Social networking and growing popularity of cloud services have made everyone to communicate each other in an easiest way. File sharing and distribution are the frequently used services provided by cloud service providers, although these facilities reduce cost of data sharing but at the same time data security and access control is the major problem. Many renowned service providers have faced the challenges to secure data and provide better access control, and we know once the data is leaked we cannot recover the data loss. Thus in order to ensure better security we need for focus on the two major problems, and those are access control and encryption policy. Cipher text policy attribute based encryption is the most effective solution for access control in real time scenarios where owner can actually decide the access rights for the end-user, but it comes with key escrow problem. We are proposing our modified escrow-free key issuing protocol to solve the problem of key escrow and our Modified Attribute Based Encryption scheme to achieve all security requirements to get a robust and secure system. Further we evaluate our model on the basis of results and lastly we conclude the paper.

Energy saving and improve the life time of the sensor node is main focus in the recent years for the researchers hence one of the application domain (Street light monitoring and controlling) of sensor required attention towards this direction. For contributing in this domain we have proposed a scheme for Street light controlling using distributed topology control (TC). The optimize version of A3 protocol reduces the number of messages send/received by the sensors which ultimately leads to the reduction of energy requirement. Experiments are carried on street light scenario for different no. of nodes by maintaining communication using Zigbee protocol. The performance of our extension is evaluated using, no. of messages send/receive & energy consumed during topology building and our approach is having good results as compared to the approach used for this type of network.

Manually examine the blood smear for the detection of malaria parasite consumes lot of time for trend pathologists. As the computational power increases, the role of automatic visual inspection becomes more important. An automated system is therefore needed to complete as much work as possible for the identification of malaria parasites. The given scheme based on used of RGB color space, G layer processing, and segmentation of Red Blood Cells (RBC) as well as cell parasites by auto-thresholding with offset value and use of morphological processing. The work compare with the manual results obtained from the pathology lab, based on total RBC count and cells parasite count. The designed system successfully detects malaria parasites and RBC cells in thin smear image.