Abstract: The present disclosure provides autotaxin (ATX) inhibitor compounds and compositions including said compounds. The present disclosure also provides methods of using said compounds and compositions for inhibiting ATX. Also provided are methods of preparing said compounds and compositions, and synthetic precursors of said compounds.

Abstract: Disclosed are a system and a method for detecting session initiation protocol (SIP) noncoding, and more particularly, to a system and a method for detecting SIP noncoding, which can manage reputation of a client terminal according to whether or not the client terminal sends an encoded SIP message through a 5G non-standalone/Standalone (5G NSA/SA), thereby preventing an SIP spoofing attack.

Abstract: The exemplary embodiments of the present disclosure provide a method and an apparatus for detecting an abnormal roaming request which acquires information of user equipment which sends a roaming request message, calculates a risk of the roaming request message using a roaming request location and a roaming request time of the user equipment, and safely processes the request according to the risk.

Abstract: An operating method of a computing device operated by at least one processor includes collecting traffic packets; extracting particular field data from the traffic packets, transforming the extracted particular field data to a vector with a reduced dimension for each traffic packet, and creating training data with the vector for each traffic packet; training a traffic prediction model with the training data, the traffic prediction model predicting from an input traffic packet a next input traffic packet and whether the next input traffic packet is abnormal; and predicting with the trained traffic prediction model a frequency of abnormal traffic packets to be input, and outputting an abnormal traffic warning by comparing the predicted frequency and a threshold.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An operating method of a computing device operated by at least one processor includes collecting traffic packets; extracting particular field data from the traffic packets, transforming the extracted particular field data to a vector with a reduced dimension for each traffic packet, and creating training data with the vector for each traffic packet; training a traffic prediction model with the training data, the traffic prediction model predicting from an input traffic packet a next input traffic packet and whether the next input traffic packet is abnormal; and predicting with the trained traffic prediction model a frequency of abnormal traffic packets to be input, and outputting an abnormal traffic warning by comparing the predicted frequency and a threshold.