Authors :
M.Y.A Sankalpa; Perera I.U; Perera M.G.D; Dr. Lakmal Rupasinghe; Dahanayake N.K; Chethana Liyanapathirana
Volume/Issue :
Volume 8 - 2023, Issue 10 - October
Google Scholar :
https://tinyurl.com/4xb4dext
Scribd :
https://tinyurl.com/27kckdpw
DOI :
https://doi.org/10.5281/zenodo.10049933
Abstract :
As remote work has gained significant
momentum, many companies are allowing bring-your-
own-device (BYOD) environments where employees are
allowed to use personal devices to access work-related
networks, systems, files and applications. As
organizations increasingly embrace bring-your-own-
device (BYOD) policies, security concerns are critical.
Employees using their personal devices to access sensitive
business data under BYOD poses several new concerns.
This paper explores how organizations can challenge the
overabundance of useless and outdated files, as well as the
storage of documents that outlive their usefulness, lack of
visibility into file severity, and identification of potential
risks. Therefore, organizations must be aware of the
location, nature and sensitivity of company collaboration
data. Also, random, inconsistent, or unexpected behavior
in a system is called anomalous behavior or simply
anomaly. Analyzing system activity, defective detection,
security scanning, failure, and risk prediction are all
helped by ML integrated log analysis. Identification of
anomalies align with the security risks not only enough.
As a result, the AI-based recommendation system may be
utilized to provide consumers individualized
recommendations and feedback based on their
preferences and areas of interest.
Keywords :
BYOD, Organization, Application, Detection, user Behavior.
As remote work has gained significant
momentum, many companies are allowing bring-your-
own-device (BYOD) environments where employees are
allowed to use personal devices to access work-related
networks, systems, files and applications. As
organizations increasingly embrace bring-your-own-
device (BYOD) policies, security concerns are critical.
Employees using their personal devices to access sensitive
business data under BYOD poses several new concerns.
This paper explores how organizations can challenge the
overabundance of useless and outdated files, as well as the
storage of documents that outlive their usefulness, lack of
visibility into file severity, and identification of potential
risks. Therefore, organizations must be aware of the
location, nature and sensitivity of company collaboration
data. Also, random, inconsistent, or unexpected behavior
in a system is called anomalous behavior or simply
anomaly. Analyzing system activity, defective detection,
security scanning, failure, and risk prediction are all
helped by ML integrated log analysis. Identification of
anomalies align with the security risks not only enough.
As a result, the AI-based recommendation system may be
utilized to provide consumers individualized
recommendations and feedback based on their
preferences and areas of interest.
Keywords :
BYOD, Organization, Application, Detection, user Behavior.
