Abstract

Phishing is networked theft in which the main motive of phishers is to steal any person’s private information, its financial details like account number, credit card details, login information, payment mode information by creating and developing a fake page or a fake web site, which look completely authentic and genuine. Nowadays email phishing has become a big threat to all, and is increasing day by day. Moreover detection of phishing emails have been considered an important research issue as phishing emails have been increasing day by day. Various techniques have been introduced and applied to deal with such a big issue. The major objective of this research paper is giving a detailed description on the classification of phishing emails using the natural language processing concepts. NLP (natural language processing) concepts have been applied for the classification of emails, along with that accuracy rate of various classifiers have been calculated. The paper is presented in four sections. An introduction about phishing its types, its history, statistics, life cycle, motivation for phishers and working of email phishing have been discussed in the first section. The second section covers various technologies of phishing- email phishing and also description of evaluation metrics. An overview of the various proposed solutions and work done by researchers in this field in form of literature review has been presented in the third section. The solution approach and the obtained results have been defined in the fourth section giving a detailed description about NLP concepts and working procedure.

Highlights

  • Phishing is basically a networked theft in which the main motive of phishers is to steal any person’s private information, its financial details like account number, credit card details, login information, payment mode info and many more

  • This section gives a description on the history and statistics, life cycle, motivation for phishers, email phishing and its working

  • Given below the various evaluation metrics: True positive rate (TPR): It states the ratio of phishing mails detected with respect to all malicious and genuine mails

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Summary

INTRODUCTION

Phishing is basically a networked theft in which the main motive of phishers is to steal any person’s private information, its financial details like account number, credit card details, login information, payment mode info and many more. Many fake sites are available and are used by phishers to fraud people by sending fake mails and steal their private info or make them a victim of email phishing by sending any kind of malicious link or pop-up in mails that the user will unknowingly open and got stuck in their trap. It is a form of fraud in which the attacker represents himself to be genuine entity and attack via communication channels. The malicious content to target an upper level person like the CEO or the person's role in the company is created

BACKGROUND
EVALUATION METRICES
TAXONOMY OF PHISHING ATTACKS
Spoofed websites
LITERATURE REVIEW
Preprocessing of Data
Generation of Datasets for Testing and Training the Model
Results
CONCLUSION
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