Computer Science Practical 5 Notes | B.Sc. (Computer Science) Semester 5 | Mumbai University | munotes

Contents

Module I Artificial Intelligence: ten exercises in Python, from breadth first search to a TensorFlow demonstration

1. How This Practical Is Examined: the Journal, the 80 Per Cent Rule and the Two-Hour Paper 1
2. The Python Laboratory from Zero: Running Your First Program and Saving It for the Journal 5
3. The Dataset, the Split and the Score: How Every Model in This Module Is Measured 11
4. Practical 1: Breadth First Search and Iterative Deepening Depth First Search 20
5. Practical 2: A* Search and Recursive Best-First Search 32
6. Practical 3: Decision Tree Learning 45
7. Practical 4: The Feed Forward Backpropagation Neural Network 59
8. Practical 5: Support Vector Machines 73
9. Practical 6: Adaboost Ensemble Learning 83
10. Practical 7: The Naive Bayes Classifier 93
11. Practical 8: K-Nearest Neighbours for Classification and for Regression 104
12. Practical 9: Association Rule Mining with Apriori 114
13. Practical 10: A Demonstration with TensorFlow and with an OpenAI-Style Tool 123

Module II Cyber and Information Security: ten exercises, from the classical ciphers to firewall rules on a real Linux

1. The Security Laboratory from Zero: OpenSSL, the Byte, and What Is Safe to Run 134
2. Practical 11, Part 1: The Substitution Ciphers 139
3. Practical 11, Part 2: The Transposition Ciphers 154
4. Practical 12: RSA Encryption and Decryption 162
5. Practical 13: Message Authentication Codes 174
6. Practical 14: Digital Signatures 183
7. Practical 15: Key Exchange Using Diffie-Hellman 193
8. Practical 16: IP Security (IPsec) Configuration 204
9. Practical 17: Web Security with SSL/TLS 214
10. Practical 18: Intrusion Detection System 225
11. Practical 19: Malware Analysis and Detection 234
12. Practical 20: Firewall Configuration and Rule-Based Filtering 243
13. The Two-Hour Paper: Sitting the Examination 254