Mrs D Kalyani, Dande Durga, B. Mouthreyini Mukarji, CH Namratha
Abstract
Rising urban crime and unpredictable security threats have increased the need for intelligent personal safety solutions. Crime-encrypted navigation systems integrate real-time crime data, geospatial analytics, and encryption techniques to provide safer route recommendations while protecting user privacy. This approach analyzes historical crime patterns, live incident reports, and environmental risk factors to dynamically guide individuals through low-risk paths. End-to-end encryption ensures that location data, travel history, and personal identifiers remain secure against unauthorized access and misuse. yy combining secure data transmission with predictive risk assessment, crimeencrypted navigation enhances situational awareness, minimizes exposure to highrisk areas, and supports informed decisionmaking without compromising confidentiality. The system demonstrates potential applications in urban mobility, emergency response, and personal safety, contributing to smarter and more secure navigation frameworks.
In this work, we proposed a crime-aware encrypted navigation system designed to enhance personal safety while preserving user privacy. yy integrating historical and real-time crime data with geospatial routing algorithms, the system generates optimal paths that minimize exposure to high-crime areas. The use of advanced encryption techniques ensures that user locations, routes, and movements remain confidential, preventing potential misuse or data breaches. Experimental evaluation demonstrates that the proposed system effectively balances safety, route efficiency, and computational performance, making it a practical solution for urban navigation applications where personal security is a critical concern.
The system can be further improved by incorporating predictive analytics and machine leaming techniques to forecast potential crime hotspots in real time. Integration with 10T devices and smart city infrastructure can provide dynamic updates, such as sudden crime alerts or road closures. Additionally, blockchain technology can be employed to securely store and verify crime data, enhancing transparency and trustworthiness. Future enhancements may also include federated learning approaches to continuously improve routing accuracy without compromising user privacy, as well as emergency response integration to provide instant assistance in case of personal safety threats.
Crime-aware encrypted navigation for personal safety has strong future potential as urban areas become more complex and safety concerns increase. Such systems can use artificial intelligence and real-time crime data to suggest safer routes while continuously adapting to changing risk conditions. yy applying strong encryption techniques, these systems protect users’ location and personal information from misuse or tracking, ensuring privacy along with safety. In the future, integration with smart city infrastructure, emergency services, and wearable devices can further enhance real-time response during critical situations. With growing awareness of personal security and data privacy, crime-aware encrypted navigation is expected to play an important role in improving safe mobility for individuals, especially vulnerable groups, in modern cities.
References
1.Safe Routing
Levy et al., “SafeRoute: Learning to Navigate Streets Safely in an Urban Environment”
2.Crime-Avoiding Routing Navigation
Rishe, Sadjadi & Adjouadi, “Crime-Avoiding Routing Navigation” (2024)
3.Navigation System for Safe Routing
Kaur et al., ”A Navigation System for Safe Routing” (IEEE MDM 2021)
4.Review Articles on Safety in Navigation
Sarde et al., “Enhancing Urban Navigation: A Review of Safety-Driven Route Search (2025).
5.0SRM-CCTV: Privacy-Aware Routing
Sintonen et al., “OSRM-CCTV: Open-source CCTV-aware routing and navigation system for privacy, anonymity and safety” (2021 Preprint)
6.Secure Navigation Processing
Aggarwal et al., “Enhancing Privacy and Security of Autonomous UAV Navigation (2024 Preprint)
7.Machine-Learning & Crime Data Systems for Safety
Nerkar et al., “Safe Route Recommendation System” (IJSRD 2024).
8.Crime Data-Driven Navigation Projects
“SMART URyAN NAVIGATION: A CRIME
DATA-DRIVEN” (Student Project Synopsis)
How to Cite This Paper
Mrs D Kalyani, Dande Durga, B. Mouthreyini Mukarji, CH Namratha (2026). Crime Aware Encrypted Navigation App For Personal Safety. International Journal of Computer Techniques, 13(3). ISSN: 2394-2231.
