Exploring enterprise information security management and risk assessment through big data and the Internet of Things

With the rapid evolution of information technology, enterprise information security management and risk assessment have gained paramount importance. The objective of this study is to offer a comprehensive solution aimed at bolstering the accuracy, security, and efficiency of information security management. This is achieved through the integration of big data and Internet of Things (IoT) technologies, thereby safeguarding critical enterprise data and private information. Effective management of enterprise information security systems is imperative for upholding confidentiality, integrity, and availability, necessitating a holistic approach. This study, through in-depth theoretical analysis, proposes the combination of blockchain technology with big data to enhance the security and trustworthiness of enterprise IoT systems. Starting with practical issues, the study stores identification cards for IoT sensor devices and related information’s hash values in the blockchain, thus establishing an integrated enterprise information security IoT system model that combines big data and blockchain. Finally, the model is tested and subjected to risk assessment. The results show that the model achieves an identification accuracy of 90.941% for system information security management, with stable data transmission latency at around 192 milliseconds, significantly outperforming other algorithms. This research carries significant implications for the field of enterprise information security management by presenting an innovative solution that demonstrates lower communication overhead and higher throughput than alternative algorithms. It not only pioneers a novel approach to managing enterprise information security but also establishes a robust experimental groundwork for the future evolution of intelligent enterprise information security management systems. By enhancing the efficiency of information security and risk assessments, this study aims to propel forward advancements in enterprise information security management, potentially mitigating risks to businesses and individuals alike, thereby contributing to the stability and security of the digital society.

Authors

Institutions

Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2024-11-14
DOI
https://doi.org/10.1177/14727978241300787
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring enterprise information security management and risk assessment through big data and the Internet of Things

Hongfang Yu
Journal of Computational Methods in Sciences and Engineering
Blockchain Technology Applications and Security
article

Exploring enterprise information security management and risk assessment through big data and the Internet of Things

Hongfang Yu
article en

Abstract

With the rapid evolution of information technology, enterprise information security management and risk assessment have gained paramount importance. The objective of this study is to offer a comprehensive solution aimed at bolstering the accuracy, security, and efficiency of information security management. This is achieved through the integration of big data and Internet of Things (IoT) technologies, thereby safeguarding critical enterprise data and private information. Effective management of enterprise information security systems is imperative for upholding confidentiality, integrity, and availability, necessitating a holistic approach. This study, through in-depth theoretical analysis, proposes the combination of blockchain technology with big data to enhance the security and trustworthiness of enterprise IoT systems. Starting with practical issues, the study stores identification cards for IoT sensor devices and related information’s hash values in the blockchain, thus establishing an integrated enterprise information security IoT system model that combines big data and blockchain. Finally, the model is tested and subjected to risk assessment. The results show that the model achieves an identification accuracy of 90.941% for system information security management, with stable data transmission latency at around 192 milliseconds, significantly outperforming other algorithms. This research carries significant implications for the field of enterprise information security management by presenting an innovative solution that demonstrates lower communication overhead and higher throughput than alternative algorithms. It not only pioneers a novel approach to managing enterprise information security but also establishes a robust experimental groundwork for the future evolution of intelligent enterprise information security management systems. By enhancing the efficiency of information security and risk assessments, this study aims to propel forward advancements in enterprise information security management, potentially mitigating risks to businesses and individuals alike, thereby contributing to the stability and security of the digital society.

Journal of Computational Methods in Sciences and EngineeringVol. 25(2)
Hunan City University (CN)
Openalex Percentile: Top 52%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.