Intelligent Cache Management for Mobile Data Warehouse Systems

This research proposes an intelligent cache mechanism for a data warehouse system in a mobile environment. Because mobile devices can often be disconnected from the host server and due to the low bandwidth of wireless networks, it is more efficient to store query results from a mobile device in the cache. For more personal use of mobile devices, we use a data mining technique to determine the pattern from a record of previous queries. Then the data, which will be retrieved by the user, are prefetched and stored in the cache, thus, improving the query efficiency. We demonstrate the feasibility of the proposed approach with experiments using simulation. Comparison of our approach with a standard approach indicates that there is a significant advantage to using mobile data warehouse systems.

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Conservation of Mobile Data and Usability Constraints

Cyber Security Standards, Practices and Industrial Applications ◽

10.4018/978-1-60960-851-4.ch003 ◽

2011 ◽

pp. 40-55

Author(s):

Rania Mokhtar ◽

Rashid Saeed

Keyword(s):

Mobile Computing ◽

Mobile Devices ◽

Cyber Security ◽

Data Encryption ◽

Mobile Environment ◽

Mobile Data ◽

Security Technologies ◽

User Data ◽

Security Standard ◽

Stored Information

An important part of ISO/IEC 27002 cyber security standard is the conservation of confidentiality that falls under its computer facility protection part which insures that the computer and its stored information can only be accessed by the authorized users. Securing mobile devices and mobile data to ensure the confidentiality, integrity, and availability of both data and security applications requires special consideration to be paid to the typical mobile environment in which a mobile computing device would be utilized. Protecting mobile devices includes multiple security technologies such as the right identification of its particular user, data encryption, physical locking devices, monitoring and tracking software, and alarms. This chapter reviews security-specific hardware and software applied to mobile computing and presents its advantages and drawbacks. Then it considers the concept of usability constraints in context of mobile computing security and introduces the seamless security method for identity proof of a particular user or device.

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Intelligent Cache Management for Mobile Data Warehouse Systems

Journal of Database Management ◽

10.4018/jdm.2005040103 ◽

2005 ◽

Vol 16 (2) ◽

pp. 46-65 ◽

Cited By ~ 6

Author(s):

Shi-Ming Huang ◽

Binshan Lin ◽

Qun-Shi Deng

Keyword(s):

Data Warehouse ◽

Cache Management ◽

Mobile Data ◽

Intelligent Cache

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Study on the Data Stream Mining and its Application Facing the Mobile Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.43.695 ◽

2010 ◽

Vol 43 ◽

pp. 695-698

Author(s):

Ji Nan Gu ◽

Guo Jing Li

Keyword(s):

Data Mining ◽

Data Stream ◽

Continuous Data ◽

Data Stream Mining ◽

Mobile Environment ◽

Mobile Business ◽

Mining Technology ◽

Mobile Data ◽

High Efficient ◽

Mobile Data Mining

the striving development of mobile business and the wide use of mobile equipment have enlightened the requirement of high efficient analyst instrument of data stream. Mobile data mining is under the environment of pervasive and finds the knowledge from the continuous data stream. We apply the mining technology of data stream to mobile environment and discuss the algorithm. And we introduce the concrete idea and steps of mobile data mining on the base of improved data stream disposing model. At last, we introduce the application instance that is the application of mobile ERP.

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Discovering Surprising Instances of Simpson's Paradox in Hierarchical Multidimensional Data

Data Warehousing and Mining ◽

10.4018/978-1-59904-951-9.ch205 ◽

2008 ◽

pp. 3235-3251

Author(s):

Carem C. Fabris ◽

Alex A. Freitas

Keyword(s):

Data Mining ◽

Data Warehouse ◽

Data Warehousing ◽

Multidimensional Data ◽

Data Mining Technique ◽

Simpson’S Paradox ◽

Mining Technique ◽

Simpson's Paradox ◽

Single Relation ◽

Novel Algorithm

This paper focuses on the discovery of surprising unexpected patterns based on a data mining method that consists of detecting instances of Simpson’s paradox. By its very nature, instances of this paradox tend to be surprising to the user. Previous work in the literature has proposed an algorithm for discovering instances of that paradox, but it addressed only flat data stored in a single relation. This work proposes a novel algorithm that considerably extends that previous work by discovering instances of Simpson’s paradox in hierarchical multidimensional data — the kind of data typically found in data warehouse and OLAP environments. Hence, the proposed algorithm can be regarded as integrating the areas of data mining and data warehousing by using an adapted data mining technique to discover surprising patterns from data warehouse and OLAP environments.

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A Study on the Analysis of Employment Decision Factor of the Visually Impaired using Data Mining Technique

Disability & Employment ◽

10.15707/disem.2013.23.1.011 ◽

2013 ◽

Vol 23 (1) ◽

pp. 273-302 ◽

Cited By ~ 6

Author(s):

임은정 ◽

신현욱 ◽

김성진

Keyword(s):

Data Mining ◽

Visually Impaired ◽

Data Mining Technique ◽

Mining Technique ◽

Employment Decision ◽

Using Data

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Retrieving Information and Discovering Knowledge from Unstructured Data Using Big Data Mining Technique: Heavy Oil Fields Example

10.2523/17805-ms ◽

2014 ◽

Cited By ~ 1

Author(s):

Wenkuang Wu ◽

Xiaoguang Lu ◽

Ben Cox ◽

Guoqiang Li ◽

Lihua Lin ◽

...

Keyword(s):

Data Mining ◽

Big Data ◽

Heavy Oil ◽

Oil Fields ◽

Unstructured Data ◽

Data Mining Technique ◽

Big Data Mining ◽

Mining Technique

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Know Your Stars Before They Fall Apart: A Social Network Analysis of Telecom Industry to Foster Employee Retention using Data Mining Technique

IEEE Access ◽

10.1109/access.2021.3050327 ◽

2021 ◽

pp. 1-1

Author(s):

Sundus Younis ◽

Ali Ahsan

Keyword(s):

Data Mining ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Employee Retention ◽

Data Mining Technique ◽

Mining Technique ◽

Telecom Industry ◽

Using Data

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Detecting Colluding Inter-App Communication in Mobile Environment

Applied Sciences ◽

10.3390/app10238351 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8351

Author(s):

Rosangela Casolare ◽

Fabio Martinelli ◽

Francesco Mercaldo ◽

Antonella Santone

Keyword(s):

Model Checking ◽

Mobile Devices ◽

Private Information ◽

End Users ◽

Home Automation ◽

Mobile Environment ◽

Data Support ◽

Bank Transfer ◽

Android Applications

The increase in computing capabilities of mobile devices has, in the last few years, made possible a plethora of complex operations performed from smartphones and tablets end users, for instance, from a bank transfer to the full management of home automation. Clearly, in this context, the detection of malicious applications is a critical and challenging task, especially considering that the user is often totally unaware of the behavior of the applications installed on their device. In this paper, we propose a method to detect inter-app communication i.e., a colluding communication between different applications with data support to silently exfiltrate sensitive and private information. We based the proposed method on model checking, by representing Android applications in terms of automata and by proposing a set of logic properties to reduce the number of comparisons and a set of logic properties automatically generated for detecting colluding applications. We evaluated the proposed method on a set of 1092 Android applications, including different colluding attacks, by obtaining an accuracy of 1, showing the effectiveness of the proposed method.

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