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Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems.

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In today’s environment, an enormous amount of unstructured data is generated in an exponential manner. Understanding such complex unstructured data is imperative in the applications including analysis of social media data, image and video data, sensor data, medical data, and customer review data. Generally, clustering is a well-accepted model in classifying and analyzing such documents. An effective and efficient text clustering technique can significantly improve the task of document analysis and grouping with minimum human intervention. The main two factors in text clustering are the text representation model and the clustering algorithm. Firstly, unstructured data must be represented in a structured format for the analysis. Text representation models transform a large volume of text into vector representations by capturing the semantic information. In this paper, we are investigating the text document representation techniques, their limitations, and how text clustering is different from humans understanding of the text data. In this paper, we are aiming to focus on different text representation methods and clustering algorithms to demonstrate how the choice of representation techniques can impact on clustering results.

The popularity of steganography in the data exfiltration of private corporate sensitive data is increased. So it is important to detect such malicious activity. Becausethe data being transferred can hide the large amount of data in video becoming increasingly attractive. To ensure privacy and security we proposed an effective steganalysis method to detect hidden data in video by using the SDN framework policy. The main objective of this paper is to prevent the illegal data transmission from the compromised private network by the malicious users.

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Applying steganography for the images like JPEG is not straight forward process due to its lossy compression. The objective of this paper is to carry out a brief research on steganography. Based on the research findings, develop and implement a steganographic application to hide data in a computer image file, as well as retrieve the hidden data from the image containing the hidden data and improving the hiding capacity by encrypting and compressing the data.

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