Cloud computing is a new paradigm in this new cyber era. Nowadays, most organizations are showing more reliability in this environment. The increasing reliability of the Cloud also makes it vulnerable. As vulnerability increases, there will be a greater need for privacy in terms of data, and utilizing secure services is highly recommended. So, data on the Cloud must have some privacy mechanisms to ensure personal and organizational privacy. So, for this, we must have an authentic way to increase the trust and reliability of the organization and individuals The authors have tried to create a way to rank things that uses the Analytical Hieratical Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). Based on the result and comparison, produce some hidden advantages named cost, benefit, risk and opportunity-based outcomes of the result.In this paper, we are developing a cloud data privacy model; for this, we have done an intensive literature review by including Privacy factors such as Access Control, Authentication, Authorization, Trustworthiness, Confidentiality, Integrity, and Availability. Based on that review, we have chosen a few parameters that affect cloud data privacy in all the phases of the data life cycle. Most of the already available methods must be revised per the industry’s current trends. Here, we will use Analytical Hieratical Process and Technique for Order Preference by Similarity to the Ideal Solution method to prove that our claim is better than other cloud data privacy models. In this paper, the author has selected the weights of the individual cloud data privacy criteria and further calculated the rank of individual data privacy criteria using the AHP method and subsequently utilized the final weights as input of the TOPSIS method to rank the cloud data privacy criteria.

To measure testability before the actual development starts will play a crucial role to the developer, designers and end users as well. Early measurement of testability, especially in early requirement stage to assist the developer for the further development process, and will also assures us to produce and deliver the high quality requirement that can surely reduce the overall cost and improves the quality of development process. Taking view of this fact, this paper identifies testability estimation factors namely understandability and modifiability and establishes the correlation among testability, understandability and modifiability. Further, a model is developed to quantify software testability in requirement phase and named as Requirement Testability Model of Object Oriented Software-RTMOOS. Furthermore, the correlation of Testability with these factors has been tested and justified with the help of statistical measures.

As the Internet of Things (IoT) has expanded rapidly, many devices are now connected and exchanging large volumes of data. Current intrusion detection syst