LSTM Based Self-Defending AI Chatbot Providing Anti-Phishing

Sai Sreewathsa Kovalluri,Aravind Ashok, Hareesh Singanamala,Prabaharan P.

ASIA CCS '18: ACM Asia Conference on Computer and Communications Security Incheon Republic of Korea June, 2018(2018)

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Abstract
Email services have to put through a lot of effort in fighting spam emails. Most of the efforts go in for detecting and filtering spam emails from benign emails. On the other front, people are educated by banks and other organizations on the awareness of such emails. These approaches are essentially passive in nature, in countering spam attacks where the attacker is not directly engaged by the adversary. Despite all these efforts, many innocent people fall for such attacks leading them to share their account details or lose a large sum of money. We propose an AI based system, that is self-aware and self-defending, which sends coherent replies to spammers with the aim of consuming their time. To make it more difficult for spammers we reply from algorithmically generated mail servers. Also, to avoid simple match filtering of mails by spammers, we make the replies different from each other and genuine, by using a language model trained by LSTM to form sentences in natural language depending upon the context of the email.
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Key words
Spam emails, Self-Defending system, Language model, deep learning, LSTM, Chatbot
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