Improved Outsourced Provable Data Possession for Secure Cloud Storage

With the advent of data outsourcing, how to efficiently verify the integrity of data stored at an untrusted cloud service provider (CSP) has become a significant problem in cloud storage. In 2019, Guo et al. proposed an outsourced dynamic provable data possession scheme with batch update for secure cloud storage. Although their scheme is very novel, we find that their proposal is not secure in this paper. The malicious cloud server has ability to forge the authentication labels, and thus it can forge or delete the user’s data but still provide a correct data possession proof. Based on the original protocol, we proposed an improved one for the auditing scheme, and our new protocol is effective yet resistant to attacks.

Efficient Noninteractive Outsourcing of Large-Scale QR and LU Factorizations

QR and LU factorizations are two basic mathematical methods for decomposition and dimensionality reduction of large-scale matrices. However, they are too complicated to be executed for a limited client because of big data. Outsourcing computation allows a client to delegate the tasks to a cloud server with powerful resources and therefore greatly reduces the client’s computation cost. However, the previous methods of QR and LU outsourcing factorizations need multiple interactions between the client and cloud server or have low accuracy and efficiency in large-scale matrix applications. In this paper, we propose a noninteractive and efficient outsourcing algorithm of large-scale QR and LU factorizations. The proposed scheme is based on the specific perturbation method including a series of consecutive and sparse matrices, which can be used to protect the original matrix and obtain the results of factorizations. The generation and inversion of sparse matrix has small workloads on the client’s side, and the communication cost is also small since the client does not need to interact with the cloud server in the outsourcing algorithms. Moreover, the client can verify the outsourcing result with a probability of approximated to 1. The experimental results manifest that as for the client, the proposed algorithms reduce the computational overhead of direct computation successfully, and it is most efficient compare with the previous ones.

Biometric Based User Authentication and Privacy Preserving In Cloud Environment

Cloud technology provides advantage of storage services for individuals and organizations thus making file access easy and simple irrespective of location. The major concern is the security while the file is been outsourced. Maintaining integrity, file unchanged, gaining confidentiality during file outsourced plays an important role. In this paper, we propose identity based data outsourcing technique to provide data security during authorization and storage. For data authorization we propose finger print based authentication. The fingerprint based authentication is performed using Minutae Map algorithm (MM). For data security we convert the data owner files to hash values using SHA algorithm. Finally in the cloud storage stage, data security and data availability is addressed using multiple cloud storage system.

Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario

The arrival of cloud computing age makes data outsourcing an important and convenient application. More and more individuals and organizations outsource large amounts of graph data to the cloud computing platform (CCP) for the sake of saving cost. As the server on CCP is not completely honest and trustworthy, the outsourcing graph data are usually encrypted before they are sent to CCP. The optimal route finding on graph data is a popular operation which is frequently used in many fields. The optimal route finding with support for semantic search has stronger query capabilities, and a consumer can use similar words of graph vertices as query terms to implement optimal route finding. Due to encrypting the outsourcing graph data before they are sent to CCP, it is not easy for data customers to manipulate and further use the encrypted graph data. In this paper, we present a solution to execute privacy-guarding optimal route finding with support for semantic search on the encrypted graph in the cloud computing scenario (PORF). We designed a scheme by building secure query index to implement optimal route finding with support for semantic search based on searchable encryption idea and stemmer mechanism. We give formal security analysis for our scheme. We also analyze the efficiency of our scheme through the experimental evaluation.

INVENTARISASI NASKAH DAN ANALISIS PENOKOHAN NASKAH HIKAYAT AMIR HAMZAH

Indonesia has many manuscripts that cannot stand the time and are susceptible to temperature changes, making it easy to be damaged or rotten. These are the reasons why it is necessary to arrange an arbitration and research upon these texts. One of the manuscripts that exist in the archipelago treasury is Hikayat Amir Hamzah, which contains a nuanced of the Islamic religion. This manuscript consists of the story of the heroism of Amir Hamzah who often fought to defend Islam. This paper aims to inventory the manuscripts so that the number of these manuscripts is acknowledged, presented the text editing, and the analysis of the characterization of Amir Hamzah. The method used in this research is descriptive method and literature review. The research steps undertaken include data searching, data outsourcing, and data analysis. There are sixteen manuscripts of ofHikayat Amir Hamzah. This does not include the texts that have not been recorded and listed in the catalog. There are many events related to Islamic values in this text, in the form of teaching and example given, such as the advice that reminds us to be sincere, not to betray, arrogant, ripple, and forget the greatness of Allah.