

Digital Library

[147]

Jiliang Zhang, Chaoqun Shen, Haihan Su, Md Tanvir Arafin, and Gang Qu. 2021. Voltage over-scaling-based lightweight authentication for IoT security. IEEE Trans. Comput. (2021).

Digital Library

[148]

Eda Zhou, Joseph Turcotte, and Lorenzo De Carli. 2020. Enabling security analysis of IoT device-to-cloud traffic. In Proceedings of the IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom’20). 1888–1894.

Cited By

Thiruppathi KJaidhar C(2025)Detection and Mitigation of IoT Based DDoS Attack Using Extended MUD Enabled Device Profiling TechniquesAdvanced Network Technologies and Intelligent Computing10.1007/978-3-031-83783-8_6(99-121)Online publication date: 8-Mar-2025
https://doi.org/10.1007/978-3-031-83783-8_6
Mingo HLawson MWilliamson A(2024)Identifying New Vulnerabilities Embedded in Consumer Internet of Things (IoT) DevicesMultisector Insights in Healthcare, Social Sciences, Society, and Technology10.4018/979-8-3693-3226-9.ch011(186-207)Online publication date: 5-Jan-2024
https://doi.org/10.4018/979-8-3693-3226-9.ch011
Kalinaki KShafik WMasha MAlli A(2024)A Review of Artificial Intelligence Techniques for Improved Cloud and IoT SecurityEmerging Technologies for Securing the Cloud and IoT10.4018/979-8-3693-0766-3.ch002(38-68)Online publication date: 23-Feb-2024
https://doi.org/10.4018/979-8-3693-0766-3.ch002
Show More Cited By

Index Terms

A Survey on IoT Profiling, Fingerprinting, and Identification
1. Computing methodologies
  1. Machine learning
2. Security and privacy
  1. Intrusion/anomaly detection and malware mitigation

Recommendations

A top-down survey on securing IoT with machine learning: goals, recent advances and challenges

The Internet of Things (IoT) has seen it all from being just another innovation to a leading technology; it is now a binding force that interconnects various aspects of our lives. The IoT's tremendous growth is driven by emerging applications and evolving ...
IoT-PRIDS: Leveraging packet representations for intrusion detection in IoT networks
Abstract
The Internet of Things (IoT) devices have been integrated into almost all everyday applications of human life such as healthcare, transportation and agriculture. This widespread adoption of IoT has opened a large threat landscape to computer ...
Graphical abstract

Display Omitted
Highlights
- A new profiling method to detect abnormal packets using “packet representations”.
- A light-weight non-ML mechanism for IoT intrusion detection.
- Comprehensive evaluation of IoT-PRIDS for detection accuracy and efficiency.
A Survey on IoT Security: Vulnerability Detection and Protection
AITC '24: Proceedings of the 2024 International Conference on Artificial Intelligence of Things and Computing

The persistent evolution of Internet of Things (IoT) devices across various sectors, including industrial applications, smart homes, and smart cities, has elevated the discourse surrounding the security of these devices to a pivotal status. Considering ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Internet of Things

ACM Transactions on Internet of Things Volume 3, Issue 4

November 2022

244 pages

EISSN:2577-6207

DOI:10.1145/3551654

Editors:
Schahram Dustdar
TU Wien, Austria
,
Gian Pietro Picco
University of Trento, Italy

Issue’s Table of Contents

This article was authored by employees of the Government of Canada. As such, the Canadian government retains all interest in the copyright to this work and grants to ACM a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, provided that clear attribution is given both to the authors and the Canadian government agency employing them. Permission to make digital or hard copies for personal or classroom use is granted. Copies must bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the Canadian Government must be honored. To copy otherwise, distribute, republish, or post, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 06 September 2022

Online AM: 31 May 2022

Accepted: 01 May 2022

Revised: 01 March 2022

Received: 01 July 2021

Published in TIOT Volume 3, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Survey
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

32
Total Citations
View Citations
2,309
Total Downloads

Downloads (Last 12 months)723
Downloads (Last 6 weeks)81

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Thiruppathi KJaidhar C(2025)Detection and Mitigation of IoT Based DDoS Attack Using Extended MUD Enabled Device Profiling TechniquesAdvanced Network Technologies and Intelligent Computing10.1007/978-3-031-83783-8_6(99-121)Online publication date: 8-Mar-2025
https://doi.org/10.1007/978-3-031-83783-8_6
Mingo HLawson MWilliamson A(2024)Identifying New Vulnerabilities Embedded in Consumer Internet of Things (IoT) DevicesMultisector Insights in Healthcare, Social Sciences, Society, and Technology10.4018/979-8-3693-3226-9.ch011(186-207)Online publication date: 5-Jan-2024
https://doi.org/10.4018/979-8-3693-3226-9.ch011
Kalinaki KShafik WMasha MAlli A(2024)A Review of Artificial Intelligence Techniques for Improved Cloud and IoT SecurityEmerging Technologies for Securing the Cloud and IoT10.4018/979-8-3693-0766-3.ch002(38-68)Online publication date: 23-Feb-2024
https://doi.org/10.4018/979-8-3693-0766-3.ch002
Ahmed AQuoitin BGros AMoeyaert V(2024)A Comprehensive Survey on Deep Learning-Based LoRa Radio Frequency Fingerprinting IdentificationSensors10.3390/s2413441124:13(4411)Online publication date: 8-Jul-2024
https://doi.org/10.3390/s24134411
Moure-Garrido MGarcia-Rubio CCampo C(2024)Reducing DNS Traffic to Enhance Home IoT Device PrivacySensors10.3390/s2409269024:9(2690)Online publication date: 24-Apr-2024
https://doi.org/10.3390/s24092690
Neto EDadkhah SSadeghi SMolyneaux H(2024)Mitigating Adversarial Attacks against IoT ProfilingElectronics10.3390/electronics1313264613:13(2646)Online publication date: 5-Jul-2024
https://doi.org/10.3390/electronics13132646
Dini PDiana LElhanashi ASaponara S(2024)Overview of AI-Models and Tools in Embedded IIoT ApplicationsElectronics10.3390/electronics1312232213:12(2322)Online publication date: 13-Jun-2024
https://doi.org/10.3390/electronics13122322
Spinnler CLabs TFranchi N(2024)SoK: A Taxonomy for Hardware-Based Fingerprinting in the Internet of ThingsProceedings of the 19th International Conference on Availability, Reliability and Security10.1145/3664476.3670872(1-12)Online publication date: 30-Jul-2024
https://dl.acm.org/doi/10.1145/3664476.3670872
Alhirabi NBeaumont SRana OPerera C(2024)Designing Privacy-Aware IoT Applications for Unregulated DomainsACM Transactions on Internet of Things10.1145/36484805:2(1-32)Online publication date: 23-Apr-2024
https://dl.acm.org/doi/10.1145/3648480
Okui NNakahara MKubota A(2024)Survey and Experimentation to Compare IoT Device Model Identification Methods2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM60985.2024.00014(13-17)Online publication date: 4-Jun-2024
https://doi.org/10.1109/WoWMoM60985.2024.00014
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Full Text

View this article in Full Text.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View full text|Download PDF

View Issue’s Table of Contents