Risk-Aware Mobile App Security Testing: Safeguarding Sensitive User Inputs

Trishla Shah, Raghav V. Sampangi, Angela Siegel
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Abstract

Over the years, mobile applications have brought about transformative changes in user interactions with digital services. Many of these apps however, are free and offer convenience at the cost of exchanging personal data. This convenience, however, comes with inherent risks to user privacy and security. This paper introduces a comprehensive methodology that evaluates the risks associated with sharing sensitive data through mobile applications. Building upon the Hierarchical Weighted Risk Scoring Model (HWRSM), this paper proposes an evaluation methodology for HWRSM, keeping in mind the implications of such risk scoring on real-world security scenarios. The methodology employs innovative risk scoring, considering various factors to assess potential security vulnerabilities related to sensitive terms. Practical assessments involving diverse set of Android applications, particularly in data-intensive categories, reveal insights into data privacy practices, vulnerabilities, and alignment with HWRSM scores. By offering insights into testing, validation, real-world findings, and model effectiveness, the paper aims to provide practical considerations to mobile application security discussions, facilitating informed approaches to address security and privacy concerns.
具有风险意识的移动应用程序安全测试:保护敏感的用户输入
多年来,移动应用程序为用户与数字服务的互动带来了变革。然而,这些应用程序中有许多都是免费的,它们以交换个人数据为代价提供便利。然而,这种便利也带来了用户隐私和安全方面的固有风险。本文介绍了一种综合方法,用于评估通过移动应用程序共享敏感数据所带来的风险。在分层加权风险评分模型(HWRSM)的基础上,本文提出了 HWRSM 的评估方法,同时考虑到这种风险评分对现实世界安全场景的影响。该方法采用创新的风险评分法,考虑各种因素来评估与敏感术语相关的潜在安全漏洞。涉及各种 Android 应用程序(尤其是数据密集型类别)的实际评估揭示了数据隐私实践、漏洞以及与 HWRSM 评分的一致性。通过对测试、验证、实际发现和模型有效性的深入分析,本文旨在为移动应用安全讨论提供实用的考虑因素,促进采用知情的方法来解决安全和隐私问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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