M. Elhoseny, A. Darwiesh, A. El-Baz, Joel J. P. C. Rodrigues
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Enhancing Cryptocurrency Security using AI Risk Management Model
With the help of social media indicators, this study offers a brand-new intelligent risk management model to enhance the security of cryptocurrency. Based on surveying the previous studies, we found most of them focused on employing many techniques to enhance virtual currencies' security. However, there is no study concentrated on mining threats depending on investors' perceptions. These perceptions can give us a clear overview about the critical risks and threats. This model employs natural language processing techniques to perform risk analysis for the interactions of users on social media platforms. Additionally, a case study on investors of virtual currencies in the USA is presented where the findings of the obtained results refer to almost a quarter of the sample includes risk indications that can be classified as not only technological risks but also financial, operational, and geopolitical risks. Furthermore, performance metrics are calculated to show the new model's capabilities such that the mean accuracy for risk analysis, risk identification, and risk assessment is 77%.
期刊介绍:
The scope will cover the following areas that are related to “consumer electronics” and other topics considered of interest to consumer electronics: Video technology, Audio technology, White goods, Home care products, Mobile communications, Gaming, Air care products, Home medical devices, Fitness devices, Home automation & networking devices, Consumer solar technology, Home theater, Digital imaging, In Vehicle technology, Wireless technology, Cable & satellite technology, Home security, Domestic lighting, Human interface, Artificial intelligence, Home computing, Video Technology, Consumer storage technology.