Sang Kil Cha

Sang Kil Cha

KAIST

H-index: 22

Asia-South Korea

About Sang Kil Cha

Sang Kil Cha, With an exceptional h-index of 22 and a recent h-index of 22 (since 2020), a distinguished researcher at KAIST, specializes in the field of Security, Software Engineering, Program Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Method and system for fuzzing windows kernel by utilizing type information obtained through binary static analysis

Evaluating Directed Fuzzers: Are We Heading in the Right Direction?

BotScreen: Trust Everybody, but Cut the Aimbots Yourself

DAFL: Directed Grey-box Fuzzing guided by Data Dependency

Reassembly is hard: a reflection on challenges and strategies

FunProbe: Probing Functions from Binary Code through Probabilistic Analysis

On the Effectiveness of Synthetic Benchmarks for Evaluating Directed Grey-box Fuzzers

Fuzzle: Making a puzzle for fuzzers

Sang Kil Cha Information

University

Position

School of Computing

Citations(all)

4161

Citations(since 2020)

2888

Cited By

2194

hIndex(all)

22

hIndex(since 2020)

22

i10Index(all)

27

i10Index(since 2020)

25

Email

University Profile Page

Google Scholar

Sang Kil Cha Skills & Research Interests

Security

Software Engineering

Program Analysis

Top articles of Sang Kil Cha

Method and system for fuzzing windows kernel by utilizing type information obtained through binary static analysis

2024/1/2

Evaluating Directed Fuzzers: Are We Heading in the Right Direction?

2024

Kihong Heo
Kihong Heo

H-Index: 11

Sang Kil Cha
Sang Kil Cha

H-Index: 14

BotScreen: Trust Everybody, but Cut the Aimbots Yourself

2023

Gihyuk Ko
Gihyuk Ko

H-Index: 2

Sang Kil Cha
Sang Kil Cha

H-Index: 14

DAFL: Directed Grey-box Fuzzing guided by Data Dependency

2023

Kihong Heo
Kihong Heo

H-Index: 11

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Reassembly is hard: a reflection on challenges and strategies

2023

FunProbe: Probing Functions from Binary Code through Probabilistic Analysis

2023/11/30

On the Effectiveness of Synthetic Benchmarks for Evaluating Directed Grey-box Fuzzers

Proceedings of the Asia-Pacific Software Engineering Conference

2023

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Fuzzle: Making a puzzle for fuzzers

2022/10/10

Soomin Kim
Soomin Kim

H-Index: 4

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Revisiting binary code similarity analysis using interpretable feature engineering and lessons learned

IEEE Transactions on Software Engineering

2022/7/1

How’d Security Benefit Reverse Engineers? The Implication of Intel CET on Function Identification

2022

SMARTIAN: Enhancing Smart Contract Fuzzing with Static and Dynamic Data-Flow Analyses

2021/11/15

NTFuzz: Enabling type-aware kernel fuzzing on windows with static binary analysis

2021/5/24

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Mind control attack: Undermining deep learning with GPU memory exploitation

Computers & Security

2021/3/1

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Hyunsoo Yoon
Hyunsoo Yoon

H-Index: 16

Boosting Fuzzer Efficiency: An Information Theoretic Perspective

2020/11/8

Marcel Böhme
Marcel Böhme

H-Index: 14

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Montage: A Neural Network Language Model-Guided JavaScript Fuzzer

2020/8/12

Ankou: Guiding Grey-box Fuzzing towards Combinatorial Difference

2020/6/27

Soomin Kim
Soomin Kim

H-Index: 4

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Asia's Surging Interest in Binary Analysis

Communications of the ACM

2020/3/20

Sang Kil Cha
Sang Kil Cha

H-Index: 14

Zhenkai Liang
Zhenkai Liang

H-Index: 24

Semantics-Preserving Mutation-Based Fuzzing on JavaScript Interpreters

Journal of the Korea Institute of Information Security & Cryptology

2020

Model-Based Fuzzing for Finding Kernel Vulnerabilities

2020

See List of Professors in Sang Kil Cha University(KAIST)