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

2021 ◽  
Author(s):  
Jiatong Ling ◽  
Hang Zhang ◽  
Dong Shaohua ◽  
Jinheng Luo
Keyword(s):  
Mobile Devices ◽  
Third Party ◽  
Location Information ◽  
Long Distance ◽  
Prevention Method

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.

ILSSPP: Intelligent location sharing system with privacy preserving features for smart cities

2021 ◽  
pp. 1-12
Author(s):  
Gokay Saldamli ◽  
Richard Chow ◽  
Hongxia Jin
Keyword(s):  
Service Providers ◽  
Smart Cities ◽  
User Interaction ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Third Party ◽  
Location Information ◽  
Fine Grained ◽  
Location Sharing ◽  
Social Network Structure

Social networking services are increasingly accessed through mobile devices. This trend has prompted services such as Facebook and Google+to incorporate location as a de facto feature of user interaction. At the same time, services based on location such as Foursquare and Shopkick are also growing as smartphone market penetration increases. In fact, this growth is happening despite concerns (growing at a similar pace) about security and third-party use of private location information (e.g., for advertising). Nevertheless, service providers have been unwilling to build truly private systems in which they do not have access to location information. In this paper, we describe an architecture and a trial implementation of a privacy-preserving location sharing system called ILSSPP. The system protects location information from the service provider and yet enables fine grained location-sharing. One main feature of the system is to protect an individual’s social network structure. The pattern of location sharing preferences towards contacts can reveal this structure without any knowledge of the locations themselves. ILSSPP protects locations sharing preferences through protocol unification and masking. ILSSPP has been implemented as a standalone solution, but the technology can also be integrated into location-based services to enhance privacy.

scholarly journals Fingerprinting Mobile Devices Using Personalized Configurations

2016 ◽  
Vol 2016 (1) ◽  
pp. 4-19 ◽  
Author(s):  
Andreas Kurtz ◽  
Hugo Gascon ◽  
Tobias Becker ◽  
Konrad Rieck ◽  
Felix Freiling
Keyword(s):  
Supervised Learning ◽  
Mobile Devices ◽  
Real World ◽  
Third Party ◽  
Learning Approach ◽  
Total Accuracy ◽  
Over Time

Abstract Recently, Apple removed access to various device hardware identifiers that were frequently misused by iOS third-party apps to track users. We are, therefore, now studying the extent to which users of smartphones can still be uniquely identified simply through their personalized device configurations. Using Apple’s iOS as an example, we show how a device fingerprint can be computed using 29 different configuration features. These features can be queried from arbitrary thirdparty apps via the official SDK. Experimental evaluations based on almost 13,000 fingerprints from approximately 8,000 different real-world devices show that (1) all fingerprints are unique and distinguishable; and (2) utilizing a supervised learning approach allows returning users or their devices to be recognized with a total accuracy of 97% over time

scholarly journals IDA-Pay: a secure and efficient micro-payment system based on Peer-to-Peer NFC technology for Android mobile devices

2012 ◽  
Vol 8 (4) ◽  
pp. 117 ◽  
Author(s):  
Luca Mainetti ◽  
Luigi Patrono ◽  
Roberto Vergallo
Keyword(s):  
Mobile Devices ◽  
Near Field ◽  
Operating Mode ◽  
Peer To Peer ◽  
Payment System ◽  
Third Party ◽  
Payment Systems ◽  
Shopping Experience ◽  
And Performance ◽  
System Effectiveness

The evolution of modern mobile devices towards novel Radio Frequency (RF) capabilities, such as Near Field Communication, leads to a potential for delivering innovative mobile services, which is still partially unexplored. Mobile proximity payment systems are going to enhance the daily shopping experience, but the access to payment security resources of a mobile device (e.g. the “Secure Element”) by third party applications is still blocked by smartphone and Operating System manufacturers. In this paper, the IDA-Pay system is presented, an innovative and secure NFC micro-payment system based on Peer-to-Peer NFC operating mode for Android mobile phones. It allows to deliver mobile-to-POS micro-payment services, bypassing the need for special hardware. A validation scenario and a system evaluation are also reported to demonstrate the system effectiveness and performance.

Mobile Accessibility in Touchscreen Devices

2014 ◽  
pp. 182-202
Author(s):  
Volkan Çalışkan ◽  
Özgürol Öztürk ◽  
Kerem Rızvanoğlu
Keyword(s):  
Mobile Devices ◽  
Video Recording ◽  
Assistive Technologies ◽  
Third Party ◽  
Future Research ◽  
Screen Reader ◽  
Observation Methods ◽  
Mobile Accessibility ◽  
Usage Patterns ◽  
Multi Method Approach

Mobile technology is a new frontier for accessibility. Although mobile developers need solid guidelines to provide accessible experiences, there is a limited number of empirical research on mobile accessibility of different mobile platforms that work through various assistive technologies. In this context, more information is needed to understand both usage patterns and hardware/software platforms to guide decisions to meet the needs of people with disabilities who use mobile devices. This study, which is a pilot study of a long-term research, evaluates the accessibility of selected built-in and third party iOS applications in the iPhone and iPad through an extensive accessibility test with two blind users who are novice users of touchscreen mobile devices. This qualitative study is based on a multi-method approach, which consists of a background questionnaire, task observation, and a structured debriefing interview. The study also employs observation methods of data collection in order to gain better insight in mobile accessibility. The participants are demanded to execute three different tasks on each platform by using VoiceOver, which is the built-in screen reader in iOS. The participants are observed during the task executions and the “think aloud” procedure and video recording of the participants collected additional data. A short debriefing interview was also made to gain a detailed insight into the user experience. The findings reveal significant accessibility problems caused specifically by design of the graphical user interface features of the applications and limitations of the screen reader. Finally, as part of future research directions, preliminary guidelines are proposed to improve accessibility for iOS applications in both platforms.

Mobile Commerce Security and Its Prevention

2018 ◽  
pp. 433-449
Author(s):  
Mona Adlakha
Keyword(s):  
Mobile Devices ◽  
Best Practice ◽  
Personal Data ◽  
Mobile Commerce ◽  
Mitigation Strategies ◽  
Risk Prevention ◽  
Third Party ◽  
Security Measures ◽  
Security Risk ◽  
Security Standards

Mobile commerce is the next generation of e-commerce, where payments and financial transactions can be carried out with utmost ease using handheld mobile devices. Mobile devices are at a higher security risk due to the large amount of critical financial and personal data available on it. The cause or consequence of these threats could be - malware and spyware attacks; multiple or incorrect m-Commerce payments; breaches due to unauthorized access or disclosure, unauthenticated transactions and risk due to the use of third party networks. This chapter discusses how to manage security risks in m-commerce by first identifying them and then discussing preventive measures for their mitigation. A continuous approach for risk prevention needs to be followed, reviewing the strategy according to the latest challenges. Various risk prevention and mitigation strategies can be adopted. Service providers must follow physical and digital security measures to protect consumer's business information. Independent auditing should ensure compliance with best practice security standards.

Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage

2019 ◽  
Author(s):  
Apeksha Lanjile ◽  
Mohamed Younis ◽  
Seung-Jun Kim ◽  
Soobum Lee
Keyword(s):  
Pipe Wall ◽  
Third Party ◽  
Harsh Environments ◽  
Detection Accuracy ◽  
Acoustic Sensors ◽  
Long Distance ◽  
Acoustic Characteristics ◽  
Pipeline Monitoring ◽  
Simulation Results ◽  
Early Detection And Prevention

Abstract Long distance transportation of various fluid commodities like water, oil, natural gas liquids is achieved through a distribution network of pipelines. Many of these pipelines operates unattended in harsh environments. Therefore, pipes are often susceptible to corrosion, leakage, cracking and third party damage leading to economic and resource infrastructure losses. Thus, early detection and prevention of any further losses is very important. Although many pipeline monitoring techniques exist, the majority of them are based on single sensing modality like acoustic, accelerometer, ultrasound, pressure. This makes the existing techniques unreliable, sensitive to noise and costly. This paper describes a methodology to combine accelerometer and acoustic sensors to increase the detection fidelity of pipeline leakages. The sensors are mounted on the pipe wall at multiple locations. Vibrational and acoustic characteristics obtained from these sensors are fused together through wavelet analysis and classified using kernel SVM and Logistic Regression in order to detect small bursts and leaks in the pipe. The simulation results have confirmed the effectiveness of proposed methodology yielding 90% leak detection accuracy.

Pipeline Acoustic Pre-Warning System and Method of Signal Analysis

2008 ◽  
Author(s):  
Pengchao Chen ◽  
Yongjun Cai ◽  
Dongjie Tan ◽  
Yi Sun ◽  
Muyang Ai ◽  
...  
Keyword(s):  
Background Noise ◽  
Signal Analysis ◽  
Warning System ◽  
Acoustic Signals ◽  
Third Party ◽  
Feature Subset ◽  
Long Distance ◽  
Long Distance Transmission ◽  
Optimal Feature Subset ◽  
Optimal Feature

This paper describes a new acoustic pre-warning system for pipelines, aimed at preventing third party damage by monitoring the pipeline acoustic signals. Many environmental factors, such as the by-passing of vehicles and pedestrians, could introduce background noise into long distance transmission of pipeline acoustic signals. As a result, normal pipeline acoustic pre-warning system is disturbed to identify abnormal events. In this work, statistical methods were applied to signal analysis in order to extract feature parameters of different events. Then the optimal feature subset was obtained by gene arithmetic to differentiate hazardous events between normal events effectively. PetroChina has applied the new pre-warning system to their long distance transmission pipelines and the system operates well.

scholarly journals An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Ou ◽  
Hui Yin ◽  
Zheng Qin ◽  
Sheng Xiao ◽  
Guangyi Yang ◽  
...  
Keyword(s):  
Location Privacy ◽  
Security Analysis ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Third Party ◽  
Location Information ◽  
User Privacy ◽  
User Revocation ◽  
And Performance ◽  
Cloud Infrastructures

Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme.

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