EZIOKWU MICHAEL CHIBUIKE

This project is to evaluate privacy policies in mobile applications. It revealed Assess the clarity, readability, and structure of privacy policies used in selected mobile applications, evaluate the consistency between the stated privacy policies and the actual data handling practices of the mobile applications, identify specific areas within mobile privacy policies where vague or misleading terms are commonly used, examine the extent to which user input data is collected, processed, and shared without clear disclosure in the privacy statements, use Python-based tools to automate the detection and analysis of discrepancies between privacy policies and app behaviours, recommend practical improvements for making mobile application privacy policies more transparent, accurate, and user-friendly. This study designed and evaluation approach to examine how mobile applications present and apply their privacy policies

This project is to evaluate privacy policies in mobile applications. It revealed Assess the clarity, readability, and structure of privacy policies used in selected mobile applications, evaluate the consistency between the stated privacy policies and the actual data handling practices of the mobile applications, identify specific areas within mobile privacy policies where vague or misleading terms are commonly used, examine the extent to which user input data is collected, processed, and shared without clear disclosure in the privacy statements, use Python-based tools to automate the detection and analysis of discrepancies between privacy policies and app behaviors, recommend practical improvements for making mobile application privacy policies more transparent, accurate, and user-friendly. This study designed and evaluation approach to examine how mobile applications present and apply their privacy policies. Selected mobile apps were reviewed based on their popularity and relevance to everyday users. Their privacy policies were extracted and assessed for clarity, length, and language. Python scripts were then used to carry out static and dynamic analysis on these apps. The static part inspected permissions and data access points declared within the app files, while the dynamic part monitored how the app behaves when in use, especially in handling user data. Any mismatch between what is written in the privacy policy and what the app does will be recorded and analyzed. Focus was also be placed on how user input data is managed, as this is often not clearly addressed in policy statements. Results were compared across apps from different categories to detect patterns or risks that repeat across multiple apps