An Integrated Soc Tool

This paper reviews current SOC tools to identify the deficiencies encountered as well as analyses the emerging requirements of modern SOC environments. It means the use of automation, machine learning and visualization in SOC environ- ments is very important in order to increase speed and efficiency. This survey compiles the recent advances in SOC architecture, automation interfaces and real-time data processing. After going through the paper, the following significant observations can be made: Firstly, there is a lack of coordination in linking numerous tools collectively; secondly, when it comes to the enhancement of the detection rate , the engagement of the machine learning algorithm; and thirdly, rising automation trends that help to minimize a huge amount of manual work. Challenges that have kept SOC from gaining widespread acceptance are discussed including cost, technical expertise, and privacy issues, followed by strategies of how an improved SOC tool can be created to overcome the drawbacks of existing solutions.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-26
DOI
https://doi.org/10.5281/zenodo.14557504
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

An Integrated Soc Tool

Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
article

An Integrated Soc Tool

article en

Abstract

This paper reviews current SOC tools to identify the deficiencies encountered as well as analyses the emerging requirements of modern SOC environments. It means the use of automation, machine learning and visualization in SOC environ- ments is very important in order to increase speed and efficiency. This survey compiles the recent advances in SOC architecture, automation interfaces and real-time data processing. After going through the paper, the following significant observations can be made: Firstly, there is a lack of coordination in linking numerous tools collectively; secondly, when it comes to the enhancement of the detection rate , the engagement of the machine learning algorithm; and thirdly, rising automation trends that help to minimize a huge amount of manual work. Challenges that have kept SOC from gaining widespread acceptance are discussed including cost, technical expertise, and privacy issues, followed by strategies of how an improved SOC tool can be created to overcome the drawbacks of existing solutions.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 62%
Parallel Computing and Optimization Techniques
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