scholarly journals PRISER: Managing Notification in Multiples Devices with Data Privacy Support

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3098 ◽  
Author(s):  
Luis Augusto Silva ◽  
Valderi Reis Quietinho Leithardt ◽  
Carlos O. Rolim ◽  
Gabriel Villarrubia González ◽  
Cláudio F. R. Geyer ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Management System ◽  
Data Privacy ◽  
Smart Devices ◽  
User Profiles ◽  
Status Data ◽  
Short Time

With the growing number of mobile devices receiving daily notifications, it is necessary to manage the variety of information produced. New smart devices are developed every day with the ability to generate, send, and display messages about their status, data, and information about other devices. Consequently, the number of notifications received by a user is increasing and their tolerance may decrease in a short time. With this, it is necessary to develop a management system and notification controls. In this context, this work proposes a notification and alert management system called PRISER. Its focus is on user profiles and environments, applying data privacy criteria.

Secure Examination Management System for M-Learning (SEMS)

2017 ◽  
Vol 2 (2) ◽  
pp. 31-35
Author(s):  
Akshada Abnave ◽  
Charulata Banait ◽  
Mrunalini Chopade ◽  
Supriya Godalkar ◽  
Soudamini Pawar ◽  
...  
Keyword(s):  
Face Recognition ◽  
Social Interactions ◽  
Mobile Devices ◽  
Management System ◽  
Mobile Apps ◽  
Smart Phones ◽  
Examination System ◽  
Open Environment ◽  
Exchange Information ◽  
Personal Mobile Devices

M-learning or mobile learning is defined as learning through mobile apps, social interactions and online educational hubs via Internet or network using personal mobile devices such as tablets and smart phones. However, in such open environment examination security is most challenging task as students can exchange mobile devices or also can exchange information through network during examination. This paper aims to design secure examination management system for m- learning and provide appropriate mechanism for anti- impersonation to ensure examination security. The users are authenticated through OTP. To prevent students from exchanging mobile devices during examination, system re-authenticates students automatically through face recognition at random time without interrupting the test. The system also provides external click management i.e. prevent students from accessing online sites and already downloaded files during examination.

scholarly journals A Secure Ciphertext Retrieval Scheme against Insider KGAs for Mobile Devices in Cloud Storage

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Run Xie ◽  
Chanlian He ◽  
Dongqing Xie ◽  
Chongzhi Gao ◽  
Xiaojun Zhang
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Privacy ◽  
Security Analysis ◽  
Data Retrieval ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Security Issues ◽  
Efficiency Comparison ◽  
Cloud Servers

With the advent of cloud computing, data privacy has become one of critical security issues and attracted much attention as more and more mobile devices are relying on the services in cloud. To protect data privacy, users usually encrypt their sensitive data before uploading to cloud servers, which renders the data utilization to be difficult. The ciphertext retrieval is able to realize utilization over encrypted data and searchable public key encryption is an effective way in the construction of encrypted data retrieval. However, the previous related works have not paid much attention to the design of ciphertext retrieval schemes that are secure against inside keyword-guessing attacks (KGAs). In this paper, we first construct a new architecture to resist inside KGAs. Moreover we present an efficient ciphertext retrieval instance with a designated tester (dCRKS) based on the architecture. This instance is secure under the inside KGAs. Finally, security analysis and efficiency comparison show that the proposal is effective for the retrieval of encrypted data in cloud computing.

scholarly journals Mobile accident report and road assistance application

2018 ◽  
Vol 8 (3) ◽  
pp. 124-128
Author(s):  
Nadide Duygu Solak ◽  
Murat Topaloglu
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Mobile Application ◽  
Traffic Accident ◽  
Daily Life ◽  
Smart Devices ◽  
Loss Assessment ◽  
The Road ◽  
Speed Up ◽  
The Moment

The number of mobile applications has been increasing rapidly in every field of life with the increasing use of smart devices. Smartphones and tablets make our lives easier with their properties and application they include. Minor or major accidents in traffic are always present in the daily life resulting in financial damage and loss of lives. There have been a number of studies done to speed up the processes to be done from the moment an accident happens. This study aims to enable people to perform all of the post-accident processes quickly and accurately with the use of mobile devices. In this way, papers and documents like photographs will be sent to the competent authorities without wasting time and effort. In addition, access to the road assistance needed will be quite easy. Keywords: Traffic accident, loss assessment and proceedings, mobile application.

Device Fingerprinting with Magnetic Induction Signals Radiated by CPU Modules

2022 ◽  
Vol 18 (2) ◽  
pp. 1-28
Author(s):  
Xiaoyu Ji ◽  
Yushi Cheng ◽  
Juchuan Zhang ◽  
Yuehan Chi ◽  
Wenyuan Xu ◽  
...  
Keyword(s):  
Operating System ◽  
Mobile Devices ◽  
Power Supply ◽  
Magnetic Induction ◽  
Smart Devices ◽  
Popular Method ◽  
Fingerprinting Technique ◽  
Extraction Scheme ◽  
Measured Information ◽  
Test Points

With the widespread use of smart devices, device authentication has received much attention. One popular method for device authentication is to utilize internally measured device fingerprints, such as device ID, software or hardware-based characteristics. In this article, we propose DeMiCPU , a stimulation-response-based device fingerprinting technique that relies on externally measured information, i.e., magnetic induction (MI) signals emitted from the CPU module that consists of the CPU chip and its affiliated power-supply circuits. The key insight of DeMiCPU is that hardware discrepancies essentially exist among CPU modules and thus the corresponding MI signals make promising device fingerprints, which are difficult to be modified or mimicked. We design a stimulation and a discrepancy extraction scheme and evaluate them with 90 mobile devices, including 70 laptops (among which 30 are of totally identical CPU and operating system) and 20 smartphones. The results show that DeMiCPU can achieve 99.7% precision and recall on average, and 99.8% precision and recall for the 30 identical devices, with a fingerprinting time of 0.6~s. The performance can be further improved to 99.9% with multi-round fingerprinting. In addition, we implement a prototype of DeMiCPU docker, which can effectively reduce the requirement of test points and enlarge the fingerprinting area.

scholarly journals Gait Recognition as an Authentication Method for Mobile Devices

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4110
Author(s):  
Matei-Sorin Axente ◽  
Ciprian Dobre ◽  
Radu-Ioan Ciobanu ◽  
Raluca Purnichescu-Purtan
Keyword(s):  
Data Privacy ◽  
Experimental Testing ◽  
Human Life ◽  
Gait Recognition ◽  
Sampling Rate ◽  
Motion Sensors ◽  
Sensitive Data ◽  
Recognition Mechanism ◽  
Efficient Gait ◽  
Short Time

With the rate at which smartphones are currently evolving, more and more of human life will be contained in these devices. At a time when data privacy is extremely important, it is crucial to protect one’s mobile device. In this paper, we propose a new non-intrusive gait recognition based mechanism that can enhance the security of smartphones by rapidly identifying users with a high degree of confidence and securing sensitive data in case of an attack, with a focus on a potential architecture for such an algorithm for the Android environment. The motion sensors on an Android device are used to create a statistical model of a user’s gait, which is later used for identification. Through experimental testing, we prove the capability of our proposed solution by correctly classifying individuals with an accuracy upwards of 90% when tested on data recorded during multiple activities. The experiments, conducted on a low sampling rate and at short time intervals, show the benefits of our solution and highlight the feasibility of an efficient gait recognition mechanism on modern smartphones.

Collaboration Management System between the Device based on Machine Socialization

2016 ◽  
Vol 6 (6) ◽  
pp. 3148
Author(s):  
Han Kyung Kim ◽  
In Shik Kang ◽  
Wung Jun Kim ◽  
Hoe Kyung Jung
Keyword(s):  
Management System ◽  
Smart Home ◽  
Smart Devices ◽  
Network Module ◽  
Human Intervention ◽  
Collaboration Management ◽  
Device To Device ◽  
Common Goals ◽  
Device To Device Communication ◽  
Smart Home Appliances

<p>The basis of IoT is in the interconnection and communication between different devices to achieve common goals through internet. These devices are interconnected through a network which enables communication within these devices without any direct human intervention. But with such great potential, this technology reached a road-block due to incompatibility within various manufacturers of the same type of device and proprietary standards. I started this project with this problem in mind and I have created a brand and platform independent machine socialization device manager system. In this paper, to overcome the above mentioned problem, I have utilized micro controllers to connect to various existing device to solve the problem and propose a device to device communication with collaboration management. This technology is not restricted to usage in only the new network module enabled smart devices but also this can be used to operate the existing old (not smart) home appliances. Machine socialization was made possible with the use of XML, (an internet standard schema language) which we have used to gather device, task and relationship information of all the devices to show schema information.</p>

scholarly journals Privacy protection in mobile crowd sensing: a survey

2019 ◽  
Vol 23 (1) ◽  
pp. 421-452 ◽  
Author(s):  
Yongfeng Wang ◽  
Zheng Yan ◽  
Wei Feng ◽  
Shushu Liu
Keyword(s):  
Privacy Protection ◽  
Data Privacy ◽  
Large Scale ◽  
System Structure ◽  
Smart Devices ◽  
Future Research ◽  
Sensitive Information ◽  
Mobile Crowd Sensing ◽  
Crowd Sensing ◽  
Mobile Crowd

AbstractThe unprecedented proliferation of mobile smart devices has propelled a promising computing paradigm, Mobile Crowd Sensing (MCS), where people share surrounding insight or personal data with others. As a fast, easy, and cost-effective way to address large-scale societal problems, MCS is widely applied into many fields, e.g., environment monitoring, map construction, public safety, etc. Despite the popularity, the risk of sensitive information disclosure in MCS poses a serious threat to the participants and limits its further development in privacy-sensitive fields. Thus, the research on privacy protection in MCS becomes important and urgent. This paper targets the privacy issues of MCS and conducts a comprehensive literature research on it by providing a thorough survey. We first introduce a typical system structure of MCS, summarize its characteristics, propose essential requirements on privacy on the basis of a threat model. Then, we survey existing solutions on privacy protection and evaluate their performances by employing the proposed requirements. In essence, we classify the privacy protection schemes into four categories with regard to identity privacy, data privacy, attribute privacy, and task privacy. Besides, we review the achievements on privacy-preserving incentives in MCS from four viewpoints of incentive measures: credit incentive, auction incentive, currency incentive, and reputation incentive. Finally, we point out some open issues and propose future research directions based on the findings from our survey.

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