Cross-middleware Interoperability in Distributed Concurrent Engineering

Secure, distributed collaboration between different organizations is a key challenge in Grid computing today. The GDCD project has produced a Grid-based demonstrator Virtual Collaborative Facility (VCF) for the European Space Agency. The purpose of this work is to show the potential of Grid technology to support fully distributed concurrent design, while addressing practical considerations including network security, interoperability, and integration of legacy applications. The VCF allows domain engineers to use the concurrent design methodology in a distributed fashion to perform studies for future space missions. To demonstrate the interoperability and integration capabilities of Grid computing in concurrent design, we developed prototype VCF components based on ESA’s current Excel-based Concurrent Design Facility (a non-distributed environment), using a STEP-compliant database that stores design parameters. The database was exposed as a secure GRIA 5.1 Grid service, whilst a .NET/WSE3.0-based library was developed to enable secure communication between the Excel client and STEP database

An Analysis and Enumeration of the Blockchain and Future Implications

The blockchain is a relatively new technology that has grown in interest and potential research since its inception. Blockchain technology is dominated by cryptocurrency in terms of usage. Research conducted in the past few years, however, reveals blockchain has the potential to revolutionize several different industries. The blockchain consists of three major technologies: a peer-to-peer network, a distributed database, and asymmetrically encrypted transactions. The peer-to-peer network enables a decentralized, consensus-based network structure where various nodes contribute to the overall network performance. A distributed database adds additional security and immutability to the network. The process of cryptographically securing individual transactions forms a core service of the blockchain and enables semi-anonymous user network presence

Computing on Masked Data to improve the Security of Big Data

Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such untrusted servers or databases. Advances in cryptographic techniques and database technologies provide the necessary security functionality but rely on a computational model in which the cloud is used solely for storage and retrieval. Much of big data computation and analytics make use of signal processing fundamentals for computation. As the trend of moving data storage and computation to the cloud increases, homeland security missions should understand the impact of security on key signal processing kernels such as correlation or thresholding. In this article, we propose a tool called Computing on Masked Data (CMD), which combines advances in database technologies and cryptographic tools to provide a low overhead mechanism to offload certain mathematical operations securely to the cloud. This article describes the design and development of the CMD tool.Comment: 6 pages, Accepted to IEEE HST Conferenc

A SURVIVABLE DISTRIBUTED DATABASE AGAINST BYZANTINE FAILURE

Distributed Database Systems have been very useful technologies in making a wide range of information available to users across the World. However, there are now growing security concerns, arising from the use of distributed systems, particularly the ones attached to critical systems. More than ever before, data in distributed databases are more susceptible to attacks, failures or accidents owing to advanced knowledge explosions in network and database technologies. The imperfection of the existing security mechanisms coupled with the heightened and growing concerns for intrusion, attack, compromise or even failure owing to Byzantine failure are also contributing factors. The importance of  survivable distributed databases in the face of byzantine failure, to other emerging technologies is the motivation for this research. Furthermore, It has been observed that most of the existing works on distributed database only dwelled on maintaining data integrity and availability in the face of attack. There exist few on availability or survibability of distributed databases owing to internal factors such as internal sabotage or storage defects. In this paper, an architecture for entrenching survivability of Distributed Databases occasioned by Byzantine failures is proposed. The proposed architecture concept is based on re-creating data on failing database server based on a set  threshold value.The proposed architecture is tested and found to be capable of improving probability of survivability in distributed database where it is implemented to  99.6%  from 99.2%.

A Comparison of Cloud Computing Database Security Algorithms

The cloud database is a relatively new type of distributed database that allows companies and individuals to purchase computing time and memory from a vendor. This allows a user to only pay for the resources they use, which saves them both time and money. While the cloud in general can solve problems that have previously been too costly or time-intensive, it also opens the door to new security problems because of its distributed nature. Several approaches have been proposed to increase the security of cloud databases, though each seems to fall short in one area or another. This thesis presents the Hoeppner Security Algorithm (HSA) as a solution to these security problems. The HSA safeguards user’s data and metadata by adding fake records alongside the real records, breaking up the database by column or groups of columns, and by storing each group in a different cloud. The efficiency and security of this algorithm was compared to the Alzain algorithm (one of the proposed security solutions that inspired the HSA), and it was found that the HSA outperforms the Alzain algorithm in most every way