Supporting Location Information Privacy in Mobile Devices

2013 ◽  
pp. 361-372 ◽  
Author(s):  
Deveeshree Nayak ◽  
M. Venkata Swamy ◽  
Srini Ramaswamy
Keyword(s):  
Mobile Devices ◽  
Information Privacy ◽  
Location Information

scholarly journals SISTEM INFORMASI GEOGRAFIS LOKASI DESA TANGGUH BENCANA (DESTANA) BERBASIS ANDROID PADA BADAN PENANGGULANGAN BENCANA DAERAH KABUPATEN GORONTALO

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Arya Pakaya
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographical Information System ◽  
Mobile Devices ◽  
Geographic Information ◽  
Geographical Information ◽  
Location Information ◽  
Test Results ◽  
Digital Map ◽  
Data Location

Tangguh Disaster Village is a village that has a self-reliant ability to adapt and face disaster threats and recover immediately from adverse catastrophic impacts. The problem in designing this system is that there is no geographical information system based on Android in the process of searching the data location of Tangguh disaster Village (DESTANA) in Gorontalo district. This research aims to design an Android-based geographic information system that can be used to locate the Tangguh Disaster village (DESTANA) data location in Gorontalo District to help local people and migrants with Use Android mobile devices that provide information about the Tangguh disaster Village (DESTANA) data location and know the location of an area presented with digital map facilities.  The results of the study concluded that the test results to search for the location information of disaster Tangguh Village (DESTANA) and display the appropriate and valid view so that the application can be used effectively and efficiently.

Intelligent Prevention Method for Third-Party Damage of Long-Distance Pipeline Based on Mobile Devices Location Information

2020 ◽  
Author(s):  
Jiatong Ling ◽  
Hang Zhang ◽  
Shaohua Dong ◽  
Jinheng Luo
Keyword(s):  
Mobile Devices ◽  
Oil And Gas ◽  
Third Party ◽  
Location Information ◽  
Long Distance ◽  
The Third ◽  
Pipeline Segment ◽  
The Third Party ◽  
The Difference ◽  
Prevention Method

Abstract As one of the main risks of long-distance oil and gas pipelines, the consequences of pipeline accidents caused by third-party damage (TPD) are usually catastrophic. At present, TPD prevention approaches mainly include manual line patrol, fiber-optical vibration warning, and unmanned aerial vehicle (UAV) line patrol, but there are some limitations such as untimely warning, false alarm, and the missed report. As the location technology of mobile device matures, the user group provides massive data sources for the collection of location information, with which the tracks and features of the third-party activity along the pipeline can be directly obtained. Therefore, this paper proposes a method to identify the TPD behavior based on the location data of mobile devices. Firstly, the characteristics of relevant destruction behaviors were extracted from the historical destruction events. Then, the location information of the third-party activity near the target pipeline is obtained and the data is processed to remove the influence of noise, to reduce the computational burden of the subsequent identification process. Finally, calculate the difference degree of neighborhood trajectory and the similarity with the TPD features based on the data feature grouping (Difference feature and Similarity feature) to classify the type of third-party activity. Taking a 10km pipeline segment as an example, the method of this paper is used to preprocess the collected data and calculate the difference degree and similarity, 232 suspected TPD events are identified. After the on-site verification of the suspected damage by the line patrol, the results show that the method can better identify the third-party activities near the pipeline.

Mobile Cloud Computing

2015 ◽  
pp. 249-265
Author(s):  
Jorge E. F. Costa ◽  
Joel J. P. C. Rodrigues
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Emerging Technologies ◽  
Location Information ◽  
Mobile Cloud ◽  
Tablet Computers ◽  
Daily Lives ◽  
Computing Technologies

Mobile devices have gained great importance in the daily lives of people. Smartphones and tablet computers make people's lives easier by being more useful and offering more capabilities and services for a plethora of activities. Those devices include various sensing modules for collecting location information related to navigation, gravity, and orientation, which bring a diversity and intelligent ubiquitous mobile experience to users. In this chapter, cloud computing and mobile cloud computing are addressed in order to give insight about the topic and offer an important overview for this book. The diverse research definitions of these emerging technologies and contributions to enhance users' lives are considered. Furthermore, the technologies and identified advantages to improve and justify the strong use of mobile cloud are discussed. Relevant mobile cloud computing applications are presented, showing good results and a promising future for mobile cloud computing technologies.

Context-Aware Framework for the Support of User Services

2013 ◽  
Vol 811 ◽  
pp. 602-607
Author(s):  
Hoon Jeong ◽  
Ha Na Do ◽  
Eui In Choi
Keyword(s):  
Mobile Devices ◽  
Wireless Network ◽  
Location Information ◽  
Context Information ◽  
Context Aware ◽  
Web Based ◽  
Current State ◽  
Exchange Information ◽  
The Web

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. Therefore users are able to use the information and service more free than previous wire network due to development of wireless network and device. In order to provide appropriate user services, it enables to recognize users current state, analyze the users profile like users tendency and preference, and draw the service answering the users request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among users context information is not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using users context and profile.

scholarly journals LIP-PA: A Logistics Information Privacy Protection Scheme with Position and Attribute-Based Access Control on Mobile Devices

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Qi Gao ◽  
Junwei Zhang ◽  
Jianfeng Ma ◽  
Chao Yang ◽  
Jingjing Guo ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Mobile Devices ◽  
Privacy Protection ◽  
Personal Information ◽  
Information Privacy ◽  
Smart Devices ◽  
Protection Scheme ◽  
Logistics Information ◽  
Attribute Based Access Control

With the fast development of Logistics Internet of Things and smart devices, the security of express information processed by mobile devices in Logistics Internet of Things has attracted much attention. However, the existing secure express schemes only focus on privacy protection of personal information but do not consider the security of the logistics information against couriers with malicious mobile devices. For example, a privacy-preserving delivery path should be required in order to prevent the privacy leakage in the express delivery procedure. Therefore, besides the security of personal information, the privacy protection of logistics information and authentication of mobile devices used in express company are important to security in Logistics Internet of Things. In this paper, we propose a secure logistics information scheme LIP-PA to provide privacy protection of both personal information and logistics information. First, we define the basic requirements of Logistics Internet of Things. Then, using attribute-based encryption and position-based key exchange, we propose a logistics information privacy protection scheme with position and attribute-based access control for mobile devices. The analysis results show that our scheme satisfies the defined requirements. Finally, the performance of our scheme is evaluated and the experiment results show that our scheme is efficient and feasible for mobile devices in real parcel delivery scenario.

Location-Based Advertising Using Location-Aware Data Mining

2018 ◽  
pp. 196-211
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
Hongyu Guo ◽  
AbdElRahman Ahmed ElSaid
Keyword(s):  
Data Mining ◽  
Mobile Devices ◽  
Farmers Markets ◽  
Mobile Users ◽  
Location Information ◽  
Grocery Stores ◽  
User Privacy ◽  
Location Aware ◽  
To Receive

This chapter describes how mobile advertisements are critical for both mobile users and businesses as people spend more time on mobile devices than on PCs. However, how to send relevant advertisements and avoid unnecessary ones to specific mobile users is always a challenge. For example, a concert-goer may like to visit restaurants or parks before the concert and may not like the advertisements of grocery stores or farmers' markets. This research tries to overcome the challenge by using the methods of location-aware data mining. Furthermore, privacy is always a great concern for location-based advertising (LBA) users because their location information has to be shared in order to receive the services. This chapter also takes the concern into serious consideration, so the user privacy will not be compromised. Preliminary experiment results show the proposed methods are effective and user-privacy is rigorously preserved.

Location Information Management in LBS Applications

2011 ◽  
pp. 2450-2455 ◽  
Author(s):  
Anselmo Cardoso de Paiva ◽  
Erich Farias Monteiro ◽  
Jocielma Jerusa Leal Rocha ◽  
Claudio de Souza Baptista ◽  
Aristófanes Corrêa Silva
Keyword(s):  
Mobile Devices ◽  
Positional Information ◽  
Market Potential ◽  
Location Based Services ◽  
Location Information ◽  
Software Applications ◽  
New Applications ◽  
Application Developers ◽  
Services Effectiveness ◽  
Climatic Information

The mobile computing advent brings a set of new applications that benefit from the constant need of information, diminishing communication costs and favoring the popularization of mobile devices, to reach an increasing number of users. The mobility characteristic opens a new area for software applications. Associated to the mobility we have the location identification, which turns into a critical attribute, once it allows the development of a great variety of new services and applications. The systems that benefit from the use of that location information are named locationbased systems (LBS); alternatively, these applications are also known as location-aware, context-aware, or adaptive information systems More precisely, we can define LBS as applications that use the location information to supply services, based on this position context, to their users (Kupper, 2005; Schiller & Voisard, 2004). The user location information makes available completely new and innovative service concepts, offering information to the user based on its own context (e.g., climatic information in the region where the user is located), increasing considerably the utility of these services. We know that location- based applications increase the services effectiveness, as they give a customized access to the data based on the user’s preferences and on its actual position. This enhances the personalization content, giving several benefits to users and to the application developers. In our daily life, several activities may use these services, like the emergency call centers, the car navigation services, and even location-based friend finder. We may verify that, beyond the already cited characteristics and benefits, what also gave the LBS applications a growing perspective were the location techniques modernization and the mobile devices popularization, enabling the offer of more precise, objective, and useful information. In Shiode et al. (Shiode, Li, Batty, Longley, & Maguire, 2002), research shows the trend of LBS market and the market potential reserved to this class of applications that, each year, turns out to be more important to the users, becoming the area that dominates the applications for mobile devices. According to Sayed (2005), the forecast annual revenues for location-based services was estimated in US $3.3 billions for United States in 2006/2007, and in US $11.7 billions on the other countries. In summary, we may say that the positional information has the potential to explore the user’s geographical context as one of the most important variables for content and services personalization for mobile devices users.

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