Blockchain and Machine Learning for Predictive Policing and Crime Pattern Analysis
Shashi Prakash Dwivedi, Modi Himabindu, Valureddi Revathi, Manish Gupta, Neeraj Patel, Muntather Almusawi · 2024
Crime pattern analysis and other forms of predictive policing are becoming indispensable tools for today's police forces. Hybrid Blockchain-Machine Learning Predictive Policing (HBL-PP) is a new method introduced by this study that aims to transform the sector by bringing together the best features of blockchain technology and machine learning algorithms. SecureCrimeChain guarantees the safe handling of crime-related data, while Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for advanced crime pattern analysis in HBL-PP. When compared to conventional approaches, HBL-PP performs much better in experimental evaluations. SecureCrimeChain guarantees the best degree of accuracy, precision, recall, and F1 score, outperforming other techniques. DeepCrimeNet has comparable performance and comes in a close second. FairPredict Pro, although fairness-aware, maintains a balance between equity and prediction accuracy.