MRm-DLDet: a memory-resident malware detection framework based on memory forensics and deep neural network

Abstract Cyber attackers have constantly updated their attack techniques to evade antivirus software detection in recent years. One popular evasion method is to execute malicious code and perform malicious actions only in memory. Malicious programs that use this attack method are called memory-resid...

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Egile Nagusiak:	Jiaxi Liu, Yun Feng, Xinyu Liu, Jianjun Zhao, Qixu Liu
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	SpringerOpen 2023-08-01
Saila:	Cybersecurity
Gaiak:	Memory-resident malware Memory forensics Malware detection Deep learning Ultra-high resolution image
Sarrera elektronikoa:	https://doi.org/10.1186/s42400-023-00157-w
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

MRm-DLDet: a memory-resident malware detection framework based on memory forensics and deep neural network

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