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Bibliographic Details
Main Author: Kumar, Subhadip
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2312.06008
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author Kumar, Subhadip
author_facet Kumar, Subhadip
contents Artificial Intelligence for IT Operations (AIOps) is a rapidly growing field that applies artificial intelligence and machine learning to automate and optimize IT operations. AIOps vendors provide services that ingest end-to-end logs, traces, and metrics to offer a full stack observability of IT systems. However, these data sources may contain sensitive information such as internal IP addresses, hostnames, HTTP headers, SQLs, method/argument return values, URLs, personal identifiable information (PII), or confidential business data. Therefore, data security is a crucial concern when working with AIOps vendors. In this article, we will discuss the security features offered by different vendors and how we can adopt best practices to ensure data protection and privacy.
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publishDate 2023
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spellingShingle Guardians of Trust: Navigating Data Security in AIOps through Vendor Partnerships
Kumar, Subhadip
Cryptography and Security
Artificial Intelligence
Artificial Intelligence for IT Operations (AIOps) is a rapidly growing field that applies artificial intelligence and machine learning to automate and optimize IT operations. AIOps vendors provide services that ingest end-to-end logs, traces, and metrics to offer a full stack observability of IT systems. However, these data sources may contain sensitive information such as internal IP addresses, hostnames, HTTP headers, SQLs, method/argument return values, URLs, personal identifiable information (PII), or confidential business data. Therefore, data security is a crucial concern when working with AIOps vendors. In this article, we will discuss the security features offered by different vendors and how we can adopt best practices to ensure data protection and privacy.
title Guardians of Trust: Navigating Data Security in AIOps through Vendor Partnerships
topic Cryptography and Security
Artificial Intelligence
url https://arxiv.org/abs/2312.06008