IT Security Guru
JUNE 11, 2024
Advancements in Artificial Intelligence (AI) and Machine Learning (ML) have lowered the barrier of entry for non-security users to independently develop and manage their own data products, which when decentralised to enable separate cross domain data analysis is known as ‘data mesh’.
The Last Watchdog
JUNE 3, 2022
“The trend that we’re seeing is that more than 30 percent of the content flowing into data lakes is from untrusted sources,” he says. “It’s It’s documents, PDFs, CSV files, Excel files, images, lots of unstructured data; we track 150 different file types. This is the dark side of digital transformation.
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Security Affairs
MARCH 8, 2024
Government experts discovered sensitive information, including personal data, technical information, classified details, and passwords, in approximately half of the Federal Administration’s files (5,182). “On August, the Government launched an administrative investigation into the data breach. .”
Security Affairs
SEPTEMBER 4, 2023
Object Storage is a data storage architecture for storing unstructured data into units called “objects” and storing them in a structurally flat data environment. The leading providers of such services are AWS, Google Cloud, and Microsoft Azure.
SecureWorld News
APRIL 30, 2023
With the increase in the complexity of IT infrastructures and the various ways of storing data, safeguarding against data leaks has become more resource-intensive. Data access control raises many questions not only among users but sometimes also among security professionals. Who is the protentional customer of such solutions?
SecureWorld News
APRIL 3, 2023
This problem becomes even more pronounced when dealing with vast amounts of data. The difference between Security Data Lake and Data Lake Corporate Data Lakes usually store unstructured data, including details about the company's products, financial metrics, customer data, marketing materials, etc.
CyberSecurity Insiders
NOVEMBER 7, 2022
But on-premises processing power against “unstructured” data was still quite slow, so it could take eons to query your essentially raw data and get any semblance of an answer about the root cause of an alert, security incident, or otherwise. Phase 3: SIEM met UEBA, aka anomaly detection.
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