Главная
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on
1
Intro
2
HOW DID WE GET HERE?
3
CLEVER HANS
4
ARTIFICIAL INTELLIGENCE?
5
INTELLIGENT SYSTEM
6
WHAT IS A ML MODEL?
7
CODE POINT OF VIEW
8
FROM TRAINING TO INFERENCE
9
BIAS - SOLVING THE WRONG PROBLEM
10
TOP 5 ATTACKS (CVSS)
11
TOP 5 ATTACKS (BUSINESS IMPACT)
12
WHERE TO ATTACK?
13
PRELIMINARY RESULTS
14
ATTACK OF THE CLONES
15
BACKDOORS
16
ENCODING
17
MISS-PREDICTIONS (ADVERSARIAL ATTACKS)
18
TURTLE OR A RIFLE?
19
ADVERSARIAL AUDIO
20
EVADING NEXT GENERATION AV USING AI
21
ACKNOWLEDGMENTS
22
REFERENCES
Description:
Explore the world of hacking machine learning systems in this conference talk from 44CON 2018. Delve into the emerging field of Adversarial ML, learning how to exploit weak points in speech, text, and face recognition algorithms. Discover techniques for achieving unexpected consequences, data leakage, memory corruption, and output manipulation in ML systems. Witness a live demonstration showcasing the potential vulnerabilities in these intelligent systems. Gain insights into the top 5 attacks based on CVSS and business impact, and understand where to focus your offensive research. Learn about various attack methods, including cloning, backdoors, encoding, and adversarial attacks on audio and visual recognition systems. Examine real-world examples, such as misclassifying rifles as bananas and evading next-generation antivirus software using AI. Equip yourself with knowledge to better understand and address the security challenges posed by machine learning technologies.

JARVIS Never Saw It Coming - Hacking Machine Learning in Speech, Text and Face Recognition

44CON Information Security Conference
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