AndroidSecurityFirstEvaluationbyMJs.pptx

Android Security PPT

1. B. Tech Major Project Evaluation-1, VII Sem Preventing Android Based Attack through Reconning Attack Framework and CVE Presented by : Mairajuddeen (2022001250) Md Adnan Alam (2022000344) Md Manshaul Haque (2021434581) Under the Supervision of:- Ms . Saptadeepa Kalita , Assistant Professor, CSE Co- Supervision of:- Mr. Avina sh Kumar, Assistant Professor, CSE DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING SHARDA SCHOOL OF ENGINEERING AND TECHNOLOGY August , 2024

2. 01 Introduction 02 Problem Statement 03 Motivation 04 Objective 05 Team Size and Project Planning 06 Guide Approval 07 Conclusion 08 References Table Of Contents Android Security Literature Review 09

3. Table of Contents Guide Approval Introduction Problem Statement Motivation Objective Literature Review Team Size and Project Planning Guide Approval Conclusion References

4. Guide Approval

5. Introduction Android Based Attacks Android devices have become integral parts of our lives, facilitating communication, productivity, and entertainment. However, with increased usage comes heightened security risks, as Android platforms are frequent targets for cyber attacks. This presentation introduces our project, focused on enhancing Android security through innovative approaches.

6. Importance of Android Security Overview: Android devices have become ubiquitous in our daily lives, serving as essential tools for communication, productivity, and entertainment. Statistics: The number of Android malware variants continues to rise, with millions of new threats detected each year. Consequences: Unauthorized access to sensitive information such as personal data, financial details, and login credentials. Financial loss through fraudulent transactions, identity theft, or ransom demands.

7. Problem Statement OS vulnerabilities : Flaws in the Android operating system that can be exploited to gain unauthorized access or execute arbitrary code. App vulnerabilities : Security weaknesses in third-party applications installed on Android devices, often exploited to steal sensitive data or hijack device functionality. Network vulnerabilities: Weaknesses in network protocols, configurations, or communication channels that can be exploited to intercept, manipulate, or disrupt data traffic. Reputational damage: Loss of trust and credibility among users, customers, and partners, leading to decreased market share, customer churn, and brand devaluation. Android Security LandScape

8. The Android ecosystem is characterized by its diversity, comprising numerous device manufacturers, software versions, and customization layers (e.g., OEM skins). This heterogeneity introduces challenges in ensuring consistent security measures across the Android ecosystem, as updates and patches may be delayed or fragmented. Many Android users are unaware of the potential security risks associated with their devices, leading to complacency and neglect of security best practices. Additionally, developers may lack sufficient knowledge or training in secure coding practices, resulting in the proliferation of vulnerable applications on the Google Play Store. Challenges in Android Security Problem Statement

9. MOTIVATION The pervasive integration of Android devices into our daily lives has revolutionized the way we communicate, work, and interact with technology. However, this widespread adoption has also made Android platforms prime targets for malicious actors seeking to exploit vulnerabilities and compromise user privacy and security. With the exponential growth of cyber threats targeting Android-based systems, there is an urgent need for proactive measures to defend against evolving attack vectors. The motivation behind our project stems from the recognition of the critical importance of securing Android ecosystems against reconnaissance-based attacks and known vulnerabilities. Reconnaissance, the initial phase of a cyber-attack where adversaries gather information about potential targets, serves as a precursor to more sophisticated exploits and breaches. By comprehensively understanding and mitigating reconnaissance tactics employed by attackers, we can disrupt their malicious intent and fortify Android defenses.

10. Objectives (Project Goals) Project Goals: Develop a comprehensive framework for preventing Android-based attacks through proactive measures. Integrate advanced reconnaissance techniques and CVE mitigation strategies to enhance Android security posture. Eg . CVE-2023-20951 and CVE-2023-20954 Key Objectives: Identify and analyse reconnaissance tactics commonly used by attackers to gather intelligence on potential targets within Android ecosystems. Research and catalog known vulnerabilities affecting Android devices and applications, prioritizing those with the highest risk of exploitation.

11. Literature Review S.No. Year Author(s) Title Scope & Achievement Limitations 1. 2023 G. Meng et al. Assessing the Effectiveness of LLMs in Android Application Vulnerability Analysis Evaluates the use of Large Language Models for Android vulnerability analysis. May be limited by the capabilities of current LLMs. 2. 2023 S. Kumar et al. A survey on security issues, vulnerabilities and attacks in Android based smartphone Extensive survey covering 15 years of research on Android vulnerabilities and threats. May not provide in-depth analysis of specific attack frameworks. 3. 2022 A. Merlo et al. A Survey on Secure Android Apps Development Life-Cycle: Vulnerabilities and Tools Comprehensive overview of Android app development security, including tools for vulnerability detection. May not cover all recent vulnerabilities or emerging attack vectors. 4. 2022 L. Xiao and W. Xu A Survey on Android Security: Issues, Malware Penetration, and Defenses Comprehensive overview of Android security issues and defenses; Identifies key areas for future research. Focuses more on general issues rather than specific attack frameworks or CVEs. 5. 2022 S. Arzt et al. Security vulnerabilities in android applications Analyzes security vulnerabilities in Android applications. May not cover all types of vulnerabilities or attack vectors.

12. 6. 2022 W. Wang et al. Effective Android Malware Detection with a Hybrid Model Based on Deep Autoencoder and Convolutional Neural Network Proposes a hybrid model for Android malware detection. May have high computational requirements. 7. 2021 Y. Zhang and X. Luo Deep Learning Based Malware Detection on Android Introduces a deep learning approach for detecting Android malware with high accuracy. High computational cost and potential issues with model generalization. 8. 2021 A. Banerjee and S. Roy Security Analysis of Android Applications Based on CVE Data Conducts security analysis of Android applications using CVE data to identify vulnerabilities. Limited to the quality and recency of CVE data available; may miss newer vulnerabilities. 9. 2021 R. Spolaor et al. An interrogation of Android application-based privilege escalation attacks Focuses on privilege escalation attacks in Android applications. May not cover other types of attacks or defense mechanisms. 10. 2021 J. Tang et al. A Novel Hybrid Method to Analyze Security Vulnerabilities in Android Applications Proposes a hybrid method for analyzing Android app vulnerabilities. May have limitations in detecting certain types of vulnerabilities.

13. 11. 2021 L. Li et al. Static Analysis of Android Apps: A Systematic Literature Review Provides a systematic review of static analysis techniques for Android apps. Focuses only on static analysis, may miss dynamic vulnerabilities. 12. 2021 A. Narayanan et al. A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization Introduces a multi-view approach for malware detection and localization. May have limitations in detecting certain types of malware. 13. 2020 J. Kim and M. Kang Mitigation of Android Malware by Using CVE and CWE Proposes a mitigation strategy utilizing CVE and CWE for Android malware. Limited to specific types of malware; may not cover emerging threats. 14. 2020 M. Khan and S. Jain A Novel Framework for Preventing Android-Based Attacks Develops a new framework for preventing attacks on Android devices. Needs further validation and real-world testing; scope may be limited. 15. 2020 H. Chen and G. Gu Dynamic Detection of Android Malware Using CVE and CPE Proposes a dynamic detection method for Android malware integrating CVE and CPE information. May have performance overhead in real-time detection scenarios.

14. 16. 2020 A. Dmitrienko et al. Privilege Escalation Attacks on Android Comprehensive analysis of privilege escalation attacks on Android. May not provide extensive information on prevention techniques. 17. 2020 X. Liu et al. Multifeature-Based Behavior of Privilege Escalation Attack Detection Method for Android Applications Proposes a detection method for privilege escalation attacks using multiple features. May not cover all types of privilege escalation attacks. 18. 2020 K. Tam et al. The Evolution of Android Malware and Android Analysis Techniques Traces the evolution of Android malware and analysis techniques. May not provide in-depth information on specific prevention strategies. 19. 2020 H. Cai et al. DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling Proposes a method for Android malware detection and categorization. May not be effective against all types of malware. 20. 2019 W. Zhou and X. Jiang Detecting and Defending Against Android Malware Using CVE Data Uses CVE data to enhance malware detection and defense mechanisms. Relies heavily on the availability and accuracy of CVE data.

15. 16. 2020 A. Dmitrienko et al. Privilege Escalation Attacks on Android Comprehensive analysis of privilege escalation attacks on Android. May not provide extensive information on prevention techniques. 17. 2020 X. Liu et al. Multifeature-Based Behavior of Privilege Escalation Attack Detection Method for Android Applications Proposes a detection method for privilege escalation attacks using multiple features. May not cover all types of privilege escalation attacks. 18. 2020 K. Tam et al. The Evolution of Android Malware and Android Analysis Techniques Traces the evolution of Android malware and analysis techniques. May not provide in-depth information on specific prevention strategies. 19. 2020 H. Cai et al. DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling Proposes a method for Android malware detection and categorization. May not be effective against all types of malware. 20. 2019 W. Zhou and X. Jiang Detecting and Defending Against Android Malware Using CVE Data Uses CVE data to enhance malware detection and defense mechanisms. Relies heavily on the availability and accuracy of CVE data.

16. 21. 2019 J. Park and M. Park Framework for Comprehensive Analysis of Android Malware Develops a framework for comprehensive analysis of Android malware, incorporating multiple detection techniques. Complexity and resource requirements might be high for comprehensive analysis. 22. 2019 R. Mathew et al. Study of Privilege Escalation Attack on Android and its Countermeasures Analyzes privilege escalation attacks and proposes countermeasures. May not cover the most recent attack vectors. 23. 2019 M. Xu et al. Toward Engineering a Secure Android Ecosystem: A Survey of Existing Techniques Surveys existing techniques for securing the Android ecosystem. May not cover the most recent developments in attack frameworks. 24. 2019 F. Martinelli et al. A Survey on Security for Mobile Devices Provides a comprehensive survey on mobile device security. May not focus specifically on Android or reconing attack frameworks. 25. 2018 S. Wang and L. Wang A Comprehensive Study on Android Exploits and Vulnerabilities Detailed analysis of various Android exploits and vulnerabilities; suggests countermeasures. Primarily focuses on analysis rather than prevention strategies.

17. 26. 2018 K. Sharma and P. S. Rao Android Malware Detection Using Machine Learning Techniques Demonstrates the use of various machine learning techniques for effective Android malware detection. Effectiveness depends on the quality of the training data and feature selection. 27. 2018 A. Dmitrienko et al. Privilege Escalation Attacks on Android Comprehensive study of privilege escalation attacks on Android. May not provide extensive information on prevention techniques. 28. 2018 A. Sadeghi et al. A Taxonomy and Qualitative Comparison of Program Analysis Techniques for Security Assessment of Android Software Provides a taxonomy of program analysis techniques for Android security. May not cover all recent developments in analysis techniques. 29. 2018 A. Feizollah et al. AndroDialysis: Analysis of Android Intent Effectiveness in Malware Detection Analyzes the effectiveness of Android Intents in malware detection. May not cover other aspects of malware detection. 30. 2017 B. Liu and Y. Li Android Security: Threats and Countermeasures Examines a wide range of threats to Android security and proposes multiple countermeasures. Broad scope may lack depth in specific areas; focuses more on threats than on reconing frameworks and CVEs.

18. 31. 2017 D. Li and Y. Wang Advanced Persistent Threats on Android: Characterization and Detection Provides characterization of advanced persistent threats (APTs) on Android and proposes detection mechanisms. Focus on APTs might overlook other significant threats; requires constant updating of detection methods. 32. 2017 K. Tam et al. Evolution of Android Application Security and Malware Detection Traces the evolution of Android application security and malware detection. May not provide detailed information on specific attack frameworks. 33. 2017 K. Allix et al. AndroZoo: Collecting Millions of Android Apps for the Research Community Introduces AndroZoo, a large collection of Android apps for research. Does not directly address attack prevention strategies. 34. 2016 Z. Wu and Z. Yang A Survey of Mobile Malware in the Android Ecosystem Comprehensive survey of mobile malware targeting Android; identifies trends and patterns. Survey-based approach may not provide in-depth technical solutions. 35. 2016 D. Arp et al. DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket Introduces DREBIN, a method for Android malware detection. May have limitations in detecting the most recent malware variants.

19. 36. 2016 S. Arzt et al. FlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Apps Introduces FlowDroid, a static taint analysis tool for Android apps. May have limitations in analyzing dynamic behaviors. 37. 2015 Z. Yan and Q. Zhang Mobile Malware Detection for Android Smartphones Proposes an effective mobile malware detection method for Android smartphones. May require frequent updates to remain effective against new malware variants. 38. 2015 M. Lindorfer et al. ANDRUBIS - 1,000,000 Apps Later: A View on Current Android Malware Behaviors Provides insights into Android malware behaviors based on large-scale analysis. May not cover the most recent malware behaviors. 39. 2015 M. Zhang et al. AppIntent: Analyzing Sensitive Data Transmission in Android for Privacy Leakage Detection Proposes a method for detecting privacy leaks in Android apps. May not cover all types of privacy vulnerabilities. 40. 2014 W. Enck and P. McDaniel Understanding Android Security Frameworks In-depth analysis of Android security frameworks; provides insights into their effectiveness and limitations. Does not focus specifically on preventing attacks through reconing frameworks and CVEs.

20. 41. 2014 V. Rastogi et al. Caught in the Act: Observing Android App Behavior in the Wild Analyzes Android app behavior in real-world scenarios. May not provide comprehensive information on attack prevention. 42. 2014 C. Yang et al. Droid2API: Effective and Efficient Detection of Android Repackaged Applications Introduces a method for detecting repackaged Android applications. May not be effective against all types of repackaging techniques. 43. 2013 W. Enck et al. A Study of Android Application Security Provides a comprehensive study of Android application security. May not cover the most recent security issues. 44. 2012 Y. Zhou et al. Dissecting Android Malware: Characterization and Evolution Characterizes Android malware and traces its evolution. May not cover the most recent malware trends. 45. 2023 Y. Zhou et al. DroidRanger: A Systematic Approach to Detecting Malicious Android Applications Proposes a systematic approach for detecting malicious Android applications. May have limitations in detecting the most sophisticated malware.

21. What have we found? Meng et al. (2023) evaluated the use of Large Language Models (LLMs) for Android vulnerability analysis, demonstrating the potential of AI-driven approaches in security research. Kumar et al. (2023) provided an extensive survey covering 15 years of research on Android vulnerabilities and threats, offering a comprehensive view of the evolving security landscape. Wang et al. (2022) proposed a hybrid model for Android malware detection based on deep autoencoder and convolutional neural network techniques.

22. Research Gaps: The rapid evolution of attack techniques necessitates more adaptive and proactive defence mechanisms (Liu et al., 2020; Tam et al., 2020). Several gaps remain in Android security research. Many studies focus on detection rather than prevention, and there is a need for more comprehensive frameworks that integrate reconnaissance detection with vulnerability mitigation. Frameworks that works on mitigation of Attacks on Android Level Security.

23. Objectives(Expected Outcomes): Expected Outcomes: Reduction in successful Android-based attacks and security incidents through proactive defence measures. Enhanced resilience of Android ecosystems against reconnaissance tactics and known vulnerabilities. Long-Term Impact: Empowerment of individuals and organizations to defend against evolving cyber threats and safeguard Android devices and applications. Strengthening of trust and confidence in the security and reliability of Android platforms, fostering continued innovation and growth in the Android ecosystem.

24. Team Size and Project Planning Week 1-6: Project Initiation Define project objectives, scope, and deliverables. Identify key stakeholders and establish communication channels. Conduct initial risk assessment and outline mitigation strategies. Kick off project team meetings to align on goals and expectations. Week 6-8: Requirements Gathering Gather requirements for the Android-based attack prevention framework. Conduct stakeholder interviews and workshops to elicit input and feedback. Document functional and non-functional requirements, prioritizing based on importance and feasibility. Week 8-14: Research and Analysis Conduct in-depth research on reconnaissance attack techniques and CVE mitigation strategies. Analyze existing frameworks and tools for preventing Android-based attacks. Identify gaps and opportunities for innovation in the field of Android security.

25. Team Size and Project Planning Week 14-20: Design Phase Develop the architectural design of the prevention framework, outlining key components and interactions. Define data models, algorithms, and protocols for detecting and mitigating attacks. Create mockups or prototypes to visualize the user interface and user experience. Week 20-25: Resource Acquisition Procure necessary hardware, software, and infrastructure resources for project implementation. Set up research and development lab environments, including high-performance computing clusters and Android device farms. Install and configure tools and software platforms required for development and testing. Week 25-30: Development Kickoff Start development of the Android-based attack prevention framework. Assign development tasks to team members based on skills and expertise. Establish coding standards, version control procedures, and collaboration tools for efficient development workflow.

26. Team Size and Project Planning Week 30-34: Continuous Development and Integration Implement core functionalities of the prevention framework, focusing on reconnaissance detection and CVE mitigation. Conduct regular code reviews and integration tests to ensure code quality and compatibility. Iterate on development based on feedback from stakeholders and testing results. Week 34-38: Testing and Quality Assurance Conduct comprehensive testing of the prevention framework to validate functionality, performance, and security. Perform penetration testing and vulnerability assessments to identify and remediate any weaknesses. Document test cases, results, and issues for tracking and resolution. Week 38-40: Documentation and Reporting Prepare documentation for the prevention framework, including user manuals, technical specifications, and release notes. Generate progress reports and status updates for stakeholders, highlighting key achievements, challenges, and next steps. Finalize project documentation and deliverables for review and approval.

27. Conclusion In conclusion, our project represents a significant step towards addressing the pressing challenges of Android security. By developing a comprehensive framework for preventing Android-based attacks through proactive measures. The importance of securing Android platforms cannot be overstated, given their widespread adoption and integral role in our daily lives. With the rise of sophisticated cyber attacks targeting Android devices. In conclusion, our project represents a proactive approach to Android security that aims to make meaningful contributions to the ongoing efforts to protect against cyber threats.

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