Identification of Multiple Attacks in Cloud Environment using Big Data

Abstract

Since the Cloud environment is prone to many attacks we are implementing a Big Data based centralized log analysis system to identify the network traffic occurred by attackers through DDOS, SQL Injection, and Brute Force attacks. The log file is automatically transmitted to the centralized cloud server where big data is initiated and uses a tool called Hadoop to process the huge amount of log files that are being sent to big data. If an attacker attacks any files then it will be compared with the attack dataset that is maintained here to detect the attacks that are being used by the attacker. This system also helps in storing the information of all registered users, and their files which get uploaded to the cloud server and downloaded from the server and IP addresses in order to view any attacks that may occur in the future. All this stored information is maintained securely using SQL which is a backend process. Thus we are implementing a system that delivers a very high performance as well as very efficient results in categorizing the attacks. Since the Hadoop tool is being used in the system, this system is able to increase its scalability and achieves a faster detection of attacks like DDOS, SQL Injection, and Brute Force attacks. This system can play a vital role in various organizations to safeguard their privacy. Data integrity, Data confidentiality, and non-repudiation can be achieved by using this system. Finally, we can say that this system avoids any faults that occurred in the previous system that was invented before this.