A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact
Deepfake refers to synthetic media generated through artificial intelligence (AI) techniques. It involves creating or altering video, audio, or images to make them appear as though they depict something or someone else. Deepfake technology advances just like the mechanisms that are used to detect th...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-01-01
|
| Series: | Cyber Security and Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772918424000067 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846170001021599744 |
|---|---|
| author | Mohammad Wazid Amit Kumar Mishra Noor Mohd Ashok Kumar Das |
| author_facet | Mohammad Wazid Amit Kumar Mishra Noor Mohd Ashok Kumar Das |
| author_sort | Mohammad Wazid |
| collection | DOAJ |
| description | Deepfake refers to synthetic media generated through artificial intelligence (AI) techniques. It involves creating or altering video, audio, or images to make them appear as though they depict something or someone else. Deepfake technology advances just like the mechanisms that are used to detect them. There’s an ongoing cat-and-mouse game between creators of deepfakes and those developing detection methods. As the technology that underpins deepfakes continues to improve, we are obligated to confront the repercussions that it will have on society. The introduction of educational initiatives, regulatory frameworks, technical solutions, and ethical concerns are all potential avenues via which this matter can be addressed. Multiple approaches need to be combined to identify deepfakes effectively. Detecting deepfakes can be challenging due to their increasingly sophisticated nature, but several methods and techniques are being developed to identify them. Mitigating the negative impact of deepfakes involves a combination of technological advancements, awareness, and policy measures. In this paper, we propose a secure deepfake mitigation framework. We have also provided a security analysis of the proposed framework via the Scyhter tool-based formal security verification. It proves that the proposed framework is secure against various cyber attacks. We also discuss the societal impact of deepfake events along with its detection process. Then some AI models, which are used for creating and detecting the deepfake events, are highlighted. Ultimately, we provide the practical implementation of the proposed framework to observe its functioning in a real-world scenario. |
| format | Article |
| id | doaj-art-3b22a9f7afb84c0fb21eaf9389071a05 |
| institution | Kabale University |
| issn | 2772-9184 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Cyber Security and Applications |
| spelling | doaj-art-3b22a9f7afb84c0fb21eaf9389071a052024-11-12T05:21:59ZengKeAi Communications Co., Ltd.Cyber Security and Applications2772-91842024-01-012100040A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal ImpactMohammad Wazid0Amit Kumar Mishra1Noor Mohd2Ashok Kumar Das3Corresponding author.; Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248 002, IndiaDepartment of Computer Science and Engineering, Graphic Era Hill University, Dehradun 248 002, IndiaDepartment of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248 002, IndiaCenter for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad 500 032, IndiaDeepfake refers to synthetic media generated through artificial intelligence (AI) techniques. It involves creating or altering video, audio, or images to make them appear as though they depict something or someone else. Deepfake technology advances just like the mechanisms that are used to detect them. There’s an ongoing cat-and-mouse game between creators of deepfakes and those developing detection methods. As the technology that underpins deepfakes continues to improve, we are obligated to confront the repercussions that it will have on society. The introduction of educational initiatives, regulatory frameworks, technical solutions, and ethical concerns are all potential avenues via which this matter can be addressed. Multiple approaches need to be combined to identify deepfakes effectively. Detecting deepfakes can be challenging due to their increasingly sophisticated nature, but several methods and techniques are being developed to identify them. Mitigating the negative impact of deepfakes involves a combination of technological advancements, awareness, and policy measures. In this paper, we propose a secure deepfake mitigation framework. We have also provided a security analysis of the proposed framework via the Scyhter tool-based formal security verification. It proves that the proposed framework is secure against various cyber attacks. We also discuss the societal impact of deepfake events along with its detection process. Then some AI models, which are used for creating and detecting the deepfake events, are highlighted. Ultimately, we provide the practical implementation of the proposed framework to observe its functioning in a real-world scenario.http://www.sciencedirect.com/science/article/pii/S2772918424000067DeepfakeArtificial Intelligence (AI)Machine learningCyber securityAuthentication |
| spellingShingle | Mohammad Wazid Amit Kumar Mishra Noor Mohd Ashok Kumar Das A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact Cyber Security and Applications Deepfake Artificial Intelligence (AI) Machine learning Cyber security Authentication |
| title | A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact |
| title_full | A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact |
| title_fullStr | A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact |
| title_full_unstemmed | A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact |
| title_short | A Secure Deepfake Mitigation Framework: Architecture, Issues, Challenges, and Societal Impact |
| title_sort | secure deepfake mitigation framework architecture issues challenges and societal impact |
| topic | Deepfake Artificial Intelligence (AI) Machine learning Cyber security Authentication |
| url | http://www.sciencedirect.com/science/article/pii/S2772918424000067 |
| work_keys_str_mv | AT mohammadwazid asecuredeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT amitkumarmishra asecuredeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT noormohd asecuredeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT ashokkumardas asecuredeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT mohammadwazid securedeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT amitkumarmishra securedeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT noormohd securedeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact AT ashokkumardas securedeepfakemitigationframeworkarchitectureissueschallengesandsocietalimpact |