A Proficient Mechanism for Cloud Security Supervision in Distributive Computing Environment

In the existing epoch, the cloud-IoT integrated distributive computing is earning very high attractiveness because of its immense characteristics which can be divided into two categories namely essential and common characteristics. The essential characteristics of cloud-IoT computing are demand dependent like broad network access, self-service, resource pooling, and speedy elastic nature. The common characteristics of cloud-IoT computing are homogeneity, massive scale, virtualization, resilient computing, low cost software availability, service orientation, geographic independent computation, and advanced safety availability. The cloud-IoT dependent internetworked distributive computation is internet based computation environment in which infrastructure, application software, and various similar / dissimilar platforms are accessible in the cloud and the end users (businessman, developers) have the right to use it as the client. Cloud is a step from Utility Computing and several industries / companies are frequently using cloud based systems in their day-to-day work. Therefore, safety issues and challenges of cloud computing cannot be avoided in the current era. Hence, the researchers must develop high order authentication protocols for preventing the safety threats of cloud based data communication systems.. The proposed CCMP (Counter Mode with Cipher Block Chaining Message Authentication Code Protocol) based management of cloud-IoT integrated information is a two phase authenticated encoding (AE) mechanism. The first phase is worn for executing privacy computations, and the second phase is used for computing validation and truthfulness. Here, both the cycles use same encoding technique. It is well known to us that the CCM/CCMP is an amalgamation of two forms namely AES counter form and CBC- MAC (cipher-block-chain message authentication code) protocol form. The counter form is worn to carry out encoding which guarantees data privacy whereas CBCMAC is worn to attain data legitimacy and reliability. In this investigation work the author has investigated and critically analyzed the CCMP dependent safe Cloud-IoT integrated distributive mechanism for data / information management. The proposed approach further improves the overall security and performance of cloud-IoT integrated computing networks. Further, the author has solved the challenges of cloud-IoT computing by studying and analyzing major cloud-IoT computing safety concerns, and safety threats which are expected in future generation cloud computing systems. In this paper, the author has proposed CCMP & CBC-HMAC (Cipher-Block-Chain key Hash-MessageAuthentication-Code) encoding protocol can be efficiently used for providing information safety and preventing various attacks when the data is being transferred between the Cloud and a local network. The prevention mechanism for unauthorized access of data within the cloud is also presented whose performance is highly satisfactory. A secure and flexible framework to support self-organize and self register of consumer’s information in to the cloud network is designed and tested. The testing results of proposed analysis provides us very clear evidences that the PRF of CCMP is a superior and secure in contrast to that of CBC-HMAC.

Quantification of abdominal fat from computed tomography using deep learning and its association with electronic health records in an academic biobank

Objective The objective was to develop a fully automated algorithm for abdominal fat segmentation and deploy this method at scale and associated with diagnoses in an academic biobank. Materials and Methods We built a fully automated image curation and labeling technique using deep learning and distributive computing to identify subcutaneous and visceral abdominal fat compartments from 47,587 CT scans in 13,422 patients in the Penn Medicine Biobank (PMBB). A classification network identified the inferior and superior borders of the abdomen, and a segmentation network differentiated visceral and subcutaneous fat. Following technical evaluation of our method, we conducted studies to validate known relationships with adiposity. Results When compared with 100 manually annotated cases, the classification network was on average within one 5 mm slice for both the superior (0.3±0.6 slices) and inferior (0.7±0.6 slices) borders. The segmentation network also demonstrated excellent performance with interclass correlation coefficients of 0.99 (p<2e-16) for subcutaneous and 0.99 (p<2e-16) for visceral fat on 100 testing cases. We performed integrative analyses of abdominal fat with the phenome extracted from the electronic health record and found highly significant associations with diabetes mellitus, hypertension, renal failure, among other phenotypes. Conclusion This work presents a fully automated and highly accurate method for the quantification of abdominal fat that can be applied to routine clinical imaging studies to fuel translation scientific discovery.

Data Security in Cloud Computing using Three Way Mechanism

Cloud computing is the front line innovation of the decennium. It empowers users to store enormous collection of information in distributed storage and make use of it as and when they please from any corner of the world, with any sorts of hardware. As this distributive computing is reliant on the internet facility, issues of security like privacy, security of information, authentication and data confidentiality is experienced. So as to dispose of these issues, an assortment of encryption calculations and systems are utilized. Numerous specialists pick what they discovered best and made use of these in different blends to give the security to the information in cloud. Going through a comparable circumstance, we have decided to utilize a mix of validation system and key trade calculation mixed with an encryption calculation. The blend is alluded to as a "Three way mechanism" since it guarantees all three of confirmation, information protection and inspection insurance policies. In this paper, we have proposed to utilize two-factor authentication mixed in (AES) Advanced Encryption Standard encryption calculation that secures the secrecy of information put away within cloud. Without user’s private key that is special to the user, even if the key that is moving is stolen or hijacked the feature of key exchange renders it pointless and is of no use. The given proposed engineering of three way mechanism making it tedious for unauthorized personnel to break this security framework, therefore securing information put away in cloud.

Mobile Agent and Semantic Web Based Frameworks for the Realization of Virtual Manufacturing Enterprises

In a virtual Manufacturing Enterprise (VME), the manufacturing and software resources are geographically distributed and communicate electronically using mediums such as the Internet. In such a context, there is a need to explore the design of distributive computing frameworks for the realization of VMEs. In this paper, 2 frameworks are discussed which are based on a mobile agent paradigm and the notion of a ‘semantic web’ respectively. In this paper, the first segment explores the design of such a mobile agent framework to support process planning and manufacturing activities; in the second segment of this paper, the creation of preliminary software modules as part of a ‘mini’ semantic web is described; the use of such a ‘semantic web’ based framework provides a new dimensionality of ‘meaning’, thereby enabling better cooperation and interaction between machines and humans.