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Exploring Effective Strategies for Combatting Cybercrime and Intersection of IoT, Deep Learning: Legal Standpoints on Progressive Data Analytics
Abstract
The Internet of Things (IoT) represents a network of interconnected devices that collect and exchange data, while deep learning, a subset of artificial intelligence involves algorithms that model high-level abstractions in data through neural networks. The fusion of these technologies has transformed various sectors, from healthcare and agriculture to smart cities and autonomous vehicles. However, this convergence has also created new avenues for cybercrime, posing significant challenges to data security and privacy. The combination of deep learning and the Internet of Things has resulted in new vulnerabilities that hackers may take advantage of in addition to creative uses. This chapter looks at legal approaches to enhanced data analysis as well as practical methods for fighting cybercrime in the context of new technologies. With a focus on deep learning, legal frameworks and forward-thinking solutions, this study attempts to convey a thorough knowledge of the confluence of deep learning, cybercrime, and IoT.
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