Academic Journal

Analysis assaulting pattern for the security problem monitoring in 5G‐enabled sensor network systems with big data environment using artificial intelligence/machine learning

التفاصيل البيبلوغرافية
العنوان: Analysis assaulting pattern for the security problem monitoring in 5G‐enabled sensor network systems with big data environment using artificial intelligence/machine learning
المؤلفون: Anand Singh Rajawat, S. B. Goyal, Pradeep Bedi, Sandeep Kautish, Divya Prakash Shrivastava
المصدر: IET Wireless Sensor Systems, Vol 14, Iss 5, Pp 181-194 (2024)
بيانات النشر: Wiley, 2024.
سنة النشر: 2024
المجموعة: LCC:Telecommunication
مصطلحات موضوعية: internet of things, security of data, sensors, Telecommunication, TK5101-6720
الوصف: Abstract The 5G‐enabled sensor network systems make it possible to connect cyber and real ‘things’ in many ways. Even so, the flow of data between 5G‐enabled sensor devices brings big data environment problems, such as huge amounts of data, duplicated data, a lack of scalability etc. Some of these problems are as follows. It is hard to keep an eye on 5G‐enabled sensor systems in a ‘big data’ environment. Cyberattacks that could put the safety of the sensor network systems at risk are hard to find, which make the situation even more complicated. The security challenges of 5G‐enabled Sensor Network Systems are studied and analyzed due to some constraints associated with the sensor nodes. The proposed advanced algorithm for securing the 5G‐enabled sensor systems is a Multidimensional big data environment using artificial intelligence/machine learning (AI/ML). Using a structure that depends on both geographical and temporal data, an improved clear point selection operation may get important information from multidimensional time series data that is spread across a wide range of sensor nodes. Therefore, the actions of the 5G‐enabled sensor network can be shown accurately and a complete model of its underlying data structure is built to analysis attacking, pattern on 5G‐enabled Sensor Network Systems using the AI/ML Algorithm.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2043-6394
2043-6386
Relation: https://doaj.org/toc/2043-6386; https://doaj.org/toc/2043-6394
DOI: 10.1049/wss2.12049
URL الوصول: https://doaj.org/article/07282bcc02eb4fccae9fd184d4df3d56
رقم الانضمام: edsdoj.07282bcc02eb4fccae9fd184d4df3d56
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20436394
20436386
DOI:10.1049/wss2.12049