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Kyuhong Park

dblp:200/1946 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2022
0000-0002-6040-0204ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 1 first-author · 2 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Systems and software security · 67% Malware analysis · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security
binary analysis
0.512021
DeepReflect: Discovering Malicious Functionality through Binary Reconstruction · USENIX Security Symposium 2021
Systems and software security › binary analysis
function identification
0.512021
DeepReflect: Discovering Malicious Functionality through Binary Reconstruction · USENIX Security Symposium 2021

Methods — techniques the papers use, named apart from their topics

machine learning · 0.5binary reconstruction · 0.5
YearPublicationVenuePosition
2022 The effect of TV drama piracy: An analysis of digital piracy users, internet buzz, and TV drama viewership
Dongyeon Kim, Kyuhong Park, Youngsok Bang
Inf. Manag.2
2021 Identifying Behavior Dispatchers for Malware Analysis
abstract
Malware is a major threat to modern computer systems. Malicious behaviors are hidden by a variety of techniques: code obfuscation, message encoding and encryption, etc. Countermeasures have been developed to thwart these techniques in order to expose malicious behaviors. However, these countermeasures rely heavily on identifying specific API calls, which has significant limitations as these calls can be misleading or hidden from the analyst. In this paper, we show that malicious programs share a key component which we call a behavior dispatcher, a code structure which is intercepted between various condition checks and malicious actions. By identifying these behavior dispatchers, a malware analysis can be guided into behavior dispatchers and activate hidden malicious actions more easily. We propose BDHunter, a system that automatically identifies behavior dispatchers to assist triggering malicious behaviors. BDHunter takes advantage of the observation that a dispatcher compares an input with a set of expected values to determine which malicious behaviors to execute next. We evaluate BDHunter on recent malware samples to identify behavior dispatchers and show that these dispatchers can help trigger more malicious behaviors (otherwise hidden). Our experimental results show that BDHunter identifies 77.4% of dispatchers within the top 20 candidates discovered. Furthermore, BDHunter-guided concolic execution successfully triggers 13.0x and 2.6x more malicious behaviors, compared to unguided symbolic and concolic execution, respectively. These demonstrate that BDHunter effectively identifies behavior dispatchers, which are useful for exposing malicious behaviors.
Kyuhong Park, Burak Sahin, Yongheng Chen, Jisheng Zhao, Evan Downing, Hong Hu 0004, Wenke Lee
AsiaCCS1
2021 DeepReflect: Discovering Malicious Functionality through Binary Reconstruction
Evan Downing, Yisroel Mirsky, Kyuhong Park, Wenke Lee
USENIX Security Symposium3