SaTC: CORE: Small: Enabling Systematic Evaluation of the Soundness of Android Security Analysis Techniques

SaTC：CORE：小型：支持对 Android 安全分析技术的健全性进行系统评估

• 批准号: 1815336
• 负责人: Adwait Nadkarni
• 金额: $ 50万
• 依托单位: College of William and Mary
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1815336&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Enabling; Systematic

Mobile devices have become the fabric of our current consumer computing landscape, driven by the diverse "apps" they support, which allow users to carry out complex computing tasks. These devices and apps have become deeply personal, and as such have access to privacy-sensitive resources and information. To prevent misuse of this access, it is imperative to understand the challenges in securing mobile apps, and in effect, the true capabilities of current approaches for security analysis. The first line of defense against malicious applications are tools that analyze applications to detect security vulnerabilities or malicious behavior, ideally before apps are published to application markets. It is important for such tools to be "sound", i.e., to detect all instances of bad behavior in the application being analyzed. Prior work has indicated that such tools may often sacrifice soundness for practical reasons (e.g., for a reasonable analysis time), leading to tools that are soundy (i.e., mostly sound, but with some unsound assumptions). However, the effectiveness of these security-focused program analysis techniques is not well understood, as the unsound assumptions may not be known beyond a small community of experts, leading to a false sense of security among the users of such tools. This research develops a framework for systematically evaluating existing security techniques to uncover previously unknown unsound assumptions. The methodology developed in the course of this research has the potential for a large economic and societal impact, as improving security tools improves the vetting of mobile applications and prevents or mitigates the loss or theft of private information. Moreover, while the far-reaching impact of this work will be in increasing reliability of applications for end users, more immediate impact can be seen in educational activities. That is, this project incorporates into software engineering and security courses the best-practices for secure mobile application development, and novel security evaluation techniques developed via this project, while disseminating awareness regarding the dangers of unsound analyses to the broader research community.This research project develops a new methodology for assessing security-focused static analysis tools for Android, by adopting the principles of mutation analysis from the field of functional software testing to systematically identify unsound assumptions. This methodology consists of three major components: (1) empirical derivation of specifications for security-focused mutation operators (i.e., security operators) through the examination of claims by security analysis tools, security bugs in open source apps, and malware samples; (2) the instantiation and seeding operators in the context of the security technique being evaluated using context-specific mutation schemes; and (3) expansion of the sound core of static program analysis tools for Android by running static analysis tools on mutants and detecting and addressing vulnerabilities. This research project cuts across the complementary disciplines of computer security and software engineering and tackles several open research questions that are currently unaddressed in both disciplines. More specifically, this project builds upon the theoretical underpinnings of mutation analysis, which aims at evaluating the efficacy of functional software tests and instantiates them in a security-focused context.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

移动的设备已经成为我们当前消费者计算领域的结构，由它们支持的各种“应用程序”驱动，这些应用程序允许用户执行复杂的计算任务。 这些设备和应用程序已经变得非常个人化，因此可以访问隐私敏感的资源和信息。 为了防止滥用这种访问权限，必须了解保护移动的应用程序的挑战，以及当前安全分析方法的实际功能。防御恶意应用程序的第一道防线是分析应用程序以检测安全漏洞或恶意行为的工具，理想情况下，在应用程序发布到应用程序市场之前。重要的是这些工具要“健全”，即，以检测正在分析的应用程序中的所有不良行为实例。先前的工作已经表明，这种工具通常可能出于实际原因而牺牲可靠性（例如，对于合理的分析时间），导致可靠的工具（即，大部分是合理的，但有一些不合理的假设）。然而，这些以安全为中心的程序分析技术的有效性还没有得到很好的理解，因为不合理的假设可能不知道超出了一个小社区的专家，导致错误的安全感，这些工具的用户之间。这项研究开发了一个框架，用于系统地评估现有的安全技术，以发现以前未知的不合理的假设。在这项研究过程中开发的方法有可能产生巨大的经济和社会影响，因为改进安全工具可以改善对移动的应用程序的审查，并防止或减轻私人信息的丢失或被盗。此外，虽然这项工作的深远影响将是为最终用户提高应用程序的可靠性，但在教育活动中可以看到更直接的影响。也就是说，该项目将安全移动的应用程序开发的最佳实践和通过该项目开发的新型安全评估技术纳入软件工程和安全课程，同时向更广泛的研究社区传播有关不合理分析的危险性的意识。该研究项目开发了一种新的方法，用于评估Android的安全性为重点的静态分析工具，通过采用功能软件测试领域的突变分析原理，系统地识别不合理的假设。该方法由三个主要部分组成：（1）经验推导的规格为安全为重点的变异算子（即， 安全操作符），通过检查安全分析工具的声明、开源应用程序中的安全漏洞和恶意软件样本;（2）在使用特定于上下文的变异方案评估的安全技术的上下文中的实例化和播种操作符;以及（3）通过在突变体上运行静态分析工具并检测和寻址，扩展Android静态程序分析工具的声音核心漏洞该研究项目跨越计算机安全和软件工程的互补学科，并解决了两个学科目前未解决的几个开放的研究问题。更具体地说，该项目建立在突变分析的理论基础之上，旨在评估功能软件测试的有效性，并在以安全为中心的环境中将其实例化。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Discovering Flaws in Security-Focused Static Analysis Tools for Android using Systematic Mutation

• 发表时间: 2018-06
• 期刊: ArXiv
• 作者: R. Bonett;Kaushal Kafle;Kevin Moran;Adwait Nadkarni;D. Poshyvanyk

DeepMutation: A Neural Mutation Tool

DeepMutation：神经突变工具

• 发表时间: 2020
• 期刊: 2020 IEEE/ACM 42nd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion
• 作者: Tufano, Michele and

µSE: Mutation-Based Evaluation of Security-Focused Static Analysis Tools for Android

µSE：基于突变的 Android 安全静态分析工具评估

• DOI: 10.1109/icse-companion52605.2021.00034
• 发表时间: 2021
• 期刊: 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion
• 作者: Ami, Amit Seal;Kafle, Kaushal;Nadkarni, Adwait;Poshyvanyk, Denys;Moran, Kevin
• 通讯作者: Moran, Kevin

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

• DOI: 10.1145/3439802
• 发表时间: 2021-02
• 期刊: ACM Transactions on Privacy and Security (TOPS)
• 作者: Amit Seal Ami;Kaushal Kafle;Kevin Moran;Adwait Nadkarni;D. Poshyvanyk

Towards a Natural Perspective of Smart Homes for Practical Security and Safety Analyses

• DOI: 10.1109/sp40000.2020.00062
• 发表时间: 2020-05
• 期刊: 2020 IEEE Symposium on Security and Privacy (SP)
• 作者: Sunil Manandhar;Kevin Moran;Kaushal Kafle;Ruhao Tang;D. Poshyvanyk;Adwait Nadkarni