Abstract
Fake digital content disseminated over the internet has been posing a great challenge for the various social media platforms and real-world applications. The technological advancement has facilitated the generation of such content, such that differentiating between fake and factual content has become ever more challenging. One such emerging technology, known as deepfake, can create some new hyper-realistic but fraudlent material that cannot be easily captured by human eyes and seems utmost realistic. The technology relies on AI and its subsets, namely machine learning, and deep learning. It is pertinent to note that the research in this direction is meager and there is an instant need for novel approaches that can reliably discriminate between genuine and fake multimedia content. The current paper aims to review the deepfake technology along with its associated threats, challenges, and future directions that can help cope with fake information circulated online. The accuracy and robustness of available methods for detecting such fake videos based on the available two generations of datasets are deliberated. Constructive criticism is presented that also highlights some of its useful applications for the digital society.
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Sharma, M., Kaur, M. (2022). A Review of Deepfake Technology: An Emerging AI Threat. In: Ranganathan, G., Fernando, X., Shi, F., El Allioui, Y. (eds) Soft Computing for Security Applications . Advances in Intelligent Systems and Computing, vol 1397. Springer, Singapore. https://doi.org/10.1007/978-981-16-5301-8_44
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