# Context-Sensitive Malicious Spelling Error Correction

## TL;DR

This paper introduces a context-sensitive method for correcting malicious spelling errors that disrupt cyber-environment control tools, demonstrating superior performance over existing spell checkers in profanity and spam detection.

## Contribution

It presents a novel context-aware approach using word embeddings for malicious spelling correction, improving detection accuracy in cyber-security applications.

## Key findings

- Malicious misspellings significantly impair detection systems.
- The proposed method outperforms state-of-the-art spell checkers.
- Enhanced correction improves cyber-environment control effectiveness.

## Abstract

Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection. In this paper, we focus on malicious spelling correction, which requires an approach that relies on the context and the surface forms of targeted keywords. In the context of two applications--profanity detection and email spam detection--we show that malicious misspellings seriously degrade their performance. We then propose a context-sensitive approach for malicious spelling correction using word embeddings and demonstrate its superior performance compared to state-of-the-art spell checkers.