Osong Medical Innovation Foundation, Korea University Research and Business Foundation

Microsoft Technology Licensing, LLC

Lg Electronics Inc.

Heejo Lee

Choongin Lee

Dongwon Seo

Bin Benjamin Zhu

Cheolseung Kim

Byeongrim Jo

Wan Yeon Lee

Jonghoon Kwon

Seongsoo Kim

Jihwan Jeong

Jieun Song

Hyunsang Choi

Seunghoon Woo

Donghyeok Kim

Hyundo Park

Seulbae Kim

Kiryong Lee

Jeong-Han Bae

Hongzhe Li

Hyuck-Min Kwon

Chanyoung Lee

According to some exemplary embodiments of the present disclosure, a method for identifying open source software (OSS) components using a processor of a computing device is disclosed. The method for identifying open source software (OSS) components may include: constructing a component database by performing redundancy elimination for each of a plurality of open source software; and identifying a component of target software by using the component database.

Method for identifying open-source software components at the source-code level

A vehicular electronic device hacking test apparatus includes a transmitter, a receiver, and a processor configured to classify a communication-connection procedure into a plurality of states based on a preset communication protocol, to generate a mutated packet appropriate for the plurality of states, and to transmit a vehicular electronic device through the transmitter, and to determine whether the vehicular electronic device is vulnerable to hacking based on whether a reception packet corresponding to the mutated packet is received through the receiver.

Apparatus for testing hacking of vehicle electronic device

A protocol model generator according to the present disclosure includes: a memory in which a protocol model generating program is stored; and a processor configured to execute the program. Herein, upon execution of the program, the processor extracts multiple strings from a binary corresponding to a protocol, generates a message pool including multiple candidate messages to be used in the protocol corresponding to the binary on the basis of the extracted multiple strings, and generates a protocol model corresponding to the protocol and configured to include nodes corresponding to the respective candidate messages included in the message pool. Further, the candidate messages include messages generated on the basis of the strings and response messages generated corresponding to the messages, and the protocol model is generated including one or more nodes and transition information between the nodes.

Protocol model generator and modeling method thereof

An apparatus for detecting code cloning of software includes a memory in which a program configured to detect code cloning from software is stored; and a processor configured to execute the program. Wherein the processor extracts multiple functions from a source code corresponding to the software, performs normalization and abstraction and compares the normalized and abstracted multiple functions with a vulnerable code clone set to determine whether there is code cloning of the software, and the vulnerable code clone set includes multiple vulnerable codes which are extracted from multiple functions included in other software, and normalized, abstracted and then stored.

Apparatus and method for detecting code cloning of software

A device for integrity verification of image data. The device comprises: a database configured to store multiple field signatures respectively corresponding to multiple editing tools; a memory configured to store a program for integrity verification of image data; and a processor configured to execute the program stored in the memory. The processor: extracts a field from the image data when the program is executed; determines whether or not there is a field signature matched with the extracted field from among the multiple field signatures; and determines whether or not the image data are edited depending on a result of the determination.

Device for integrity verification of image data and method for integrity verification using the same

The present disclosure includes: a communication module; a memory that stores a secret key encryption and restoration program; and a processor that executes the program, wherein when a request for restoration of a secret key is received from a user, the processor restores the secret key of which restoration is requested on the basis of restoration information received from each of a key management server and one or more trusted devices according to execution of the program, the secret key of the user is generated and encrypted by the processor in response to the request from the user, and the restoration information is generated corresponding to the secret key and then transmitted to each of the key management server and the one or more trusted devices through the communication module.

Device, server and method for providing secret key encryption and restoration

The present disclosure includes: searching a code clone corresponding to a used source code from any analysis target source code; detecting a security sink and sensitive data of the security sink on the basis of patch information in the searched code clone; acquiring a source code which is from the user input point the a security sink by backwardly tracing the sensitive data detected in the analysis target source code; and verifying whether the searched code clone is a vulnerability in the analysis target source code by performing a concolic testing on the basis of a path from the input point to the security sink.

Software vulnerability analysis method and device

The present invention discloses an application attestation server and an application attestation method. Specially, there is provided an application attestation server that attests a certain application in a smart device, the application attestation server comprising: an executable code generation unit configured to generate executable codes for attestation with respect to the application; a transceiver configured to transmit an executable code randomly selected from the generated executable codes to the smart device, and receive a result of execution of the selected executable code with respect to the application from the smart device; a malicious application analysis unit configured to analyze whether the application is a malicious application based on the received result; and an analysis result providing unit configured to provide an analysis result of the malicious application analysis unit to a user. Herein, the executable code generation unit configures to generate the executable codes by randomly combining information relevant to the application.

Server and method for attesting application in smart device using random executable code

A router is provided. The router includes a packet marking unit that inserts marking information generated based on an address of the router into a packet received by the router, according to a packet marking probability that is dynamically set, and a marking probability determination unit that calculates filtering efficiency of the router, and determines the packet marking probability based on the filtering efficiency. The marking information is used to obtain the address of the router by a device that has received the packet containing the marking information.

Adaptive probabilistic packet filtering router and method thereof

This document describes techniques for using features extracted from a URL to detect a malicious URL and categorize the malicious URL as one of a phishing URL, a spamming URL, a malware URL or a multi-type attack URL. The techniques employ one or more machine learning algorithms to train classification models using a set of training data which includes a known set of benign URLs and a known set of malicious URLs. The classification models are then employed to detect and/or categorize a malicious URL.

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Seoul, South Korea

Heejo Lee