With
technology constantly becoming present in people’s lives, smart homes are
increasing in popularity. A smart home system controls lighting, temperature, security
camera systems, and appliances. These devices and sensors are connected to the
internet, and these devices can easily become the target of attacks. To
mitigate the risk of using smart home devices, the security and privacy thereof
must be artificially smart so they can adapt based on user behavior and environments.
The security and privacy systems must accurately analyze all actions and predict
future actions to protect the smart home system. We propose a Hybrid Intrusion Detection
(HID) system using machine learning algorithms, including random forest, X gboost,
decision tree, K -nearest neighbors, and misuse detection technique.
References
[1]
Alghayadh, F. and Debnath, D. (2020) Hid-Smart: Hybrid Intrusion Detection Model for Smart Home. 2020 10th Annual Computing and Communication Workshop and Conference, Las Vegas, 6-8 January 2020, 384-389.
https://doi.org/10.1109/CCWC47524.2020.9031177
[2]
Granjal, J., Monteiro, E. and Silva, J.S. (2015) Security for the Internet of Things: A Survey of Existing Protocols and Open Research Issues. IEEE Communications Surveys & Tutorials, 17, 1294-1312. https://doi.org/10.1109/COMST.2015.2388550
[3]
Lee, K., Kim, D., Ha, D., Rajput, U. and Oh, H. (2015) On Security and Privacy Issues of Fog Computing Supported Internet of Things Environment. 2015 6th International Conference on the Network of the Future, Montreal, 30 September-2 October 2015, 1-3. https://doi.org/10.1109/NOF.2015.7333287
[4]
Yamauchi, M., Ohsita, Y., Murata, M., Ueda, K. and Kato, Y. (2019) Anomaly Detection for Smart Home Based on User behavior. 2019 IEEE International Conference on Consumer Electronics, Las Vegas, 11-13 January 2019, 1-6.
https://doi.org/10.1109/ICCE.2019.8661976
[5]
Lee, I. and Lee, K. (2015) The Internet of Things (IoT): Applications, Investments, and Challenges for Enterprises. Business Horizons, 58, 431-440.
https://doi.org/10.1016/j.bushor.2015.03.008
[6]
Capellupo, M., Liranzo, J., Bhuiyan, M.Z.A., Hayajneh, T. and Wang, G. (2017) Security and Attack Vector Analysis of IoT Devices. International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, Guangzhou, 12-15 December 2017, 593-606.
https://doi.org/10.1007/978-3-319-72395-2_54
[7]
Antonakakis, M., April, T., Bailey, M., Bernhard, M., Bursztein, E., Cochran, J., Durumeric, Z., Halderman, J.A., Invernizzi, L., Kallitsis, M., et al. (2017) Understanding the Mirai Botnet. 26th USENIX Security Symposium, Vancouver, 16-18 August 2017, 1093-1110.
[8]
Shirali-Shahreza, S. and Ganjali, Y. (2018) Protecting Home User Devices with An SDN-Based Firewall. IEEE Transactions on Consumer Electronics, 64, 92-100.
https://doi.org/10.1109/TCE.2018.2811261
[9]
Kim, B.-K., Hong, S.-K., Jeong, Y.-S. and Eom, D.-S. (2008) The Study of Applying Sensor Networks to a Smart Home. 2008 Fourth International Conference on Networked Computing and Advanced Information Management, Gyeongju, 2-4 September 2008, 676-681. https://doi.org/10.1109/NCM.2008.221
[10]
Xu, K., Wang, F., Egli, R., Fives, A., Howell, R. and Mcintyre, O. (2014) Object-Oriented Big Data Security Analytics: A Case Study on Home Network Traffic. International Conference on Wireless Algorithms, Systems, and Applications, Harbin, 23-25 June 2014, 313-323. https://doi.org/10.1007/978-3-319-07782-6_29
[11]
Komninos, N., Philippou, E. and Pitsillides, A. (2014) Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures. IEEE Communications Surveys & Tutorials, 16, 1933-1954.
https://doi.org/10.1109/COMST.2014.2320093
[12]
Chase, J. (2013) The Evolution of the Internet of Things. Texas Instruments, 1, 1-7.
[13]
Alghayadh, F. and Debnath, D. (2020) A Hybrid Intrusion Detection System for Smart Home Security. 2020 IEEE International Conference on Electro Information Technology, Chicago, 31 July-1 August 2020, 319-323.
https://doi.org/10.1109/EIT48999.2020.9208296
[14]
Mamdouh, M., Elrukhsi, M.A. and Khattab, A. (2018) Securing the Internet of Things and Wireless Sensor Networks via Machine Learning: A Survey. 2018 International Conference on Computer and Applications, Beirut, 25-26 August 2018, 215-218. https://doi.org/10.1109/COMAPP.2018.8460440
[15]
Perlich, C. (2010) Learning Curves in Machine Learning. In: Sammut, C. and Webb, G.I., Eds., Encyclopedia of Machine Learning, Springer, Boston, 10-50.
https://doi.org/10.1007/978-0-387-30164-8
[16]
Geneiatakis, D., Kounelis, I., Neisse, R., Nai-Fovino, I., Steri, G. and Baldini, G. (2017) Security and Privacy Issues for an IoT Based Smart Home.2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics, Opatija, 22-26 May 2017, 1292-1297.
https://doi.org/10.23919/MIPRO.2017.7973622
[17]
Dixit, A. and Naik, A. (2014) Use of Prediction Algorithms in Smart Homes. International Journal of Machine Learning and Computing, 4, 157-162.
https://doi.org/10.7763/IJMLC.2014.V4.405
[18]
Samuel, S.S.I. (2016) A Review of Connectivity Challenges in IoT-Smart Home. 2016 3rd MEC International Conference on Big Data and Smart City, Muscat, 15-16 March 2016, 1-4. https://doi.org/10.1109/ICBDSC.2016.7460395
[19]
Altolini, D., Lakkundi, V., Bui, N., Tapparello, C. and Rossi, M. (2013) Low Power Link Layer Security for IoT: Implementation and Performance Analysis. 2013 9th International Wireless Communications and Mobile Computing Conference, Sardinia, 1-5 July 2013, 919-925. https://doi.org/10.1109/IWCMC.2013.6583680
[20]
Giri, A., Dutta, S., Neogy, S., Dahal, K. and Pervez, Z. (2017) Internet of Things (IoT): A Survey on Architecture, Enabling technologies, Applications and Challenges. Proceedings of the 1st International Conference on Internet of Things and Machine Learning, Liverpool, October 2017, Article No. 7.
https://doi.org/10.1145/3109761.3109768
[21]
Dey, S., Roy, A. and Das, S. (2016) Home Automation Using Internet of Thing. 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, New York, 20-22 October 2016, 1-6.
https://doi.org/10.1109/UEMCON.2016.7777826
[22]
Bugeja, J., Jacobsson, A. and Davidsson, P. (2016) On Privacy and Security Challenges in Smart Connected Homes. 2016 European Intelligence and Security Informatics Conference, Uppsala, 17-19 August 2016, 172-175.
https://doi.org/10.1109/EISIC.2016.044
[23]
Karimi, K. and Krit, S. (2019) Smart Home-Smartphone Systems: Threats, Security Requirements and Open Research Challenges. 2019 International Conference of Computer Science and Renewable Energies, Agadir, 22-24 July 2019, 1-5.
https://doi.org/10.1109/ICCSRE.2019.8807756
[24]
Yang, Y., Wu, L., Yin, G., Li, L. and Zhao, H. (2017) A Survey on Security and Privacy Issues in Internet-of-Things. IEEE Internet of Things Journal, 4, 1250-1258.
https://doi.org/10.1109/JIOT.2017.2694844
[25]
Brdiczka, O., Langet, M., Maisonnasse, J. and Crowley, J.L. (2008) Detecting Human Behavior Models from Multimodal Observation in a Smart Home. IEEE Transactions on Automation Science and Engineering, 6, 588-597.
https://doi.org/10.1109/TASE.2008.2004965
[26]
Alghayadh, F. and Debnath, D. (2020) Performance Evaluation of Machine Learning for Prediction of Network Traffic in a Smart Home. 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, New York, 28-31 October 2020, 837-842.
https://doi.org/10.1109/UEMCON51285.2020.9298134
[27]
Amouri, A., Alaparthy, V.T. and Morgera, S.D. (2018) Cross Layer-Based Intrusion Detection Based on Network Behavior for IoT. 2018 IEEE 19th Wireless and Microwave Technology Conference, Sand Key, 9-10 April 2018, 1-4.
https://doi.org/10.1109/WAMICON.2018.8363921
[28]
Doshi, R., Apthorpe, N. and Feamster, N. (2018) Machine Learning ddos Detection for Consumer Internet of Things Devices. 2018 IEEE Security and Privacy Workshops, San Francisco, 24 May 2018, 29-35. https://doi.org/10.1109/SPW.2018.00013
[29]
Shahreza, M.L., Moazzami, D., Moshiri, B. and Delavar, M. (2011) Anomaly Detection Using a Self-Organizing Map and Particle Swarm Optimization. Scientia Iranica, 18, 1460-1468. https://doi.org/10.1016/j.scient.2011.08.025
[30]
Novák, M., Jakab, F. and Lain, L. (2013) Anomaly Detection in User Daily Patterns in Smart-Home Environment. Journal of Selected Areas in Health Informatics, 3, 1-11.
[31]
Cook, D.J., Crandall, A.S., Thomas, B.L. and Krishnan, N.C. (2012) CASAS: A Smart Home in a Box. Computer, 46, 62-69. https://doi.org/10.1109/MC.2012.328
