Dark Side of Big Data: When information becomes a Weapon Big data is rapidly transforming decision-making and cybersecurity, but the increasing use of AI tools, fake videos, and large-scale attacks is creating new risks to data systems. In real time, threats are detected by machine learning. However, strict regulatory measures and enhanced data protection measures are necessary to secure privacy, security, and public trust.

Abstract

The big data is getting bigger and bigger. This has changed the way we collect, store, and analyze information. Big data is really changing how we make decisions in various areas. It helps us come up with ideas and things, but big data also makes it easier for people to try to hack into our systems and steal our information. Big data is a problem when it comes to keeping our information safe from cyber threats.

Conventional attack systems usually struggle to handle this scale and data speed, requiring modern methods like machine learning to identify odd patterns and indicators of threats in real time. For example, distributed denial-of-service attacks primarily target big data frameworks, exploiting their complexity and distribution to cause a common breakdown. Random forest classifiers are machine learning models to upgrade the detection of such attacks by effectively checking shared continuous data flow.