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Assessing Security and Privacy Concerns in LLM Applications: Legal and Social Concerns
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Author(s): Bhupinder Singh (Sharda University, India), Arunima Shastri (Christ University, Bangalore, India)and Saurabh Chandra (Bennett University, Greater Noida, India)
Copyright: 2026
Pages: 24
Source title:
Theory, Practice, and Future Direction of Large Language Models
Source Author(s)/Editor(s): Ismail Lamaakal (University Mohammed Premier, Morocco), Yassine Maleh (Sultan Moulay Slimane University, Morocco), Khalid El Makkaoui (University Mohammed Premier, Morocco), Ibrahim Ouahbi (University Mohammed Premier, Morocco)and Ahmed Abd El-Latif (Prince Sultan University, Saudi Arabia)
DOI: 10.4018/979-8-3693-8387-2.ch008
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Abstract
Large language models (LLMs) like Open AI's GPT-4 have transformed many industries, including natural language processing. But, still the applications of these need a properly secure mechanism as it is getting attached to everyday technology at on an extensive rate and large security & privacy risk are encapsulated in its use which must be controlled for safe and ethical use. LLM models are trained with an avalanche of data, often from web-scraped sources that could be handling personal and sensitive content. This may inadvertently have the LAZ model hold on to, and possibly leak, some private data of users who use the API. Having measures to address them through comprehensive strategies and conforming with regulations are important in the responsible usage of LLM applications.
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