Data Redundancy, Data Phishing, and Data Cloud Backup

Abstract

Data today is extremely complex and massive in size. By taking these factors into account, machine learning and ETL techniques will find it much easier to separate useful data from unusable raw data. In web technology, OLTP and OLAP are used to manipulate data on a daily basis. During the transaction, a massive amount of data is maintained in the database or data warehouse. There was no Cloud storage to back up data in the past. Because of the significant increase in internet usage, people are sharing more of their personal information online. Cybercriminals can now access a vast amount of personal data and financial activities. Phishing is one instance of a very efficient type of cybercrime that allows offenders to trick users and obtain crucial data. Phishing has advanced into a more complex attack vector since the first known instance was published in 1990. One of the most common online fraud types now is phishing. Phishing attacks can cause serious losses for their victims, including the theft of confidential information, identities, businesses, and state secrets. This article evaluates these attacks by addressing existing phishing techniques and discussing the current state of phishing. Phishing attacks have been classified in studies based on common phishing methodologies and defences, ignoring the importance of the entire phishing lifecycle. This article provides a new, in-depth model of the anatomy of phishing attacks, including attack phases, attacker types, threats, targets, attack media, and attacking strategies. The suggested physiology would also help readers understand the lifecycle of a phishing attack, which would aid in the development of a comprehensive anti-phishing system. This will improve public awareness of phishing attacks and the methods used. New approaches are also proposed, and certain preventive measures are investigated.