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Synthetic Data, Hashing, Enterprise Data Leakage, and the Reality of Privacy Risks: What to Know
Manage episode 431299434 series 3474671
This story was originally published on HackerNoon at: https://hackernoon.com/synthetic-data-hashing-enterprise-data-leakage-and-the-reality-of-privacy-risks-what-to-know.
The rise of large language models (LLMs) and generative AI creates opportunities for massive data leakage.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #privacy, #synthetic-data, #differential-privacy, #hashing, #enterprise-data, #privacy-risks, #what-is-synthetic-data, #generative-ai-risks, and more.
This story was written by: @yaw.etse. Learn more about this writer by checking @yaw.etse's about page, and for more stories, please visit hackernoon.com.
The rise of large language models (LLMs) and generative AI creates opportunities for massive data leakage. Synthetic data is often considered the convenient solution to the data privacy challenges associated with LLM training and fine-tuning. Despite the enthusiasm, it’s critical to recognize that synthetic data is not inherently anonymous.
204 episodios
Manage episode 431299434 series 3474671
This story was originally published on HackerNoon at: https://hackernoon.com/synthetic-data-hashing-enterprise-data-leakage-and-the-reality-of-privacy-risks-what-to-know.
The rise of large language models (LLMs) and generative AI creates opportunities for massive data leakage.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #privacy, #synthetic-data, #differential-privacy, #hashing, #enterprise-data, #privacy-risks, #what-is-synthetic-data, #generative-ai-risks, and more.
This story was written by: @yaw.etse. Learn more about this writer by checking @yaw.etse's about page, and for more stories, please visit hackernoon.com.
The rise of large language models (LLMs) and generative AI creates opportunities for massive data leakage. Synthetic data is often considered the convenient solution to the data privacy challenges associated with LLM training and fine-tuning. Despite the enthusiasm, it’s critical to recognize that synthetic data is not inherently anonymous.
204 episodios
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