摘要:
Disclosed is a method for detecting a cyberthreat through correlation analysis of security events, which includes extracting a false-positive data set by extracting, from source data, information about security events occurring during a predetermined time period based on a time at which erroneous detection occurred; extracting a true-positive data set by extracting, from the source data, information about security events occurring during the predetermined time period based on a time at which an intrusion threat was correctly detected; extracting a current data set by extracting information about security events occurring during the predetermined time period from data to be analyzed; generating event coincidence statistics by extracting a frequency of each security event in the respective data sets and by compiling statistics thereon; generating an event vector based on the event coincidence statistics; and performing intrusion threat detection through a vector space model based on the event vector.
摘要:
Disclosed herein are an apparatus and method for detecting a malicious script. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program is configured to extract token-type features, each of which corresponds to a lexical unit, and tree-node-type features of an abstract syntax tree from an input script, to train two learning models to respectively learn two pieces of learning data that are generated in consideration of features extracted respectively from the token-type features and the node-type features as having the highest frequency, and to detect whether the script is a malicious script based on the result of ensemble-based malicious script detection performed for the script, which is acquired using an ensemble detection model generated from the two learning models.
摘要:
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.
摘要:
Disclosed herein are an apparatus and method for generating a data set. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program classifies collected data into numerical feature data and categorical feature data using a filter method, performs correlation analysis on the numerical feature data and the categorical feature data using an analysis of variance (ANOVA) method and a Chi-Squared method, and generates a data set for supervised learning and a data set for unsupervised learning using correlation scores calculated through correlation analysis.
摘要:
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.
摘要:
An apparatus and method for detecting abnormal connection behavior are disclosed. The apparatus for detecting abnormal connection behavior includes a data extraction unit, a data storage unit, and a detection unit. The data extraction unit collects network data transmitted and received over a network including a plurality of hosts, and extracts data required for the detection of abnormal connection behavior from the network data. The data storage unit stores the extracted data required for the detection of abnormal connection behavior. The detection unit detects abnormal connection behavior based on characteristic factors corresponding to the stored data required for the detection of abnormal connection behavior and characteristic factors corresponding to malicious behavior.
摘要:
Disclosed herein is an apparatus and method that process knowledge, experience information, or the like possessed by group members via a dynamically created social group, in the form of collaborative storyboards, thus enabling the collaborative storyboards to be shared among a plurality of social groups, as well as the corresponding members. The presented apparatus includes a social group management unit for managing information about a social group and a user joining the social group as a member, and an information management unit for accepting information finally determined with respect to information of content desired to be shared, which is posted by the user on a storyboard of the social group, in collaboration with other users, as a post of the storyboard of the social group, and distributing the post to the social group.
摘要:
A visualizing apparatus of social network elements collects social network relationship information, community information, and content information of a user, generates relationship data between the user, the contents, and the community using the collected information, and visualizes an association relationship between the user, the contents, and the community using the relationship data between the user, the contents, and the community.