{'fraction_non_alphanumeric': 0.016646848989298454, 'fraction_numerical': 0.0, 'mean_word_length': 5.2835820895522385, '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}}
Performance Analysis of Data Leakage Detection System

Data Leakage is the biggest issue, in this digital world. Big organizations keep consolidated data of personal information of employees, users, customers, clients, etc. Even there are many algorithms used for privacy preservation to protect the sensitive or confidential data, data leakage becomes an uncontrolled threat in the digital world. The purpose of this research is to analyze the performance of data leakage detection system used in the information retrieval system in web application. In this paper, we consider the models such vector space model and Interaction information retrieval model. The idea is to check the semantically similar documents in the Web for leaked data. The result inferred that Interaction Information Retrieval Model is better than Vector Space Model.