Abstract: A malware detection prioritization method is disclosed. The method includes receiving, by a user interface of an electronic device, a user input. The method further includes selecting, by a selector of the electronic device, characteristics of malware applications based on the user input and one or more malware severity criteria associated with at least one of proliferation or an operation impact. The method further includes converting, by a transformer of the electronic device, the characteristics of the malware applications into numerical values. The method further includes processing, by a machine learning model of the electronic device, the numerical values and the user input to generate an indication of one or more highest severity malware applications among the malware applications. The method further includes monitoring, by a detection engine of the electronic device, for the one or more highest severity malware applications.

Abstract: A dynamic hybrid residential threat detection method is disclosed. The method includes receiving, by a packet selector on a customer premises equipment (CPE), communication sessions and selecting and sending, by the packet selector, a predefined number of packets of the communication sessions to a CPE detection engine based on packet selection rules. The method also includes inspecting, by the CPE detection engine, the predefined number of packets of each communication session based on CPE detection rules that establish what type of inspection is to be performed by the CPE detection engine based at least in part on CPE resource constraints. The method further includes sending, by the packet selector, the predefined number of packets of at least some of the communication sessions to a cloud detection engine and blocking particular communication traffic on the CPE based on the inspection and/or an instruction from the cloud detection engine.

Abstract: A dynamic hybrid residential threat detection method is disclosed. The method includes receiving, by a packet selector on a customer premises equipment (CPE), communication sessions and selecting and sending, by the packet selector, a predefined number of packets of the communication sessions to a CPE detection engine based on packet selection rules. The method also includes inspecting, by the CPE detection engine, the predefined number of packets of each communication session based on CPE detection rules that establish what type of inspection is to be performed by the CPE detection engine based at least in part on CPE resource constraints. The method further includes sending, by the packet selector, the predefined number of packets of at least some of the communication sessions to a cloud detection engine and blocking particular communication traffic on the CPE based on the inspection and/or an instruction from the cloud detection engine.

Abstract: A dynamic hybrid residential threat detection method is disclosed. The method includes receiving, by a packet selector on a customer premises equipment (CPE), communication sessions and selecting and sending, by the packet selector, a predefined number of packets of the communication sessions to a CPE detection engine based on packet selection rules. The method also includes inspecting, by the CPE detection engine, the predefined number of packets of each communication session based on CPE detection rules that establish what type of inspection is to be performed by the CPE detection engine based at least in part on CPE resource constraints. The method further includes sending, by the packet selector, the predefined number of packets of at least some of the communication sessions to a cloud detection engine and blocking particular communication traffic on the CPE based on the inspection and/or an instruction from the cloud detection engine.