1Conclusion
583. Reduced false positives:
2References
594. Linking related attacks:
3Classification
605. User/device behavior analysis:
4Logistic Regression:
616. Automated virtual patching:
5Random Forest :
62Detecting XSS Vulnerabilities
6Regression: – Linear Regression
63Detecting XSS Exploits
7Clustering
641. Behavioral Analysis Engine
8 – K-means: – DBSCAN
652. Advanced Client Challenges
9Anomaly Detection
663. Collective Threat Intelligence
10 – Isolation Forest: – Autoencoders
674. Selective Rate Limiting
11Conclusion
68Conclusion
12References
69References
13Neural Networks
70Identity & Access Modeling
14•Object Detection in Images/Video
71Dynamic Authorization
15•Facial Recognition
72Detecting Business Logic Abuse
16•Malware Classification
73Hardening Business Logic
17•Fake Media Detection
74Bot Detection
18•User Behavior Analysis
7515.3.1 DDoS Protection Analysis
19•Fraud Detection
76Negative Security Models: Traffic Authentication
20•Phishing Campaign Tracking
77Validation Engines
21•Network Anomaly Detection
78Behavioral Models
22Conclusion
79Sanitization Checks
23References:
80Conclusion
24Conclusion
81References
25References
82Random Forests
26Conclusion
83Artificial Neural Networks
27References
84Support Vector Machines
281. Signature-based Detection
85Resampling Data
292. Anomaly-based Detection
86Class Weights
30Conclusion
87Domain Driven Features
31References
88Derived Features
32Convolutional Neural Networks
89Batch Analysis
33Recurrent Neural Networks
90Online Analysis
34Graph Neural Networks
91Conclusion
35Packing
92References:
36Polymorphism
93Conclusion
37Metamorphism
94References
38Conclusion
95Conclusion
39References:
96References
40Volumetric Attacks
97Conclusion
41Protocol Attacks
98References
42Application Attacks
9920.1.1 Host Activity Monitoring
43Conclusion
100Memory Analysis: Python code
44References
101User and Insider Threat Detection
45Conclusion
102Deep learning can also enhance malware detection beyond binary analysis and behavior monitoring:
46References
103Conclusion: References
47Conclusion
104Evasion Attack using Fast Gradient Sign Method
48References:
105Model Inversion Attack through Model Queries
49Conclusion
106Conclusion
50References:
107References
51Conclusion
108Interpretable Models:
52References
109Explainable AI Systems:: SHAP - Shapley Additive Explanations
53SQL injection:
110Customized Explanations:
54Cross-site scripting (XSS):
111Interactive Explanations:
55Account takeover:
112Actionable Insights:
561. Continuous traffic analysis:
113Conclusion
572. Rapid blacklist updates:
114References
