Abstract In the cloud environment, pay-per-use is used to provide services for the end-users. With all the benefits available, a threat is present in the security of sensitive data. Users of the cloud cannot rely on cloud service providers for the security of data. In this work we present a model of cloud system that supports privacy-preserving and public auditing. The design... In the cloud environment, pay-per-use is used to provide services for the end-users. With all the benefits available, a threat is present in the security of sensitive data. Users of the cloud cannot rely on cloud service providers for the security of data. In this work we present a model of cloud system that supports privacy-preserving and public auditing. The design introduced now has three components such as data owner, cloud server, and third-party auditor (TPA). In this proposed model the data owner first encrypts the data using the Advanced Encryption Standard (AES) algorithm and applies a Steganography technique by combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) in order to hide the encrypted data and subsequently save them on a cloud server. In the next phase, the SHA-2 value is developed for the hidden file and creates a signature on it. The Third Party Auditor then next authorize the data onto the cloud instead of data owners by generating the value of the SHA-2 and create a signature on it, eventually, compares both signatures to verify the data integrity. We thus intend to produce an efficient and secure system that is capable of privacy preserving public auditing maintaining the data confidentiality and integrity. In the experimentation process, it is found that the security and performance have recorded a good level of security and found to me more efficient. Read More Read Less

Abstract In the last couple of years, the Internet of Things (IoT) is found to have increasing applications. The IoT components include smart-devices which communicate and exchange the information without the physical intervention of humans. The growth of newer models of IoT and their systems lead the devices more vulnerable and prone to a severe kind of threats. This current study... In the last couple of years, the Internet of Things (IoT) is found to have increasing applications. The IoT components include smart-devices which communicate and exchange the information without the physical intervention of humans. The growth of newer models of IoT and their systems lead the devices more vulnerable and prone to a severe kind of threats. This current study has introduced a new system capturing and verification procedures in Blockchain supported smartIoT systems that can show the trust-level confidence to outside networks. This work has a Behavior Monitor and get implemented on a selected node that can extract the activity of each device and analyzes the behavior using deep machine learning strategy. In addition, we use Trusted Execution Technology (TEE) which can provide a secure execution environment (enclave) for sensitive application code and data on blockchain. To prove the proposed model, we analyze various IoT devices data that is infected by attacks. Experimental findings prove the ability of our proposed method in terms of accuracy and time required for detection. Read More Read Less

Abstract Time is the essence of the cyber-physical system which determines the efficiency of a system. While designing the Cyber Physical Systems, the performance indicator, the Throughput is used. When analyzing throughput reachable by a CPS at design-time implies to optimize the behaviour of the system in such a way that it may run with an optimal frequency. The synchronous dataflow... Time is the essence of the cyber-physical system which determines the efficiency of a system. While designing the Cyber Physical Systems, the performance indicator, the Throughput is used. When analyzing throughput reachable by a CPS at design-time implies to optimize the behaviour of the system in such a way that it may run with an optimal frequency. The synchronous dataflow graphs can be used as a formal model of computation that fosters the analysis of systems where performance is always prominent. We in this current work describe the throughput estimation for CPS applications modeled with the SDFGs. For assessing the optimal throughput reachable by a CPS application, we use SDFGs to describe computations and communications in the CPS application and we propose a mathematical formulation of scheduling and mapping decisions in order to deploy the behavioural model of the CPS onto a platform, which essentially consists of heterogeneous and distributed resources. Read More Read Less