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A scalable file based data store for forensic analysis

DIGITAL INVESTIGATION 2015年第S1期12卷 S90-S101页

作者： Cruz, Flavio Moser, Andreas Cohen, Michael Carnegie Mellon Univ Pittsburgh PA 15213 USA Google Inc Zurich Switzerland

In the field of remote forensics, the GRR Response Rig has been used to access and store data from thousands of enterprise machines. Handling large numbers of machines requires efficient and scalable storage mechanisms that allow concurrent data operations and efficient data access, independent of the size of the stored data and the number of machines in the network. We studied the available GRR storage mechanisms and found them lacking in both speed and scalability. In this paper, we propose a new distributed data store that partitions data into database files that can be accessed independently so that distributed forensic analysis can be done in a scalable fashion. We also show how to use the NSRL software reference database in our scalable data store to avoid wasting resources when collecting harmless files from enterprise machines. (C) 2015 The Authors. Published by Elsevier Ltd.

关键词： distributed database Incident response Sqlite Evidence analysis distributed computing

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Analysis of problems induced by imprecise dating of measurements in oil and gas production

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IFAC-PapersOnLine 2015年第8期48卷 966-973页

作者： Nicolas Petit

In this paper we discuss the negative impact on monitoring algorithms of working with imprecisely dated data. Two examples from the world of the oil & gas industry are presented and serve to illustrate that this problem can be of practical importance. First analytical results show that when signals with significant time variations are monitored, the impact of dating of measurements can be as troublesome (or even worse) than measurement noises.

关键词： process control monitoring algorithms synchronisation of data information technology distributed database

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NoSQL For Dummies 1

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丛书名： For dummies.

2015年

作者： Adam Fowler

ISBN: (数字)9781118905784

ISBN: (纸本)1118905741;9781118905746

Get up to speed on the nuances of NoSQL databases and what theymean for your organization This easy to read guide to NoSQL databases provides the type ofno-nonsense overview and analysis that you need to learn, includingwhat NoSQL is and which database is right for you. Featuringspecific evaluation criteria for NoSQL databases, along with a lookinto the pros and cons of the most popular options, NoSQL ForDummies provides the fastest and easiest way to dive into thedetails of this incredible technology. You'll gain an understandingof how to use NoSQL databases for mission-critical enterprisearchitectures and projects, and real-world examples reinforce theprimary points to create an action-oriented resource for ITpros. If you're planning a big data project or platform, you probablyalready know you need to select a NoSQL database to complete yourarchitecture. But with options flooding the market and updates andadd-ons coming at a rapid pace, determining what you require now,and in the future, can be a tall task. This is where NoSQL ForDummies comes in! * Learn the basic tenets of NoSQL databases and why they havecome to the forefront as data has outpaced the capabilities ofrelational databases * Discover major players among NoSQL databases, includingCassandra, MongoDB, MarkLogic, Neo4J, and others * Get an in-depth look at the benefits and disadvantages of thewide variety of NoSQL database options * Explore the needs of your organization as they relate to thecapabilities of specific NoSQL databases Big data and Hadoop get all the attention, but when it comesdown to it, NoSQL databases are the engines that power many bigdata analytics initiatives. With NoSQL For Dummies, you'llgo beyond relational databases to ramp up your enterprise's dataarchitecture in no time.

关键词： NoSQL For Dummies Adam Fowler big data Not Only SQL non-relational database scalable database distributed database MongoDB Cassandra Riak MarkLogic Neo4j commercial NoSQL BigTable Basho Technologies NanoTechnology 10gen Gartner NoSQL Magic Quadrant NoSQL pros and cons NoSQL evaluation criteria emerging technology big data database enterprise NoSQL NoSQL selection criteria graph database key/value database column store database open-source NoSQL open-source database

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Data Outsourcing based on Secure Association Rule Mining Processes

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INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS 2015年第3期9卷 41-48页

作者： Sujatha, V. Bhattacharyya, Debnath Chaitanya, P. Silpa Kim, Tai-hoon Vignans Nirula ITW Palakaluru Dept Comp Sci & Engn Guntur AP India Vignans Inst Informat Technol Dept Comp Sci & Engn Visakhapatnam Andhra Pradesh India Sungshin Womens Univ Dept Convergence Secur Seoul 136742 South Korea

Data mining is the process of extracting information from data warehousing applications. Data outsourcing is the major task in present days, for accessing services and other features of the database processing. But sometimes this process may achieve to split among various parties with recommended data items in analyzing of the data. Data security is one of the key processes in outsourcing data to various outside users. Traditionally Fast Distribution Mining algorithm was proposed for securing distributed data. This paper addresses a problem by secure association rules over partitioned data in both horizontal and vertical representation. A secure frequency developed algorithm is used for doing above process efficiently in partitioned data, which includes services of the data in outsourcing process. Frequent item sets are used to access services in outsourcing data in recent application development data mining. Our proposed work maintains efficient security over vertical and horizontal view of representation in secure mining applications. The result shows that algorithm timing is desirable for big size data for security considerations using association rule mining operations in real time application development.

关键词： Association Rules Cryptography distributed database distributed Computation Privacy Preserving Data Mining

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Privacy Preservation in Vertical Partitioned Medical database in the Cloud Environments

Privacy Preservation in Vertical Partitioned Medical Databas...

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International Conference on Futuristic Trends on Computational Analysis and Knowledge Management

作者： Raghvendra Kumar Yogesh Sharma Prashant Kumar Pattnaik Jodhpur National University KIIT University

ISBN: (纸本)9781479984343

In this paper we introduced the concept of cloud computing with the help of secure multi party computation, secure multi party computation play a very crucial role in the field of distributed database where the number of parties or resources is greater than or equal to two. In secure multi party computation each party will calculate their common function and send to the next party present in the database environments. Secure multi party computation is used to increases the performance and efficiency. Cloud computing is new emerging technology in the field of information and communication technology. Which will use the high speed infrastructure and services provided by the cloud service provider? In this paper we implement and study the concept of the vertical partitioned resource database in the cloud environments. Where every party contains their own private resources and wants to communicate with each other without disclosing their private information to the other resources present in the secure multi party cloud based environment.

关键词： distributed database Cloud computing SMC Association Rule Mining Ring topology

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Securing the Clustered database using Data Modification Technique

Securing the Clustered Database using Data Modification Tech...

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International Conference on Computational Intelligence and Communication Networks

作者： Pinkal Jain Sandeep Nandanwar Dept. of Computer Science and Engineering VITS College

ISBN: (纸本)9781509000777

The new era of information communication and technology (ICT), everyone wants to store/share their Data or information in online media, like in cloud database, mobile database, grid database, drives etc. When the data is stored in online media the main problem is arises related to data is privacy because different types of hacker, attacker or crackers wants to disclose their private information as publically. Security is a continuous process of protecting the data or information from attacks. For securing that information from those kinds of unauthorized people we proposed and implement of one the technique based on the data modification concept with taking the iris database on weka tool. And this paper provides the high privacy in distributed clustered database environments.

关键词： Data Mining distributed database Privacy preserving protocols Clustering

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Quality-aware schedulers for weak consistency key-value data stores

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distributed AND PARALLEL databaseS 2014年第4期32卷 535-581页

作者： Xu, Chen Sharaf, Mohamed A. Zhou, Xiaofang Zhou, Aoying E China Normal Univ Inst Software Engn Shanghai 200062 Peoples R China Univ Queensland Sch Informat Technol & Elect Engn Brisbane Qld Australia

Highly distributed NoSQL key-value data stores are rapidly becoming the favorite choice for hosting modern web applications. Such platforms rely on data partitioning, replication and relaxed consistency to achieve high levels of performance and scalability. However, these design choices often exhibit a trade-off between latency (i.e., Quality of Service (QoS)) and consistency (i.e., Quality of Data (QoD)). In this work, in addition to latency-based SLAs, we also adopt the application tolerance to data staleness as another requirement determining the end-user satisfaction and our goal is to strike a fine balance between both the QoS and QoD provided to the end-user. Towards achieving that goal, we propose a suite of quality-aware schedulers for efficiently allocating the necessary computational resources between the foreground user-queries and the background system-updates at data store nodes. This suite of schedulers features our proposed Freshness/Tardiness (FIT) mechanism, which introduces a novel selective approach for scheduling the execution of queries and updates. Our experimental results show that FIT provides significant improvements in balancing the trade-off between QoS and QoD under both the state-transfer and operation-transfer update propagation models employed in current key-value data stores.

关键词： NoSQL Key-value data stores distributed database Scheduling Consistency SLA FLA Quality of data Quality of service

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ConfluxDB: Multi-Master Replication for Partitioned Snapshot Isolation databases

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PROCEEDINGS OF THE VLDB ENDOWMENT 2014年第11期7卷 947-958页

作者： Chairunnanda, Prima Daudjee, Khuzaima Oezsu, M. Tamer Univ Waterloo Cheriton Sch Comp Sci Waterloo ON Canada

Lazy replication with snapshot isolation (SI) has emerged as a popular choice for distributed databases. However, lazy replication often requires execution of update transactions at one (master) site so that it is relatively easy for a total SI order to be determined for consistent installation of updates in the lazily replicated system. We propose a set of techniques that support update transaction execution over multiple partitioned sites, thereby allowing the master to scale. Our techniques determine a total SI order for update transactions over multiple master sites without requiring global coordination in the distributed system, and ensure that updates are installed in this order at all sites to provide consistent and scalable replication with SI. We present ConfluxDB, a PostgreSQL-based implementation of our techniques, and demonstrate its effectiveness through experimental evaluation.

关键词： distributed database distributed systems Experimental evaluation Global coordination Lazy replication Replicated systems Snapshot isolation Update transaction

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A modular, prospective, semi-automated drug safety monitoring system for use in a distributed data environment

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PHARMACOEPIDEMIOLOGY AND DRUG SAFETY 2014年第6期23卷 619-627页

作者： Gagne, Joshua J. Wang, Shirley V. Rassen, Jeremy A. Schneeweiss, Sebastian Brigham & Womens Hosp Dept Med Div Pharmacoepidemiol & Pharmacoecon Boston MA 02120 USA Harvard Univ Sch Med Boston MA 02120 USA

PurposeThe aim of this study was to develop and test a semi-automated process for conducting routine active safety monitoring for new drugs in a network of electronic healthcare databases. MethodsWe built a modular program that semi-automatically performs cohort identification, confounding adjustment, diagnostic checks, aggregation and effect estimation across multiple databases, and application of a sequential alerting algorithm. During beta-testing, we applied the system to five databases to evaluate nine examples emulating prospective monitoring with retrospective data (five pairs for which we expected signals, two negative controls, and two examples for which it was uncertain whether a signal would be expected): cerivastatin versus atorvastatin and rhabdomyolysis;paroxetine versus tricyclic antidepressants and gastrointestinal bleed;lisinopril versus angiotensin receptor blockers and angioedema;ciprofloxacin versus macrolide antibiotics and Achilles tendon rupture;rofecoxib versus non-selective non-steroidal anti-inflammatory drugs (ns-NSAIDs) and myocardial infarction;telithromycin versus azithromycin and hepatotoxicity;rosuvastatin versus atorvastatin and diabetes and rhabdomyolysis;and celecoxib versus ns-NSAIDs and myocardial infarction. ResultsWe describe the program, the necessary inputs, and the assumed data environment. In beta-testing, the system generated four alerts, all among positive control examples (i.e., lisinopril and angioedema;rofecoxib and myocardial infarction;ciprofloxacin and tendon rupture;and cerivastatin and rhabdomyolysis). Sequential effect estimates for each example were consistent in direction and magnitude with existing literature. ConclusionsBeta-testing across nine drug-outcome examples demonstrated the feasibility of the proposed semi-automated prospective monitoring approach. In retrospective assessments, the system identified an increased risk of myocardial infarction with rofecoxib and an increased risk of rhabdomyolysis with

关键词： prospective active surveillance monitoring distributed database pharmacoepidemiology

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distributed database Searching System based on Alchemi

Distributed Database Searching System based on Alchemi

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International Forum on Computer Science-Technology and Applications

作者： Xia Hongxia Li Weifeng Wuhan Univ Technol Dept Comp Sci & Technol Wuhan 430070 Peoples R China

ISBN: (纸本)9780769539300

With the information expanding and network popularization, the way that accessing single database can not satisfy the demands for users. The requirement to access distributed database is increased. This paper firstly implemented distributed database query with the grid computing architecture Alchemi which is based on .NET. Then, a distributed database searching system model was constructed by grid computing technology, while the architecture and the operation process of the model were described in detail. Finally, the model was achieved with the platform of ***. According to the analyses of the configuration information and experimental results, it is proved that, compared with the current distributed database searching system, the system that developed by Alchemi is not only easy to configure, but also able to assure the efficiency and accuracy of the query.

关键词： distributed database grid computing Alchemi grid thread .NET Remoting dataset

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