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Artificial Intelligence Based Authentication for Mobile Device

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Document pages: 20 pages

Abstract: In the real world, providing authentication is the challenging task for the developers. Because the attackers came up with the latest patches for the software, that has been developed by the software developers. There is so many ways to protect our mobile device like third-party applications, blocking the unknown users, providing authentication for the authorized users, finding the unauthorized that are requesting permission from mobile device without user’s knowledge. The attackers are creating the third-party application and that has been launched in online. Attackers are sharing that download links in different ways to the targeted mobile devices through social media, SMS. Once if we installing that application in our mobile device, automatically they’re gaining the access on that particular device. Intelligence based Decision making is useful to overcome the unauthorized access on our mobile device. Now-a- days Artificial Intelligence will play a key role in various applications to make our work in efficient and effective manner by reducing the manpower in most of the industries. In this analysis, we are enhancing the details of the artificial intelligence for authentication on mobile device. Our study is actuated by 3 key observations of today’s web threat: (1) the overwhelming majority of on-line square measure threat, (2) a threat request must always belong to some campaign, (3) threat from identical campaign square measure generated from some guide that obfuscates some elements of the threat, e.g., sensitive terms, departure alternative elements unchanged. We tend to gift the look of an internet, unattended threat learning and detection schema. Like Threat campaign Assassin (TCA), suggesting that unattended threat filtering holds high promise in battling today’s web threat.

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