Distinctive Measurement Scheme for Security and Privacy in Internet of Things Applications Using Machine Learning Algorithms

被引:12
作者
Alhalabi, Wadee [1 ]
Al-Rasheed, Amal [2 ]
Manoharan, Hariprasath [3 ]
Alabdulkareem, Eatedal [4 ]
Alduailij, Mai [4 ]
Alduailij, Mona [4 ]
Selvarajan, Shitharth [5 ]
机构
[1] King Abdulaziz Univ, Comp Sci Dept, Virtual Real Res Grp, POB 80200, Jeddah 21589, Saudi Arabia
[2] Princess Nourah Bint Abdulrahman Univ, Coll Comp & Informat Sci, Dept Informat Syst, POB 84428, Riyadh 11671, Saudi Arabia
[3] Panimalar Engn Coll, Dept Elect & Commun Engn, Chennai 600069, India
[4] Princess Nourah Bint Abdulrahman Univ, Coll Comp & Informat Sci, Dept Comp Sci, POB 84428, Riyadh 11671, Saudi Arabia
[5] Kebri Dehar Univ, Dept Comp Sci & Engn, Kebri Dehar 250, Ethiopia
关键词
software defined networks (SDN); security; privacy; Internet of Things (IoT); machine learning; IOT;
D O I
10.3390/electronics12030747
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
More significant data are available thanks to the present Internet of Things (IoT) application trend, which can be accessed in the future using some platforms for data storage. An external storage space is required for practical purposes whenever a data storage platform is created. However, in the IoT, certain cutting-edge storage methods have been developed that compromise the security and privacy of data transfer processes. As a result, the suggested solution creates a standard mode of security operations for storing the data with little noise. One of the most distinctive findings in the suggested methodology is the incorporation of machine learning algorithms in the formulation of analytical representations. The aforementioned integration method ensures high-level quantitative measurements of data security and privacy. Due to the transmission of large amounts of data, users are now able to assess the reliability of data transfer channels and the duration of queuing times, where each user can separate the specific data that has to be transferred. The created system is put to the test in real time using the proper metrics, and it is found that machine learning techniques improve security more effectively. Additionally, for 98 percent of the scenarios defined, the accuracy for data security and privacy is maximized, and the predicted model outperforms the current method in all of them.
引用
收藏
页数:17
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共 22 条
  • [1] Safety, Security and Privacy in Machine Learning Based Internet of Things
    Abbas, Ghulam
    Mehmood, Amjad
    Carsten, Maple
    Epiphaniou, Gregory
    Lloret, Jaime
    [J]. JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2022, 11 (03)
  • [2] Secure lightweight cryptosystem for IoT and pervasive computing
    Abutaha, Mohammed
    Atawneh, Basil
    Hammouri, Layla
    Kaddoum, Georges
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [3] Optimal Accuracy-Privacy Trade-Off for Secure Computations
    Ah-Fat, Patrick
    Huth, Michael
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2019, 65 (05) : 3165 - 3182
  • [4] Blockchain-Based Trust and Reputation Management in SIoT
    Alam, Sana
    Zardari, Shehnila
    Shamsi, Jawwad Ahmed
    [J]. ELECTRONICS, 2022, 11 (23)
  • [5] Prevention of Cyber Security with the Internet of Things Using Particle Swarm Optimization
    Alterazi, Hassan A.
    Kshirsagar, Pravin R.
    Manoharan, Hariprasath
    Selvarajan, Shitharth
    Alhebaishi, Nawaf
    Srivastava, Gautam
    Lin, Jerry Chun-Wei
    [J]. SENSORS, 2022, 22 (16)
  • [6] Multi-Perspective Trust Management Framework for Crowdsourced IoT Services
    Bahutair, Mohammed
    Bouguettaya, Athman
    Neiat, Azadeh Ghari
    [J]. IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 15 (04) : 2396 - 2409
  • [7] LSB: A Lightweight Scalable Blockchain for IoT security and anonymity
    Dorri, Ali
    Kanhere, Salil S.
    Jurdak, Raja
    Gauravaram, Praveen
    [J]. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2019, 134 : 180 - 197
  • [8] UML Profile for Messaging Patterns in Service-Oriented Architecture, Microservices, and Internet of Things
    Gorski, Tomasz
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (24):
  • [9] A Robust Security Task Offloading in Industrial IoT-Enabled Distributed Multi-Access Edge Computing
    Gyamfi, Eric
    Jurcut, Anca
    [J]. FRONTIERS IN SIGNAL PROCESSING, 2022, 2
  • [10] Text Data Security and Privacy in the Internet of Things: Threats, Challenges, and Future Directions
    Khadam, Umair
    Iqbal, Muhammad Munwar
    Alruily, Meshrif
    Al Ghamdi, Mohammed A.
    Ramzan, Muhammad
    Almotiri, Sultan H.
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2020, 2020