Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues. Ciphertext-policy ABE provides a scalable way of encrypting data such that the encryptor defines the attribute set that the decryptor needs to possess in order to de-crypt the ciphertext. Thus, different users are allowed to decrypt different pieces of data per […]
BACK-PROPAGATION NEURAL NETWORK LEARNING ALGORITHM FOR PRIVACY PRESERVING IN CLOUD COMPUTING
Back -Propagation is an effective method for learning neural networks and has been widely used in various applications. The accuracy of the learning result, despite other facts, is highly affected by the volume of high-quality data used for learning. As compared to learning with only local data set, collaborative learning improves the learning accuracy by […]
DECENTRALIZED DISRUPTION-TOLERANT MILITARY NETWORKS WITH SECURE DATA RETRIEVAL SCHEME USING CP-ABE
Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow nodes to communicate with each other in these extreme networking environments. Typically, when there is no end-to-end connection between a source and a destination pair, the messages from the source node may need to wait in the intermediate nodes for a substantial amount of time […]
WIRELESS AD HOC NETWORKS WITH A NOVEL NCAC-MAC PROTOCOL
Network coding is an interesting technique which can provide throughput improvements and a high degree of robustness in packet networks. Network coding is a networking technique in which transmitted data is encoded and decoded to increase network throughput, reduce delays and make the network more robust. Cooperative communication, which utilizes neighboring nodes to relay the […]
BPN LEARNING MADE PRACTICAL WITH CLOUD COMPUTING FOR PRIVACY PRESERVING
To protect each participant’s private data set and intermediate results generated during the BPN network learning process, it requires secure computation of various operations, for example, addition, scalar product, and the nonlinear sigmoid function, which are needed by the BPN network algorithm; Back -Propagation is an effective method for learning neural networks and has been […]
SYSTEMATIC AND PRACTICAL PERFORMANCE ANALYSIS FRAMEWORK USING MODELING OF DFS
Distributed File System (DFS) is a set of client and server services that allow an organization using Microsoft Windows servers to organize many distributed SMB file shares into a distributed file system. DFS provides location transparency and redundancy to improve data availability in the face of failure or heavy load by allowing shares in multiple […]
INCREASE THROUGHPUT AND REDUCE DELAY IN WIRELESS AD HOC NETWORKS USING NCAC-MAC PROTOCOL
The broadcast nature of the wireless medium (the so-called wireless broadcast advantage) is exploited in cooperative fashion. The wireless transmission between a transmitter-receiver pair can be received and processed at neighboring nodes for performance gain, rather than be considered as the interference traditionally. Network coding, which combines several packets together for transmission, is very helpful […]
Two-Phase Validation Commit Protocol for Secure Cloud Transaction
This work proposes a Two-Phase Validation Commit (2PVC) protocol that ensures that a transaction is safe by checking policy, credential, and data consistency during transaction execution. This paper defines several different levels of policy consistency constraints and corresponding enforcement approaches that guarantee the trustworthiness of transactions executing on cloud servers. 2PVC can be used to […]
RISK OF UNKNOWN VULNERABILITIES MEASUREMENT USING K-ZERO DAY SAFETY
This metric then simply counts how many zero-day vulnerabilities are required to compromise a network asset. A larger count will indicate a relatively more secure network, because the likelihood of having more unknown vulnerabilities all available at the same time, applicable to the same network, and exploitable by the same attacker, will be lower. It […]
DISTRIBUTED FILE SYSTEMS MODELING FOR SYSTEMATIC AND PRACTICAL PERFORMANCE ANALYSIS FRAMEWORK
Performance analysis is an important concern in the distributed system research area. Researchers have made a lot effort to evaluate, model, and analyze distributed systems for computing intensive or data intensive applications. There exist well-known evaluation benchmarks (e.g., LINPACK, mpiBLAST) for computing paradigms. In this paper, we propose a systematic and practical performance analysis framework, […]
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