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Machine Learning and Cryptographic Algorithms – Analysis and Design in Ransomware and Vulnerabilities Detection

EasyChair Preprint no. 3207

8 pagesDate: April 20, 2020


 The AI, deep learning and machine learning algorithms are gaining the ground in every application domain of information technology including information security. We have traditional password management systems, auto-provisioning systems and user information management systems. On the existing systems cyber-attacks of Ransomware asking for ransom increasing every day. Ransomware is the class of malware where the goal is to gain the data through encryption mechanism and render back with the ransom. The ransomware attacks are mainly on the vulnerable systems which are exposed to the network with weak security measures. With the help of machine learning algorithms, the pattern of the attacks can be analyzed. Create or discuss a workaround solution of a machine learning model with combination of cryptographic algorithm which will enhance the effectiveness of the system response to the possible attacks. The other part of the problem, which is hard part to create an intelligence for the organizations for preventing the ransomware attacks with the help of intelligent system password management and intelligent account provisioning.  In this paper I elaborate on the machine learning algorithms analysis for the intelligent ransomware detection problem, later part of this paper would be design of the algorithm.

Keyphrases: AI, Encryption, machine learning, Ransomware

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Nandkumar Niture},
  title = {Machine Learning and Cryptographic Algorithms – Analysis and Design in Ransomware and Vulnerabilities Detection},
  howpublished = {EasyChair Preprint no. 3207},

  year = {EasyChair, 2020}}
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