A conceptual anonymity model to ensure privacy for sensitive network data
In today's world, a great amount of people, devices, and sensors are well connected through various online platforms, and the interactions between these entities produce massive amounts of useful information. This process of data production and sharing appears to be on the rise. The growing pop...
Main Authors: | Arafat, N.H.M., Pramanik, Md Ileas, Abu Jafar, Md Muzahid, Lu, Bibo, Jahan, Sumaiya, Murad, Saydul Akbar |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2021
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/42380/1/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy.pdf http://umpir.ump.edu.my/id/eprint/42380/2/A%20conceptual%20anonymity%20model%20to%20ensure%20privacy%20for%20sensitive%20network%20data_ABS.pdf |
Similar Items
-
PhishGuard: Machine learning-powered phishing URL detection
by: Murad, Saydul Akbar, et al.
Published: (2023) -
Multiple vehicle cooperation and collision avoidance in automated vehicles : Survey and an AI‑enabled conceptual framework
by: Abu Jafar, Md Muzahid, et al.
Published: (2023) -
Impact learning : A learning method from feature’s impact and competition
by: Prottasha, Nusrat Jahan, et al.
Published: (2023) -
SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
by: Murad, Saydul Akbar, et al.
Published: (2024) -
Impact learning: A learning method from feature’s impact and competition
by: Prottasha, Nusrat Jahan, et al.
Published: (2023)