International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
www.irjet.net
BITCOIN HEIST: RANSOMWARE ATTACKS PREDICTION USING DATA SCIENCE Mrs. M. Bhuvaneswari1, S. Gopinath2, K.S. Shyam 3, A. Manoj 4, B. Sudarshan5 1Guided by (Assistant Professor) Department of Information Technology, Meenakshi College of Engineering,
Chennai, Tamil Nadu, India 2-5Student of the Department of Information Technology, Meenakshi College of Engineering, Chennai,
Tamil Nadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------data science and machine learning, their relationship, and Abstract - Ransomware attacks are emerging as a major how they have transformed various industries.
source of malware intrusion in recent times. While so far ransomware has affected general-purpose adequately resourceful computing systems. Many ransomware prediction techniques are proposed but there is a need for more suitable ransomware prediction techniques for machine learning techniques. This paper presents an attack of ransomware prediction technique that uses for extracting information features in Artificial Intelligence and Machine Learning algorithms for predicting ransomware attacks. The application of the data science process is applied for getting a better model for predicting the outcome. Variable identification and data understanding is the main process of building a successful model. Different machine learning algorithms are applied to the pre-processed data and the accuracy is compared to see which algorithm performed better other performance metrics like precision, recall, f1score are also taken in consideration for evaluating the model. The machine learning model is used to predict the ransomware attack outcome
What is Data Science? Data science is a multidisciplinary field that involves extracting insights and knowledge from data. It is a combination of statistics, computer science, and domain expertise. Data scientists use various techniques to analyze and interpret data, including data mining, machine learning, and statistical modeling. Data science has become increasingly important in recent years due to the exponential growth of data. Every day, we generate massive amounts of data through our interactions with technology, social media, and other digital platforms. This data contains valuable insights that can be used to make informed decisions and drive business growth. What is Machine Learning? Machine learning is a subfield of artificial intelligence that refers to the activity of instructing systems to learn from data. It helps computers to detect links and patterns in data without being particularly trained to do so. Semi-supervised, unsupervised, and supervised algorithms are all available for machine learning.
Key Words: Ransomware API, Ransomware prediction, Cyber forensic, Machine/Deep Learning.
1. INTRODUCTION Digital currencies called crypto currencies, like Bit coin, are created to operate independently of the established financial system. Block chain technology is used by crypto currencies to record transactions, making them decentralized money. A crypto-exchange platform is primarily used to manage crypto currency transactions, often known as the buying and selling of digital currency. These transactions sometimes include significant amounts of crypto currencies and are typically made anonymous using the block chain, which draws cybercriminals. Platforms and exchange methods for crypto currencies are susceptible to cyber attacks, just like any other system.
A labeled dataset is used to supervise the training of a machine learning system. The algorithm develops prediction abilities based on input data and output data that match. Unsupervised learning refers to the process of developing an algorithm utilizing a dataset without any labels. The algorithm discovers links and patterns in the data without having any prior understanding of what the data means. In semi-supervised learning, both supervised and unsupervised learning are employed. The Relationship Between Data Science and Machine
Data science and machine learning are two of the most rapidly growing fields in technology. They have revolutionized the way businesses operate, how people interact with technology, and how we approach solving complex problems. This essay will explore the concepts of
© 2023, IRJET
|
Impact Factor value: 8.226
Learning Machine learning and data science are closely related. One of the various methods used in data science to analyse and understand data is machine learning. Machine learning
|
ISO 9001:2008 Certified Journal
|
Page 454