A Study on Static Analysis Model of Mobile Application for Privacy Protection

Traditional static analysis methods such as formal validation and theorem proving were used to analyze protocols security previously. These methods can not measure and evaluate actual security of protocols accurately for the setting and suppose are far from the actual conditions. This paper proposes a new dynamic protocol analysis model. The system based on the model can be used to active test in actual running conditions, analyze known protocols security, integrity, robustness, and analyze unknown protocols online, provide support for protocol designer. The systems structure, working flow and implementation of key modules are described. The experimental results validate the validity of the models design.

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Persepsi Peserta Terhadap Aplikasi Mobile JKN Berbasis Technology Acceptance Model Di Klinik Pratama Surya Medika Semarang

Jurnal Ilmiah Manajemen Kesatuan ◽

10.37641/jimkes.v9i2.793 ◽

2021 ◽

Vol 9 (2) ◽

pp. 191-200

Author(s):

Harsono Harsono ◽

Sigit Sugiharto ◽

Rinayati Rinayati

Keyword(s):

Technology Acceptance ◽

Technology Acceptance Model ◽

Mobile Application ◽

Ease Of Use ◽

Perceived Usefulness ◽

Perceived Ease Of Use ◽

Analysis Model ◽

Cross Sectional ◽

Quantitative Descriptive ◽

Acceptance Model

The JKN Mobile Application is an application designed by BPJS Health to balance the current increasing use of mobile technology and to provide easy acces and convenience for JKN participants online. This study aims to determine the extent to which JKN participants perceptions of the JKN Mobile Application are measured using the TAM (Technology Acceptance Model) analysis model based on the usefulness (perceived usefulness) and ease of use (perceived ease of use) This research is a quantitative descriptive study using a cross-sectional research design with a research sample of 38 JKN participants registered at the Pratama Surya Medika Clinic Semarang through random sampling with the research instrument used is a questionnaire. The results showed that the overall JKN mobile application was rated 82,5% as very useful and 84% very easy to operate so it was very helpful and supportive for JKN participants in getting health services at the Pratama Surya Medika Clinic Semarang Keywords: JKN Participant Perception, JKN Mobile Application, TAM (Technology Acceptance Model)

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Static Analysis Model For Assessing Source Codes With TFIDF

10.1109/fie49875.2021.9637183 ◽

2021 ◽

Author(s):

Ricardo Lemos De Souza ◽

Fabiana Zaffalon Ferreira ◽

Silvia Da Silva Botelho

Keyword(s):

Static Analysis ◽

Analysis Model ◽

Source Codes

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What I Say Means What I Do: Risk Concerns and Mobile Application-Selection Behaviors

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/00187208211004288 ◽

2021 ◽

pp. 001872082110042

Author(s):

Jing Chen ◽

Huangyi Ge ◽

Ninghui Li ◽

Robert W. Proctor

Keyword(s):

Privacy Protection ◽

Mobile Application ◽

Mobile Apps ◽

Selection Task ◽

Clear Understanding ◽

Privacy Concerns ◽

Weakest Link ◽

Personalized Risk ◽

Risk Categories ◽

Over Time

Objective The goal of this study was to examine the relation between users’ reported risk concerns and their choice behaviors in a mobile application (app) selection task. Background Human users are typically regarded as the weakest link in cybersecurity and privacy protection; however, it is possible to leverage the users’ predilections to increase security. There have been mixed results on the relation between users’ self-reported privacy concerns and their behaviors. Method In three experiments, the timing of self-reported risk concerns was either a few weeks before the app-selection task (pre-screen), immediately before it (pre-task), or immediately after it (post-task). We also varied the availability and placement of clear definitions and quizzes to ensure users’ understanding of the risk categories. Results The post-task report significantly predicted the app-selection behaviors, consistent with prior findings. The pre-screen report was largely inconsistent with the reports implemented around the time of the task, indicating that participants’ risk concerns may not be stable over time and across contexts. Moreover, the pre-task report strongly predicted the app-selection behaviors only when elaborated definitions and quizzes were placed before the pre-task question, indicating the importance of clear understanding of the risk categories. Conclusion Self-reported risk concerns may be unstable over time and across contexts. When explained with clear definitions, self-reported risk concerns obtained immediately before or after the app-selection task significantly predicted app-selection behaviors. Application We discuss implications for including personalized risk concerns during app selection that enable comparison of alternative mobile apps.

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Nonlinear Static Analysis and Structural Optimization of Rigid Clamp Band Connection Device between Launch Vehicle and Satellite

Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University ◽

10.1051/jnwpu/20203851122 ◽

2020 ◽

Vol 38 (5) ◽

pp. 1122-1128

Author(s):

Xin Guo ◽

Shiyao Zhu ◽

Guanri Liu ◽

Bin Yu ◽

Qiaofei Zhang ◽

...

Keyword(s):

Static Analysis ◽

Structural Strength ◽

Axial Loading ◽

Launch Vehicle ◽

Parametric Modeling ◽

Nonlinear Static Analysis ◽

Analysis Model ◽

Section Shape ◽

Heavy Lift ◽

Stiffness Characteristics

The Rigid Clamp Band Connection Device (RCBCD) is a novel satellite-rocket connection method adapted to the heavy lift trend of the launch vehicle. The static analysis model for the Rigid Clamp Band (RCB) and the Docking Ring (DR) under preloading state is established, and the structural strength and connection stiffness characteristics under the axial loading are analyzed, and the axisymmetric equivalent and parametric modeling techniques are combined to optimize the section shape parameter, which improves the overall connection performance. The results show that the structural stress concentrated on the "line-to-face" contact position between RCB and DR. Increasing the axial dimension of RCB, reducing the V-type angle and deepening the occlusion depth of RCB and DR can effectively improve the connection rigidity of RCB. By optimizing the section shape, the connection performance of RCBCD can be improved by above 70% under the structural strength and mass constraints.

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A Static Analysis Model for Implicit Information Leakage in Android Application

2018 IEEE 18th International Conference on Communication Technology (ICCT) ◽

10.1109/icct.2018.8599963 ◽

2018 ◽

Author(s):

Hongsheng Cao ◽

Jian Jiao ◽

Denghui Li

Keyword(s):

Static Analysis ◽

Information Leakage ◽

Android Application ◽

Analysis Model ◽

Implicit Information

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Systematic Mutation-Based Evaluation of the Soundness of Security-Focused Android Static Analysis Techniques

ACM Transactions on Privacy and Security ◽

10.1145/3439802 ◽

2021 ◽

Vol 24 (3) ◽

pp. 1-37

Author(s):

Amit Seal Ami ◽

Kaushal Kafle ◽

Kevin Moran ◽

Adwait Nadkarni ◽

Denys Poshyvanyk

Keyword(s):

Static Analysis ◽

Mobile Application ◽

Application Security ◽

Android Apps ◽

Analysis Tools ◽

Security Research ◽

Private Data ◽

Depth Analysis ◽

Application Analysis ◽

And Performance

Mobile application security has been a major area of focus for security research over the course of the last decade. Numerous application analysis tools have been proposed in response to malicious, curious, or vulnerable apps. However, existing tools, and specifically, static analysis tools, trade soundness of the analysis for precision and performance and are hence sound y . Unfortunately, the specific unsound choices or flaws in the design of these tools is often not known or well documented, leading to misplaced confidence among researchers, developers, and users. This article describes the Mutation-Based Soundness Evaluation (μSE) framework, which systematically evaluates Android static analysis tools to discover, document, and fix flaws, by leveraging the well-founded practice of mutation analysis. We implemented μSE and applied it to a set of prominent Android static analysis tools that detect private data leaks in apps. In a study conducted previously, we used μSE to discover 13 previously undocumented flaws in FlowDroid, one of the most prominent data leak detectors for Android apps. Moreover, we discovered that flaws also propagated to other tools that build upon the design or implementation of FlowDroid or its components. This article substantially extends our μSE framework and offers a new in-depth analysis of two more major tools in our 2020 study; we find 12 new, undocumented flaws and demonstrate that all 25 flaws are found in more than one tool, regardless of any inheritance-relation among the tools. Our results motivate the need for systematic discovery and documentation of unsound choices in soundy tools and demonstrate the opportunities in leveraging mutation testing in achieving this goal.

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