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Malware Analysis Using Artificial Intelligence and Deep Learning
Manage episode 513147045 series 3683458
A tartalmat a CyberSecurity Summary biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a CyberSecurity Summary vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Discuss artificial intelligence and deep learning techniques applied to malware analysis and detection, as well as other cybersecurity challenges. They cover various neural network architectures like MLPs, CNNs, RNNs, LSTMs, and GANs, and their effectiveness in tasks such as classifying malware families, identifying malicious URLs, and detecting anomalies in network traffic or system logs. The papers also explore methods for feature extraction from malware binaries, including static and dynamic analysis, and how adversarial examples can challenge these detection systems. Furthermore, they address the use of AI for troll detection on social media platforms and image spam classification.
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You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Malware-Analysis-Artificial-Intelligence-Learning/dp/3030625818?&linkCode=ll1&tag=cvthunderx-20&linkId=c97d080f094227b8fb921fea640e5e56&language=en_US&ref_=as_li_ss_tl
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