{'fraction_non_alphanumeric': 0.028858218318695106, 'fraction_numerical': 0.0, 'mean_word_length': 5.333333333333333, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
User density and spatial cloaking algorithm selection: Improving privacy protection of mobile users

Data sharing and privacy protection of mobile users have always been a challenge to research and development, as well as commercial and enterprise deployment of the Global Positioning System (GPS) and location-based mobile applications. The concepts of k-anonymity, two spatial cloaking algorithms — Nearest Neighbor Cloak (NNC) and Hilbert Cloak (HC) — that utilize k-anonymity, as well as user density's impacts on the performance are discussed in this paper. The proposed research seeks to examine and adopt an adaptive scheme that utilizes these cloaking algorithms to improve security, privacy protection and performance of a system, using k-anonymity to generate the k-ASR in an anonymizer.