Korea Internet & Security Agency

Do Won Kim

Tae Eun Kim

Hyung Jin Cho

Seong Min Park

Young Kwon Park

Seul Ki Choi

Ki Jong Son

Bo Min Choi

Jin Hyun Cho

Sung Moon Kwon

Hwan Kuk Kim

Tae Hyeon Kim

Sae Woom Lee

Jong Ki Kim

Eun Hye Ko

Gyeong Jin Na

A method of supporting decision-making of security control includes: (a) when an system for automatically analyzing a security threat receives a security warning from a security device, collecting security threat events generating the security warning from the security device; (b) when the collected security threat events exceed a preset event processing threshold, generating, by the system for automatically analyzing a security threat, a first request message for preferentially processing a security event; (c) when receiving the first request message generated from the system, determining, by the system for supporting priority of security control, a priority processing order of the security threat events, and notifying the system; and (d) when receiving the second request message generated from the system, determining, by the system for supporting priority of security control, a priority processing order and notifying the system for automatically analyzing a security threat of the determined priority processing order.

Method for supporting decision-making in security control environment based on artificial intelligence

Disclosed is a system and a method of detecting an abnormal act threatening to security based on artificial intelligence according to the present invention, and, more particularly, a system and a method of detecting an abnormal act threatening to security based on artificial intelligence that are capable of rapidly carrying out pre-processing of a large-scaled data set based on multi processing, and efficiently detecting the abnormal act threatening to security via various pieces of security device on the basis of studied artificial intelligence.

System and method of detecting abnormal act threatening to security based on artificial intelligence

Provided is a method for detecting abnormal traffic. The method comprises collecting non-access stratum (NAS) traffic between a user equipment (UE) and a mobility management node, identifying a ciphering algorithm supported by the UE from a network access request message transmitted from the UE to the mobility management node, and identifying the UE as a first type of terminal at risk based on a determination that the UE only supports a null ciphering algorithm.

Method and apparatus for detecting null-ciphering channels

Provided is a method for rearranging traffic data performed by a computing device. The method comprises obtaining traffic data transmitted and received between a base station and a terminal, calculating a value of a Radio Resource Control (RRC) inactivity timer based on a RRC release message included in the traffic data, determining a size of a time window using the calculated value of the RRC inactivity timer and rearranging, for each time window having the determined size, the traffic data of a target terminal by an RRC connection request time.

Method and apparatus for rearranging traffic data

Provided are methods of detecting a Diameter spoofing attack. According to an embodiment, the method comprises, obtaining a normal International Mobile Subscriber Identity (IMSI) from a packet of a Diameter S6a protocol transmitted from a Mobile Management Entity (MME) to a Home Subscriber Server (HSS) of a home network, adding a record comprising the normal IMSI to a session table, obtaining an Insert Subscriber Data Request (IDR) message of the Diameter S6a protocol and determining a category of the IDR message.

Method and apparatus for detecting diameter protocol IDR message spoofing attack in mobile communication network

Growing community of inventors

Jeollanam-do, South Korea

Do Won Kim