Free download скачать Deepfake Defense 2026 Detect, Defend & Defeat Threats
Published 4/2026
Created by Armaan Sidana
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 10 Lectures ( 1h 42m ) | Size: 1.1 GB
Detect, Defend & Defeat AI Fakes: GANs, Voice Cloning, EfficientNet Forensics, C2PA & 10 Hands-On Labs
[h2]What you'll learn[/h2]
Build a complete deepfake detection pipeline
Fine-tune and harden AI detection models
Implement enterprise deepfake defense frameworks
Investigate suspected deepfakes using OSINT methodology
[h2]Requirements[/h2]
● Basic Python knowledge
● Command line comfort
● A computer with 8GB+ RAM
● Basic cybersecurity awareness
[h2]Description[/h2]
Deepfakes are rapidly emerging as one of the most significant cyber threats of 2026. Fraud losses are projected to reach $40 billion by 2027, with a single AI-generated video call already costing one company $25 million. Meanwhile, Deepfake-as-a-Service platforms can produce highly convincing fakes for as little as $20. If your organization does not yet have a detection and defense strategy, it is already at risk.
This course provides a complete, end-to-end toolkit-covering everything from how deepfakes are created to how they can be detected, investigated, and mitigated at enterprise scale.
What sets this course apart?
This is not a passive, lecture-based experience. You will build real systems through 10 hands-on labs, including
• Image classification models
• Frame-by-frame video analysis pipelines
• Audio voice-clone detection systems
• C2PA content provenance implementation
• Invisible watermarking techniques
• EfficientNet fine-tuning
• Grad-CAM forensic visualization
• Adversarial attack and defense strategies
• OSINT-based investigations
• A full capstone detection system achieving an AUC of 0.983
You will begin by mastering the attacker's toolkit-GANs, diffusion models, voice cloning (XTTS-v2, ElevenLabs), lip-sync systems like Wav2Lip, real-time face swapping pipelines, and the economics behind Deepfake-as-a-Service. Understanding how deepfakes are built is key to understanding how they fail.
Building layered defenses
You will then design and implement advanced detection and defense mechanisms, including
• Frequency-domain analysis and GAN fingerprinting
• EfficientNet-B4 transfer learning on FaceForensics++ (AUC 0.971 in 15 epochs)
• Grad-CAM explainability heatmaps suitable for forensic reporting
• Adversarial hardening against FGSM and PGD attacks
• Multimodal fusion of visual, audio, temporal, and metadata signals (AUC 0.998)
• Lip-sync verification using SyncNet and behavioral biometrics like blink patterns
• Metadata and EXIF forensic analysis
• C2PA content provenance with ECDSA P-384 signatures
• Robust invisible watermarking (DWT-DCT) resilient to compression and re-encoding
Enterprise-ready defense strategy
Beyond technical detection, the course covers full-spectrum enterprise defense, including
• STRIDE threat modeling
• Business Email Compromise (BEC 2.0) attack scenarios
• Multi-Factor Identity Verification (MFIV) protocols
• Zero-trust integration for platforms like Teams and Zoom
• Employee awareness and training programs
• A six-phase incident response framework
• Vendor evaluation across leading solutions (Hive, Sensity, Azure, Pindrop)
Real-world investigation skills
You will also develop practical OSINT and forensic investigation capabilities, including
• Keyframe extraction using InVID
• Reverse image and video searches (TinEye, Yandex)
• Analysis of real-world deepfake cases from Slovakia, the United States, and Pakistan
• End-to-end forensic reporting with proper chain-of-custody documentation
Who should take this course?
This course is designed for
• Security professionals
• Digital forensics analysts
• Machine learning engineers
• Journalists and fact-checkers
• Anyone responsible for protecting information integrity
Basic Python and command-line knowledge are recommended. All machine learning concepts are explained from first principles.
What you will achieve
By the end of this course, you will have
• A production-ready deepfake detection API
• A custom-trained, adversarially hardened EfficientNet model
• A complete enterprise defense playbook
• Professional-grade OSINT investigation skills
• A fully integrated capstone detection system combining all components
The attacker only needs to succeed once. You need to succeed every time.
This course ensures you are prepared.
[h2]Who this course is for[/h2]
■ Everyone
[h2]Homepage[/h2]
https://www.udemy.com/course/deepfake-defense-2026-detect-defend-defeat-threats
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