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Nagamani, T.
- Efficient Search over Encrypted Mobile Cloud Using TEES
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
2 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
3 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
Source
Networking and Communication Engineering, Vol 8, No 2 (2016), Pagination: 39-42Abstract
Cloud storage gives us huge amount of storage at a feasible cost. The major problem is there is no security for the data which is stored in the cloud [1]. The solution for this problem is the administrator should encrypt the file before it is stored in the cloud and after retrieving the file from the cloud the user should decrypt and use it. This increases work load for the computing and the communication as there is only particular bandwidth and battery life. Due to this issue the searching of the encrypt file will be difficult. So in this paper we introduce Traffic and Energy saving Encrypted Search (TEES) [2]. This system will use the bandwidth and the energy in a proper way and hence it decreases the workload of computing by 23 % to 46% and the consumption of energy by 35% to 55% for a file download. It also decreases the traffic in the network during the decrypted file download from the cloud.
Keywords
Traffic and Energy saving Encryption Search, Boolean Search, Order Preserving Encryption, Authentication.
- Camera Shake Elimination Using Weighted Fourier Burst Accumulation
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
2 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
Source
Digital Image Processing, Vol 8, No 2 (2016), Pagination: 35-44Abstract
Camera shakes during exposure leads to objectionable image blur and ruins many photographs.If the photographer takes a lots of images, a modality available in virtually all modern digital cameras, we show that it is possible to combine the images to get a clear sharp version. This is done without explicitly solving any blur estimation and subsequent inverse problem. In previous method they have used blind de-convolution algorithm. Most blind de-convolution algorithms try to estimate the latent image without any other input than the noisy blurred image itself. In our proposed system we implement the new method called Fourier Burst Accumulation. It performs a weighted average in the Fourier domain, with weights depending on the Fourier spectrum magnitude. We directly compute the corresponding Fourier transforms. Since camera shake motion kernels have a small spatial support, their Fourier spectrum magnitudes vary very smoothly. Thus, can apply low pass filter before computing the weights, with filter of standard deviation σ. The strength of the low pass filter (controlled by the parameter σ) should depend on the assumed kernel size (the smaller the kernel the more regular its Fourier spectrum magnitude). Although this low pass filter is important, the results are not too sensitive to the value of σ. The final Fourier burst aggregation is (note that the smoothing is only applied to the weights calculation).The extension to color images is straightforward. The accumulation is done channel by channel using the same Fourier weights for all channels. Then the weights are computed by arithmetically averaging the Fourier magnitude of the channels before the low pass filtering.
Keywords
SIFT, FFT, CCD, HSV.- Effective Identification of Malicious Threats and Security Issues in Android Apps
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
Source
Automation and Autonomous Systems, Vol 8, No 2 (2016), Pagination: 31-33Abstract
The Mobile phones are used world widely, the day without mobile phone is imaginary now-a-days. The consequence of using App is security. In order to avoid security problem, we use three methods:user review, user rating, online feedback. In Online feedback we use url to represent the security level. There are three levels of risk:high, low, medium. User rating and user review are taken as input and online feedback are produced as result.Keywords
Risk Communication, Usability, Mobile Security.- Identifying and Ranking Risk Using Probabilistic Generative Models
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 8, No 2 (2016), Pagination: 43-45Abstract
The world has been changed to Smart Phone World, therefore more issues also been developed. One of the main advantage of smart phone is "Apps" .But without any knowledge user installs the app, hence it results in threats. So to avoid this lots of technique have been evolved .But none give the best solution. Therefore, this will be reduced by using the Probabilistic Generative Method. Hence, this method reduces the risk problem gradually.Keywords
App Security, Low Risk App, Risk Level, Datasets.- Multikeyword Ranked Search over Cloud Data
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
2 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 9, No 2 (2017), Pagination: 21-24Abstract
For greater flexibility, from local to commercial public cloud, data owners are stimulated to farm out their complex data management systems in cloud. Before outsourcing, Sensitive data has to be encrypted to protect data privacy which obsoletes traditional data exploitation based on plaintext keyword search. Thus, the main objective is enabling an encrypted cloud data search service. So, it is very important to allow multi-keyword query for the search service, while considering the large number of data users and documents in cloud, thus cloud computing is the long dreamed vision of computing as a utility, where cloud customers can vaguely store their data into the cloud so as to enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources. Similarity ranking to meet the efficient data retrieval need. Related works are mainly focus on single keyword search or Boolean keyword search, and seldom differentiate the search results. Here, it is proposed a basic MRSE scheme using secure inner product computation, and then radically improve it by getting the different privacy requirements.Keywords
Boolean Keyword, Cloud, Coordinate Matching, Encryption, Keyword Search, Information Retrieval, Ranked Search.- A Survey on Disease Prediction from Healthcare Communities over Big Data
Authors
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, IN
Source
Biometrics and Bioinformatics, Vol 10, No 1 (2018), Pagination: 1-5Abstract
Data mining is the process of extracting hidden interesting patterns from massive database. Medical domain contains heterogeneous data in the form of text, numbers and images that can be mined properly to provide variety of useful information for the physicians. The patterns obtained from the medical data can be useful for the physicians to detect diseases, predict the survivability of the patients after disease, severity of diseases etc. The main aim of this paper is to analyse the application of data mining in medical domain and some of the techniques used in disease prediction.Medical datasets are often categorized by huge amount of disease measurements and comparatively small amount of patient records. These measurements (feature selection) are not relevant, where this irrelevant and redundancy features are difficult to evaluate. On the other hand, the large number of features may cause the problem of memory storage in order to represent the data set. Different kinds of machine learning algorithms can convenient with imprecision and uncertainty in data analysis and can effectively remove impurities and failure information.Keywords
Machine Learning, Accuracy, Datasets Datamining, Disease Prediction.References
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