Enhancing Networking Cipher Algorithms with Natural Language

TL;DR

This paper surveys networking cipher algorithms and proposes integrating natural language processing (NLP) as an additional protective layer, leveraging language patterns to enhance encryption security.

Contribution

It introduces novel methods for using NLP to strengthen encryption by exploiting language characteristics and discusses NLP as both a vulnerability and a protective tool in networking.

Findings

NLP can identify vulnerabilities in encryption models.

Language patterns can be used to reinforce stream cipher security.

NLP integration offers a new layer of protection against attacks.

Abstract

This work provides a survey of several networking cipher algorithms and proposes a method for integrating natural language processing (NLP) as a protective agent for them. Two main proposals are covered for the use of NLP in networking. First, NLP is considered as the weakest link in a networking encryption model; and, second, as a hefty deterrent when combined as an extra layer over what could be considered a strong type of encryption -- the stream cipher. This paper summarizes how languages can be integrated into symmetric encryption as a way to assist in the encryption of vulnerable streams that may be found under attack due to the natural frequency distribution of letters or words in a local language stream.