DETECTION OF RANSOMWARE ATTACKS IN NETWORK USING MACHINE LEARNING

DETECTION OF RANSOMWARE ATTACKS IN NETWORK USING MACHINE LEARNING

1.ABSTRACT

The development of computer and communication technology has resulted in considerable changes from the past. Despite the fact that utilising new inventions benefits people, organisations, and governments greatly, some people are prejudiced against them. For instance, information security in file systems, information accessibility, and so on.Due to several groups, including the criminal underworld, professionals, and digital activists, including dread of the digital world, which has caused many issues for individuals and organisations, has reached the point where it may jeopardise national and open security. Intrusion Detection Systems (IDS) were created as a result to maintain a safe distance from internet threats. The new CICIDS2017 dataset was utilised to train the Support vector machine (SVM) computations, which are currently being used to identify port sweep efforts. Instead of SVM, we might use other algorithms like CNN, ANN, and random forest. Keywords: data security, information accessibility, digital fear, intrusion detection systems. 

1 B Ramakrishna 2 A Ajith Reddy 3 B Srinivas 4 Dr V Shanmukha Rao

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