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This paper presents a survey on Proxy re-encryption techniques with respect to secure cloud data and its application. To keep sensitive user data confidential against untrusted servers, cryptographic methods are used to provide security and access control in clouds. As the data is shared over the network, it is needed to be encrypted. There are many encryption schemes that provide security and access control over the network.Proxy re-encryption enables the semi-trusted proxy server to re-encrypt the ciphertext encrypted under Alice's public key to another ciphertext encrypted under Bob's public key. The re-encryption is done without the server being able to decrypt the ciphertext.Cloud services and applications should follow the standard security measures including data confidentiality, integrity,privacy, robustness and access control.In this paper the proxy re-encryption(PRE) schemes, Conditional PRE,Identity based PRE and Broadcast PRE,Type based PRE, Key private PRE,Attribute based PRE,Threshold PRE and its role in securing the cloud data are explained.

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Target object detection in aerial surveillance using image processing techniques is growing more and more important. Aerial surveillance is more suitable for monitoring fast moving targets and covers a much larger spatial area. These technologies have a variety of applications, such as traffic management, police and military. Aerial view has the advantage of providing a better perspective of the area being covered and this make use of the aerial videos taken from aerial vehicles. In an automatic vehicle detection system for aerial surveillance background colors are eliminated and then features are extracted. This system extracts features including color feature and local feature points. For vehicle color extraction, system utilizes color transform to separate vehicle colors and non-vehicle colors effectively. For edges detection, system applies moment-preserving method to adjust the thresholds for canny edge detector automatically, which improves the adaptability and accuracy of the system. A support Vector Machine is constructed for classification purpose.