JP-Morgan-and-Chase-Internship-in-Cybersecurity.pptx

in this ppt we have tell about a project on fraud detection using ml algorithms.

1. JP Morgan & Chase - Internship in Cybersecurity This presentation outlines my internship experience at JP Morgan & Chase in Cybersecurity. by Abhay

2. Company Overview 1 1799 Founded as a bank in New York City. 2 1990s Expansion into investment banking and asset management. 3 2000s Focus on cybersecurity and technology innovation.

3. Cybersecurity in Financial Institutions Vital Importance Protect sensitive financial data and customer information. Growing Threats Cybercrime cost $1.5 trillion in 2023.

4. Fraud Detection in Financial Services Data Analysis Using Pandas and Matplotlib for fraud detection. Machine Learning Developing models to identify fraudulent patterns. Real-Time Monitoring Implementing systems to detect and prevent fraud in real-time.

5. Web Application Security Vulnerability Assessment Identifying potential security weaknesses. Mitigation Strategies Implementing solutions to address vulnerabilities. Continuous Monitoring Regularly scanning for new threats and vulnerabilities.

6. Email Classifier Using Machine Learning 1 Spam Detection Classifying emails as spam or legitimate. 2 Phishing Prevention Identifying and blocking phishing emails. 3 Data Analysis Analyzing email data to improve classification accuracy.

7. Access Control System Design Role Permissions Administrator Full access to all systems and data. User Limited access to specific systems and data.

8. Tools Learned Python Programming language for data analysis and machine learning. Pandas Data manipulation and analysis library. Django Web framework for building secure web applications. Scikit-learn Machine learning library for building classification models.

9. Research & Gap Analysis 1 False Positives Identifying and reducing false positives in fraud detection. 2 Security Gaps Analyzing system vulnerabilities and identifying areas for improvement. 3 Data Accuracy Ensuring data quality and accuracy for effective analysis.

10. Objectives 1 Fraud Detection Improve fraud detection accuracy and efficiency. 2 Web Security Implement secure coding practices and mitigate vulnerabilities. 3 Access Control Enhance access control mechanisms to protect sensitive data.