Advanced Machine Learning Approach for Suspicious Coded Message Detection using Enigma Cipher

Abstract

Framework to avoid global crime especially terrorist attacks, bomb blasts, and drone attacks all major and minor attacks with the help of SCMD (Suspicious Cryptographic Message Detection) such as cryptanalysis of SMS or any messaging system. When the server received a suspicious encrypted message, the proposed framework will decrypt the suspicious message and facilitate in predicting the crime, criminal name, location, and criminal details and report to the electronic crime agency. To date, no proper solution to avoid such a big crime as the world is facing problems still today along with this machine learning technique, Artificial Intelligence and semantic web ontology and Cryptanalysis of Enigma Cipher. Terrorists communicate with their teammates in different locations of the world and instruct with resources to attack the government or public while communicating they use the encrypted message to maintain secrecy. Our framework at the server site will detect encrypted messages and decrypt them with the help of Cryptanalysis of Enigma Cipher techniques. The framework will decrypt a suspicious message and expedites predicting the type of crime from microblogs before it gets executed by criminals. Details of criminals will be alerted to cybercrime the department that reduces the tension for the various security departments. Criminals use an encrypted message to pass activity among teammates who may be in living in any corner of the World and other people may decrypt and convert it to plain text and takes action.