Identification and Management of Frauds in Edge Computing Systems

摘要

Edge computing enables edge devices to perform intricate tasks competently. However, identifying fraud while performing these tasks is a foremost necessity. Phishing is a type of fraudulency that is sent in by the hackers via email, URL's, blogs redirecting to a new page and so on, where the attacker imitates as a genuine person. The main prospect is to collect data relating to a person's credentials to confidential data and use in form of blackmail for huge ransom money. Foremost attackers sent in Phishing mails where URLs are redirected via HTTP protocol in edge computing systems that is undetectable leading to huge loss for the corporate world, now anti-phishing algorithms, Machine Learning Algorithms, anti-phishing frameworks, anti-phishing simulators are built in order to detect faults in many domains to scale down activities of Phishing. Cyber activity in form of phishing has become one of the day-to-day prompting attacks to the corporate society, in the world that leads to many sinful activities an anti-phishing is used in order to distinguish these faults and scale down the amount of damage that is being performed. This paper deliberates on the types of phishing and anti-phishing methods with a common algorithm for suspicious phishing host, and an anti-phishing pseudo code for captcha images that can be used for identifying fraudulency and manage the same in edge computing devices.