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9. Learning with Differential Privacy

10. Secure Distributed Learning

11. Outsourced Computation for Learning

12. Applications—Privacy-Preserving Image Processing

13. Threats in Open Environment

14. Secure Cooperative Learning in Early Years

15. Introduction

16. Cryptanalysis on ZUC 1.4

17. Concluding Remarks

18. Introduction and Preliminaries

19. Design Specification of ZUC Stream Cipher

20. Privacy-Preserving Federated Learning

21. Telephony Architecture

22. Attacks on Deep Learning and Their Countermeasures

23. Pros and Cons of X-Based PPDL

24. Preliminaries

25. X-Based PPDL

26. Introduction

27. Conclusion

28. Deep Feature Learning

29. Location Privacy in Wireless Vehicular Networks

30. Location Privacy in Mobile Crowd Sensing Applications

31. Location Privacy in Mobile Social Network Applications

32. Introduction

33. Location Privacy-Preserving Mechanisms

34. Deep Learning-Based IDSs

35. Deep Learning

36. Introduction

37. Classical Machine Learning and Its Applications to IDS

38. Intrusion Detection Systems

39. Summary

40. Digital Forensic Data and Open Source Intelligence (DFINT+OSINT)

41. Data Reduction of Mobile Device Extracts

42. Digital Forensic Data and Intelligence

43. Requirements and State of the Art

44. Introduction

45. Quick Analysis of Digital Forensic Data

46. Data Reduction and Data Mining Frame-Work

47. Crawling Botnets

48. The Anatomy of P2P Botnets

49. Introduction

50. Deployment of Sensor Nodes in Botnets

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