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This presentation introduces Mem2Img, a convolutional-neural-network ensemble framework for detecting memory-resident malware and process-injected threats. It addresses limitations of antivirus software, YARA rules, and handcrafted machine-learning features in identifying unknown or shellcode-based malware.
