A Spatialization-based Method for Checking and Updating Metadata

In this paper the application of spatialization technology on metadata quality check and updating was dis-cussed. A new method based on spatialization was proposed for checking and updating metadata to overcome the defi-ciency of text based methods with the powerful functions of spatial query and analysis provided by GIS software. Thismethod employs the technology of spatialization to transform metadata into a coordinate space and the functions ofspatial analysis in GIS to check and update spatial metadata in a visual environment. The basic principle and technicalflow of this method were explained in detail, and an example of implementation using ArcMap of GIS software wasillustrated with a metadata set of digital raster maps. The result shows the new method with the support of interactionof graph and text is much more intuitive and convenient than the ordinary text based method, and can fully utilize thefunctions of GIS spatial query and analysis with more accuracy and efficiency.

Developing a Geological Management Information System: National Important Mining Zone Database

Geo-data is a foundation for the prediction and assessment of ore resources, so managing and making full use of those data, including geography database, geology database, mineral deposits database, aeromagnetics database, gravity database, geochemistry database and remote sensing database, is very significant. We developed national important mining zone database （NIMZDB） to manage 14 national important mining zone databases to support a new round prediction of ore deposit. We found that attention should be paid to the following issues： ① data accuracy： integrity, logic consistency, attribute, spatial and time accuracy; ② management of both attribute and spatial data in the same system;③ transforming data between MapGIS and ArcGIS; ④ data sharing and security; ⑤ data searches that can query both attribute and spatial data. Accuracy of input data is guaranteed and the search, analysis and translation of data between MapGIS and ArcGIS has been made convenient via the development of a checking data module and a managing data module based on MapGIS and ArcGIS. Using AreSDE, we based data sharing on a client/server system, and attribute and spatial data are also managed in the same system.

Towards Public Integrity Audition for Cloud-IoT Data Based on Blockchain

With the rapidly developing of Internet of Things (IoT), the volume ofdata generated by IoT systems is increasing quickly. To release the pressure ofdata management and storage, more and more enterprises and individuals preferto integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted,a variety of methods have been proposed to deal with the problem of data integritychecking. In traditional data integrity audition schemes, the task of data auditing isusually performed by Third Party Auditor (TPA) which is assumed to be trustful.However, in real-life TPA is not trusted as people thought. Therefore, theseschemes suffer from the underlying problem of single-point failure. Moreover,most of the traditional schemes are designed by RSA or bilinear map techniqueswhich consume heavy computation and communication cost. To overcome theseshortcomings, we propose a novel data integrity checking scheme for cloud-IoTdata based on blockchain technique and homomorphic hash. In our scheme, thetags of all data blocks are computed by a homomorphic hash function and storedin blockchain. Moreover, each step within the process of data integrity checking issigned by the performer, and the signatures are stored in blockchain through smartcontracts. As a result, each behavior for data integrity checking in our scheme canbe traced and audited which improves the security of the scheme greatly. Furthermore, batch-audition for multiple data challenges is also supported in our scheme.We formalize the system model of our scheme and give the concrete construction.Detailed performance analyses demonstrate that our proposed scheme is efficientand practical without the trust-assumption of TPA.

A Data Transmission Method Using a Cyclic Redundancy Check and Inaudible Frequencies

This paper describes a data transmission method using a cyclic redundancy check and inaudible frequencies.The proposed method uses inaudible high frequencies from 18 k Hz to 22 k Hz generated via the inner speaker of smart devices.Using the proposed method,the performance is evaluated by conducting data transmission tests between a smart book and smart phone.The test results confirm that the proposed method can send 32 bits of data in an average of 235 ms,the transmission success rate reaches 99.47%,and the error detection rate of the cyclic redundancy check is0.53%.

ID-Based Public Auditing Protocol for Cloud Storage Data Integrity Checking with Strengthened Authentication and Security

Cloud storage service reduces the burden of data users by storing users＇ data files in the cloud. But, the files might be modified in the cloud. So, data users hope to check data files integrity periodically. In a public auditing protocol, there is a trusted auditor who has certain ability to help users to check the integrity of data files. With the advantages of no public key management and verification, researchers focus on public auditing protocol in ID-based cryptography recently. However, some existing protocols are vulnerable to forgery attack. In this paper, based on ID-based signature technology, by strengthening information authentication and the computing power of the auditor, we propose an ID-based public auditing protocol for cloud data integrity checking. We also prove that the proposed protocol is secure in the random oracle model under the assumption that the Diffie-Hellman problem is hard. Furthermore, we compare the proposed protocol with other two ID-based auditing protocols in security features, communication efficiency and computation cost. The comparisons show that the proposed protocol satisfies more security features with lower computation cost.

DTrace: fine-grained and efficient data integrity checking with hardware instruction tracing

Recently released Intel processors have been equipped with hardware instruction tracing facilities to securely and efficiently record the program execution path.In this paper,we study a case for data integrity checking based on Intel Processor Trace(Intel PT),the instruction tracing facility on x86 processors.We incorporate software instrumentation and hardware instruction tracing to guarantee fine-grained data integrity without frequently switching the processor mode.We incorporate the idea in a system named DTrace which provides primitives to instruct Intel PT to capture the data load and store events,even current Intel PT implementations only record control transfers.The trace is analyzed before the program makes security-sensitive operations.We apply DTrace in several case studies to show that the primitives that DTrace provides are easy to use and help to enhance data integrity in applications.We further evaluate DTrace with several microbenchmarks to show the time cost that DTrace’s data tracing operation incurs.We also evaluate DTrace on Nginx to show the performance impact when Nginx is enhanced in security to provide the integrity during the runtime execution for programmer-defined security sensitive data.We find the performance overhead that DTrace incurs for the data tracing is moderate.

DTrace:fine-grained and efficient data integrity checking with hardware instruction tracing

Recently released Intel processors have been equipped with hardware instruction tracing facilities to securely and efficiently record the program execution path.In this paper,we study a case for data integrity checking based on Intel Processor Trace(Intel PT),the instruction tracing facility on x86 processors.We incorporate software instrumentation and hardware instruction tracing to guarantee fine-grained data integrity without frequently switching the processor mode.We incorporate the idea in a system named DTrace which provides primitives to instruct Intel PT to capture the data load and store events,even current Intel PT implementations only record control transfers.The trace is analyzed before the program makes security-sensitive operations.We apply DTrace in several case studies to show that the primitives that DTrace provides are easy to use and help to enhance data integrity in applications.We further evaluate DTrace with several microbenchmarks to show the time cost that DTrace’s data tracing operation incurs.We also evaluate DTrace on Nginx to show the performance impact when Nginx is enhanced in security to provide the integrity during the runtime execution for programmer-defined security sensitive data.We find the performance overhead that DTrace incurs for the data tracing is moderate.