{'fraction_non_alphanumeric': 0.01, 'fraction_numerical': 0.0, 'mean_word_length': 4.853801169590644, '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}}
Analysis of Malware Propagation in Twitter

Malware propagation in social networks is a potential risk that has not been well-studied yet as there are no formal threat models for social networks. In this paper we investigate the vulnerability and cost of spreading malware via Twitter. Towards this end we present three specific attack scenarios targeted for Twitter and systematically analyze the cost of staging each of these attacks. Our analysis presents the first step for understanding the threats on the security of a class of social networks. We identify the attack related parameters and verify these parameters by testing the attack on a Net Logo based simulator. Our analysis indicates that the cost of staging attacks to infect users of Twitter is low and that the proposed attack scenarios are plausible. Further, even with a low degree of connectivity and a low probability of clicking links, Twitter and its structure can be exploited by such attacks to infect many users with malware.