Full Paper View Go Back

Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges

Danial Haider1 , Tehreem Saboor2 , Aqsa Rais3

  1. Dept. of Avionics Engineering, Air University, Islamabad 44000, Pakistan.
  2. Dept. of Computer Science, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, Islamabad 44000, Pakistan.
  3. Dept. of Computer Science, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, Islamabad 44000, Pakistan.

Section:Research Paper, Product Type: Journal-Paper
Vol.12 , Issue.4 , pp.32-47, Aug-2024


Online published on Aug 31, 2024


Copyright © Danial Haider, Tehreem Saboor, Aqsa Rais . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Danial Haider, Tehreem Saboor, Aqsa Rais, “Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges,” International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.32-47, 2024.

MLA Style Citation: Danial Haider, Tehreem Saboor, Aqsa Rais "Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges." International Journal of Scientific Research in Computer Science and Engineering 12.4 (2024): 32-47.

APA Style Citation: Danial Haider, Tehreem Saboor, Aqsa Rais, (2024). Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges. International Journal of Scientific Research in Computer Science and Engineering, 12(4), 32-47.

BibTex Style Citation:
@article{Haider_2024,
author = {Danial Haider, Tehreem Saboor, Aqsa Rais},
title = {Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {8 2024},
volume = {12},
Issue = {4},
month = {8},
year = {2024},
issn = {2347-2693},
pages = {32-47},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3593},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3593
TI - Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Danial Haider, Tehreem Saboor, Aqsa Rais
PY - 2024
DA - 2024/08/31
PB - IJCSE, Indore, INDIA
SP - 32-47
IS - 4
VL - 12
SN - 2347-2693
ER -

78 Views    81 Downloads    17 Downloads
  
  

Abstract :
As we know, the cyber-attacks are merging day by day. Everything that relates to the internet has compromised with the attacks. Internet connection and their connectivity with other devices make them more vulnerable to attacks. Numerous industries, including aerial observation, wireless communication, healthcare, construction, precision farming, search and rescue, and the military, heavily rely on their usage. Moreover, these systems or networks are still exposed and have loopholes that make it welcomed to attackers to invade the system or network easily. Intrusion detection system is the system that is used to sense and also protect the network from cyber-attacks that are possible due to internet connections. This paper highlights the threat and issues that are link with the intrusion detection system in IoT domain. Also, paper emphasis on the significance or importance of the IDS in IoT. Also highlights the various IDS like signature-based IDS, anomaly-based IDS etc. Furthermore, describes and elaborates the problems that are faced with respect to each type of IDS. Finally, suggest remediation against each problem of each type of IDS to safeguard the IoT domain.

Key-Words / Index Term :
IoT, IDS, Attacks, Challenges

References :
[1] Spadaccino, P., & Cuomo, F. Intrusion Detection Systems for IoT: opportunities and challenges offered by Edge Computing and Machine Learning. arXiv preprint arXiv:2012.01174,2020
[2] Sanju, P. Enhancing Intrusion Detection in IoT Systems: A Hybrid Metaheuristics-Deep Learning Approach with Ensemble of Recurrent Neural Networks. Journal of Engineering Research, 100122, 2023
[3] Sicato, J. C. S., Singh, S. K., Rathore, S., & Park, J. H. A comprehensive analyses of intrusion detection system for IoT environment. Journal of Information Processing Systems, 16(4), 975-990, 2020
[4] R. Nicole, “Title of paper with only first word capitalized,” J. Name Khan, A. R., Kashif, M., Jhaveri, R. H., Raut, R., Saba, T., & Bahaj, S. A. Deep learning for intrusion detection and security of Internet of things (IoT): current analysis, challenges, and possible solutions. Security and Communication Networks, 2022.Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interface,” IEEE Transl. J. Magn. Japan, vol. 2, pp. 740–741, August 1987 [Digests 9th Annual Conf. Magnetics Japan, p. 301, 1982],2022
[5] Benkhelifa, E., Welsh, T., & Hamouda, W. A critical review of practices and challenges in intrusion detection systems for IoT: Toward universal and resilient systems. IEEE communications surveys & tutorials, 20(4), 3496-3509.2018
[6] Hassija, V.; Saxena, V.; Chamola, V. Scheduling drone charging for multi-drone network based on consensus time-stamp and game theory. Comput. Commun. 2019, 149, 51–61. [Google Scholar] [CrossRef]
[7] Khraisat, A., & Alazab, A. A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges. Cybersecurity, 4, 1-27, 2021
[8] Awajan, A. A novel deep learning-based intrusion detection system for IOT networks. Computers, 12(2), 34,2023
[9] Santhosh Kumar, S. V. N., Selvi, M., & Kannan, A. A comprehensive survey on machine learning-based intrusion detection systems for secure communication in internet of things. Computational Intelligence and Neuroscience, 2023.
[10] Mohy-eddine, M., Guezzaz, A., Benkirane, S., & Azrour, M. An efficient network intrusion detection model for IoT security using K-NN classifier and feature selection. Multimedia Tools and Applications, 1-19,2023
[11] Shah, H., Shah, D., Jadav, N. K., Gupta, R., Tanwar, S., Alfarraj, O., ... & Marina, V. Deep learning-based malicious smart contract and intrusion detection system for IoT environment. Mathematics, 11(2), 418.,2023
[12] Othman, T. S., Koy, K. R., & Abdullah, S. M. Intrusion Detection Systems for IoT Attack Detection and Identification Using Intelligent Techniques. networks, 5(6),2023
[13] Savanovi?, N., Toskovic, A., Petrovic, A., Zivkovic, M., Damaševi?ius, R., Jovanovic, L., ... & Nikolic, B. Intrusion detection in healthcare 4.0 internet of things systems via metaheuristics optimized machine learning. Sustainability, 15(16), 12563 ,2023
[14] Bhavsar, M., Roy, K., Kelly, J., & Olusola, O. Anomaly-based intrusion detection system for IoT application. Discover Internet of Things, 3(1), 5 ,2023
[15] Mahadik, S., Pawar, P. M., & Muthalagu, R. Efficient Intelligent Intrusion Detection System for Heterogeneous Internet of Things (HetIoT). Journal of Network and Systems Management, 31(1), 2,2023
[16] Heidari, A., & Jabraeil Jamali, M. A. Internet of Things intrusion detection systems: A comprehensive review and future directions. Cluster Computing, 26(6), 3753-3780 ,2023
[17] Jeyaselvi, M., Dhanaraj, R. K., Sathya, M., Memon, F. H., Krishnasamy, L., Dev, K., ... & Qureshi, N. M. F. A highly secured intrusion detection system for IoT using EXPSO-STFA feature selection for LAANN to detect attacks. Cluster Computing, 26(1), 559-574 ,2023
[18] Musleh, D., Alotaibi, M., Alhaidari, F., Rahman, A., & Mohammad, R. M. Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT. Journal of Sensor and Actuator Networks, 12(2), 29,2023
[19] Al Sawafi, Y., Touzene, A., & Hedjam, R.Hybrid Deep Learning-Based Intrusion Detection System for RPL IoT Networks. Journal of Sensor and Actuator Networks, 12(2), 21,2023
[20] Otoum, Y., Liu, D., & Nayak, A. DL?IDS: a deep learning–based intrusion detection framework for securing IoT. Transactions on Emerging Telecommunications Technologies, 33(3), e3803,2022
[21] Ahmad, Z., Shahid Khan, A., Wai Shiang, C., Abdullah, J., & Ahmad, F. Network intrusion detection system: A systematic study of machine learning and deep learning approaches. Transactions on Emerging Telecommunications Technologies, 32(1), e4150,2021
[22] Visoottiviseth, V., Sakarin, P., Thongwilai, J., & Choobanjong, T. Signature-based and behavior-based attack detection with machine learning for home IoT devices. In 2020 IEEE REGION 10 CONFERENCE (TENCON) (pp. 829-834). IEEE,2020
[23] Khattak, H. A., Shah, M. A., Khan, S., Ali, I., & Imran, M. Perception layer security in Internet of Things. Future Generation Computer Systems, 100, 144-164. 2019
[24] OS, J. N., & Bhanu, S. M. S. A survey on code injection attacks in mobile cloud computing environment. In 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 1-6). IEEE.2018, January
[25] M. Devi and A. Majumder, ‘‘Side-channel attack in Internet of Things: A survey,’’ in Applications of Internet of Things (Lecture Notes in Networks and Systems), J. K. Mandal, S. Mukhopadhyay, and A. Roy, Eds. Singapore: Springer, 2021, pp. 213–222.
[26] K. O. A. Alimi, K. Ouahada, A. M. Abu-Mahfouz, and S. Rimer, ‘‘A survey on the security of low power wide area networks: Threats, challenges, and potential solutions,’’ Sensors, vol. 20, no. 20, pp. 1–19, 2020
[27] H. Mrabet, S. Belguith, A. Alhomoud, and A. Jemai, ‘‘A survey of IoT security based on a layered architecture of sensing and data analysis,’’ K. Nirmal, B. Janet, and R. Kumar, ‘‘Analyzing and eliminating phishing
[28] R. Vishwakarma and A. K. Jain, ‘‘A survey of DDoS attacking techniques and defence mechanisms in the IoT network,’’ Telecommun. Syst., vol. 73, no. 1, pp. 3–25, Jan. 2020
[29] Raoof, A. Matrawy, and C.-H. Lung, ‘‘Enhancing routing security in IoT: Performance evaluation of RPL’s secure mode under attacks,’’ IEEE Internet Things J., vol. 7, no. 12, pp. 11536–11546, Dec. 2020.
[30] D. Dinculean? and X. Cheng, ‘‘Vulnerabilities and limitations of MQTT protocol used between IoT devices,’’ Appl. Sci., vol. 9, no. 5, p. 848, Feb. 2019.
[31] Tewari and B. B. Gupta, ‘‘Security, privacy and trust of different layers in Internet-of-Things (IoTs) framework,’’ Future Gener. Comput. Syst., vol. 108, pp. 909–920, Jul. 2020.
[32] Ahlawat, A. Sangwan, and V. Sindhu, ‘‘IoT system model, challenges and threats,’’ Int. J. Sci. Technol. Res., vol. 9, no. 3, pp. 6771–6776, 2020.
[33] Prabadevi and N. Jeyanthi, ‘‘A review on various sniffing attacks and its mitigation techniques,’’ Indonesian J. Elect. Eng. Comput. Sci., vol. 12, no. 3, pp. 1117–1125, 2018
[34] Tariq, N., Saboor, T., Ashraf, M., Butt, R., Anwar, M., & Humayun, M. IoT Security, Future Challenges, and Open Issues. In Cybersecurity Measures for Logistics Industry Framework (pp. 116-140). IGI Global. 2024
[35] Butt, M. H. F., Li, J. P., Saboor, T., Arslan, M., & Butt, M. A. F. Intelligent Phishing Url Detection: A Solution Based On Deep Learning Framework. In 2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) (pp. 434-439). IEEE. 2021, December.
[36] Butt, M. H. F., Li, J. P., & Saboor, T. A tunable and explainable attributes (TEA) for recommendation system. In 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) (pp. 39-43). IEEE. 2020, December
[37] Mortada M. Abdulwahab, Hadeel A.Mohamed, Mutseuim A. Alameen, Mohamed A. Mosalam, Faris M.Elsadig, "Wireless Sensor Network of Monitoring Water Distribution Network Service using IoT," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.1, pp.51-55, 2023
[38] Prabhat Bisht, Manmohan Singh Rauthan, "Machine Learning and Natural Language Processing Based Web Application Firewall for Mitigating Cyber Attacks in Cloud," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.3, pp.1-15, 2023

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at  support@isroset.org or view contact page for more details.

Go to Navigation