Varnost poslovnih podatkov pri implementaciji inteligentnega sistema ChatGPT

diplomsko delo

Marija Koleva (Author), Mirjana Kljajić Borštnar (Mentor)

Abstract

Namen diplomske naloge je bil raziskati implementacijo in uporabo generativnih modelov, predvsem modelov generative pre-trained transformer (GPT), v poslovnem okolju podjetja X in razumeti njihov vpliv na poslovne procese. S poudarkom na varnosti in produktivnosti smo preučili prednosti in izzive integracije teh tehnologij ter opredelili ključne ugotovitve, ki vključujejo izboljšano učinkovitost, inovativnost, kakovost storitev in varnost podatkov. Uporabljene metode vključujejo študijo primera, intervju z vodjo projekta, analizo podatkov in pregled literature. Glavni zaključki vključujejo poudarek na potrebi po implementaciji varnostnih protokolov, upoštevanju etičnih vidikov in implementaciji najboljših praks pri implementaciji generativnih modelov. Priporočila vključujejo uporabo robustnih varnostnih mehanizmov, optimizacijo poslovnih procesov in nadaljnje raziskovanje možnosti uporabe generativnih modelov v poslovnem okolju.

Keywords

generativni modeli;GPT;poslovno okolje;varnost;produktivnost;

Data

Language:	Slovenian
Year of publishing:	2024
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FOV - Faculty of Organizational Sciences
Publisher:	[M. Koleva]
UDC:	004.9
COBISS:	210103043
Views:	0
Downloads:	1
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Other data

Secondary language:	English
Secondary title:	Business data security in the implementation of chatgpt enterprise
Secondary abstract:	The aim of the thesis was to investigate the implementation and use of generative models, especially generative pre-trained transformer (GPT) models, in the business environment of Company X and to understand their impact on business processes. With a focus on security and productivity, we examined the benefits and challenges of integrating these technologies and identified key findings that include improved efficiency, innovation, quality of service and data security. Methods used include case study, project manager interviews, data analysis and literature review. The main conclusions include an emphasis on the need to implement security protocols, to consider ethical aspects and to implement best practices in the implementation of generative models. Recommendations include the use of robust security mechanisms, optimization of business processes, and further exploration of the possibility of using generative models in a business environment.
Secondary keywords:	Umetna inteligenca;Varstvo podatkov (računalništvo);Univerzitetna in visokošolska dela;
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za organizacijske vede
Pages:	VI, 49 f.
ID:	24820643