Abstract:
A method, an apparatus, and a system for analyzing traffic through obtaining flow data of a flow from a switch or a router of a network, calculating an average byte per packet rate (BPR) and a TCP flag ratio (TCPFR) for all flows included in a session including the flow using the flow data, and comparing the average BPR and the TCPFR with an average BPR and a TCPFR of previously-known traffic and determining whether the traffic including the flow is normal traffic or abnormal traffic based on the comparison result are provided.
Abstract:
A method and a computation apparatus detecting cyber threats using a neural network through steps of: generating a learning model by performing machine learning on training data based on baseline data, converting a security event collected in real time into input data for the neural network, and determining, as an output corresponding to the input data based on the learning model, whether the security event is normal or threat are provided.
Abstract:
A ransomware detection apparatus and an operation method thereof are provided. The ransomware detection apparatus may include a frequency converter receiving an OP code currently being executed in a CPU and converting a value of the OP code into a frequency domain to generate a first OP code frequency waveform, a memory storing a second OP code frequency waveform, which is a value obtained by converting the OP code corresponding to a ransomware encryption algorithm into a frequency domain, and a ransomware determiner comparing the first OP code frequency waveform with the second OP code frequency waveform to determine whether ransomware operates.
Abstract:
An apparatus for quantifying network threat situations includes a traffic analyzing unit to analyze packet patterns of traffics occurring on a target network being monitored to extract one or more suspicious domains. An IP monitoring unit gives security levels among a plurality of security levels to the suspicious domains according to the number of access IPs accessing the suspicious domains. An activity index computing unit computes activity indices for the suspicious domains from activity indices according to the access times to the suspicious domains of the access IPs. An attack amount anticipation unit analogizes an expected amount of attacks for each suspicious domain according to an expected amount of attacks for each zombie computer, the security level and the activity index of the suspicious domain.