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A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection
Cyber intrusion attacks that compromise the users' critical and sensitive data are escalating in volume and intensity, especially with the growing connections between our daily life and the Internet.
Intrusion Detection in Internet of Things using Convolutional Neural Networks
As security mechanisms are often neglected during the deployment of IoT devices, they are more easily attacked by complicated and large volume intrusion attacks using advanced techniques.
Clustering based opcode graph generation for malware variant detection
Hence, for each malware family, a group of signatures is generated to represent the family.
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