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AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

computers, Materials & Continua 2024年第11期81卷 3371-3393页

作者： Juhwan Kim Baehoon Son Jihyeon Yu Joobeom Yun Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Republic of Korea

Digital forensics aims to uncover evidence of cybercrimes within compromised *** cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised *** analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather ***,forensic analysts must sift through extensive datasets to isolate pertinent ***,manually identifying suspicious traces among numerous artifacts is time-consuming and *** studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital *** the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific *** this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital *** system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly *** key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic *** evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative *** system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

关键词： Digital forensics autoencoder logarithmic entropy prioritization anomaly detection windows artifacts artificial intelligence

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Adaptive Emulation Framework for Multi-Architecture IoT Firmware Testing

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computers, Materials & Continua 2023年第5期75卷 3291-3315页

作者： Jihyeon Yu Juhwan Kim Youngwoo Lee Fayozbek Rustamov Joobeom Yun Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer and Information Security Sejong UniversitySeoul05006Korea

Internet of things(IoT)devices are being increasingly used in numerous ***,the low priority on security and various IoT types have made these devices vulnerable to *** prevent this,recent studies have analyzed firmware in an emulation environment that does not require actual devices and is efficient for repeated ***,these studies focused only on major firmware architectures and rarely considered exotic *** addition,because of the diversity of firmware,the emulation success rate is not high in terms of large-scale *** this study,we propose the adaptive emulation framework for multi-architecture(AEMA).In the field of automated emulation frameworks for IoT firmware testing,AEMA considers the following issues:(1)limited compatibility for exotic firmware architectures,(2)emulation instability when configuring an automated environment,and(3)shallow testing range resulting from structured *** tackle these problems,AEMAcan emulate not onlymajor firmware architectures but also exotic firmware architectures not previously considered,such as Xtensa,ColdFire,and reduced instruction set computer(RISC)version five,by implementing a minority ***,we applied the emulation arbitration technique and input keyword extraction technique for emulation stability and efficient test case *** compared AEMA with other existing frameworks in terms of emulation success rates and fuzz *** a result,AEMA succeeded in emulating 864 out of 1,083 overall experimental firmware and detected vulnerabilities at least twice as fast as the experimental ***,AEMAfound a 0-day vulnerability in realworld IoT devices within 24 h.

关键词： Internet of things(IoT) emulation framework firmware fuzzing concolic execution vulnerability

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Privacy Enhanced P2P Power Trading Using DID-Based Identity Verification in a Microgrid 25th

Privacy Enhanced P2P Power Trading Using DID-Based Identity ...

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25th International Conference on information security Applications, WISA 2024

作者： Lee, Taeyang Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul Korea Republic of

ISBN: (纸本)9789819616237

Smart meters play a crucial role in accurately measuring power usage and distribution data in microgrids. However, fine-grained data collection raises significant privacy concerns. To address this, it is essential to develop a distributed power trading system that is both trustworthy and privacy-preserving. In this paper, we propose a peer-to-peer power trading mechanism that ensures privacy through identity verification based on decentralized identifiers, zero-knowledge proofs, and pseudonyms. Besides, we introduce an efficient claims verification scheme with Boneh-Lynn-Shacham aggregate signature. We also validate the security of our proposed mechanism through the Real-or-Random model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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Ransomware Classification Framework Using the Behavioral Performance Visualization of Execution Objects

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computers, Materials & Continua 2022年第8期72卷 3401-3424页

作者： Jun-Seob Kim Ki-Woong Park Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A ransomware attack that interrupted the operation of Colonial Pipeline(a large *** pipeline company),showed that security threats by malware have become serious enough to affect industries and social infrastructure rather than individuals *** agents and characteristics of attacks should be identified,and appropriate strategies should be established accordingly in order to respond to such *** this purpose,the first task that must be performed is malware *** creators are well aware of this and apply various concealment and avoidance techniques,making it difficult to classify *** study focuses on new features and classification techniques to overcome these *** propose a behavioral performance visualization method using utilization patterns of system resources,such as the central processing unit,memory,and input/output,that are commonly used in performance analysis or tuning of *** extracted the usage patterns of the system resources for ransomware to performbehavioral performance *** results of the classification performance evaluation using the visualization results indicate an accuracy of at least 98.94%with a 3.69%loss ***,we designed and implemented a framework to perform the entire process—from data extraction to behavioral performance visualization and classification performance measurement—that is expected to contribute to related studies in the future.

关键词： Behavioral performance visualization ransomware malware classification

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security Function for 5G-Advanced and 6G: Malicious UE Detection in Network Slicing 25th

Security Function for 5G-Advanced and 6G: Malicious UE Det...

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25th International Conference on information security Applications, WISA 2024

作者： Park, Jaehyoung Kim, Jihye Lee, Jong-Hyouk Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Department of Computer and Information Security Sejong University Seoul05006 Korea Republic of

ISBN: (纸本)9789819616237

Starting with Software Defined Networking (SDN) and Network Functions Virtualization (NFV) technologies, network slicing is emerging as a critical technology in 5G-Advanced and 6G mobile communications to allocate logical networks end-to-end, meeting diverse service requirements. However, the advent of network slicing introduces new security threats, including inter-slice security, intra-slice security, and lifecycle security of network slicing. While recent research has focused on security orchestration technologies using SDN/NFV for network slicing and AI-based attack detection, there remains a gap in research on security by design within the components of 3GPP 5G systems. Therefore, this paper investigates security by design in the 5G-Advanced and 6G architectures. To address these issues, we propose a malicious User Equipment (UE) detection function to identify attacks within the network-slicing environment. We illustrate the interaction between the detection function and other 3GPP 5G system components for network slicing security with its algorithm for detecting malicious UEs in network slices. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Malicious UE Network Slicing security by Design

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ARP Spoofing Mitigation for the E2 Interface in Open RAN: An xApp Approach 25th

ARP Spoofing Mitigation for the E2 Interface in Open RAN:...

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25th International Conference on information security Applications, WISA 2024

作者： Kim, Jihye Park, Jaehyoung Lee, Jong-Hyouk Department of Computer and Information Security Sejong University Seoul05006 Korea Republic of Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of

ISBN: (纸本)9789819616237

In the 5G-Advanced and 6G era, the Open Radio Access Network (Open RAN) will support hardware and software interoperability between different vendors. The O-RAN Alliance, which leads the Open RAN initiative, has released standards addressing potential threats and mitigation requirements to the framework. While the standards specify Man-in-the-Middle (MitM) attacks on the E2 interface and recommend using IPsec, a Layer 3 security protocol, they do not cover defenses against Layer 2 attacks, such as Address Resolution Protocol (ARP) spoofing. This paper proposes an xApp with preventive and reactive mechanisms to protect the E2 interface from ARP spoofing in Open RAN. The xApp proactively prevents attacks through a static ARP table and continuously monitors the E2 interface to detect and react to the ARP spoofing, offering better network resilience than existing methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Radio access networks

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A Method for De-Identification Analysis of Encrypted Video 9

A Method for De-Identification Analysis of Encrypted Video

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Joint 9th International Conference on Digital Arts, Media and Technology with 7th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Kim, Deok-Han Kim, Young-Gab Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of

ISBN: (纸本)9798350318241

As the variety of video content increases, so does the likelihood of data breaches of sensitive personal information. Consequently, several video de-identification techniques have been developed to protect personal data, alongside ongoing research into video encryption technology, which offers the advantage of decryption to obtain the original video without storing a separate video copy. While it is possible to visually evaluate whether individual encrypted frames have been correctly de-identified, human interpretation makes this method vulnerable to subjective bias. Many video encryption studies employ traditional image quality evaluation metrics, such as peak signal-to-noise ratio and structural similarity index measure (SSIM), to objectively demonstrate the de-identification of encrypted videos. However, these metrics prove to be insufficiently effective for this purpose. These image metrics can measure the de-identification rate of a single frame in encrypted videos, but not the entire video. This study introduces a quantitative analysis method to confirm de-identification in fully encrypted videos. In this study, we measured the de-identification rates of all frames of encrypted videos using a weighted sum of SSIM and edge differential ratio. We also measured the de-identification rate of a fully encrypted video. Finally, we graphically analyzed these data using line charts. This objective methodology enabled the identification of portions of the encrypted video where de-identification techniques may not have been appropriately applied. © 2024 IEEE.

关键词： Quality control

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Improved MIMO Signal Detection Based on DNN in MIMO-OFDM System

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computers, Materials & Continua 2022年第2期70卷 3625-3636页

作者： Jae-Hyun Ro Jong-Gyu Ha Woon-Sang Lee Young-Hwan You Hyoung-Kyu Song Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO detection based on the ensemble machine learning,all learning models for the DNN are generated in offline and the detection is performed in online by using already learned *** the offline learning,the received signals and channel coefficients are set to input data,and the labels which correspond to transmit symbols are set to output *** the online learning,the perfectly learned models are used for signal detection where the models have fixed bias and *** performance improvement,the proposed scheme uses the majority vote and the maximum probability as the methods of the model combinations for obtaining diversity gains at the MIMO *** simulation results show that the proposed scheme has improved symbol error rate(SER)performance without additional receive antennas.

关键词： MIMO DNN ensemble machine learning ML

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Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

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computers, Materials & Continua 2022年第1期70卷 491-504页

作者： Hyun-Sun Hwang Jae-Hyun Ro Chan-Yeob Park Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is *** this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO *** massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational ***,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel *** GS has good performance by using previous calculation results as ***,the required time for obtaining the precoding symbols is too long due to the sequential process of ***,the HGS with parallel calculation is proposed in this paper to reduce the required *** rows of channel matrix are eliminated for parallel calculation *** addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel *** HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.

关键词： Massive MIMO GS matrix inversion linear precoding

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Plotting OSS-Based Supply Chain Attack Strategies and the Defense Failure 25th

Plotting OSS-Based Supply Chain Attack Strategies and the ...

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25th International Conference on information security Applications, WISA 2024

作者： Sarang, Arpita Dinesh Choi, Sang-Hoon Park, Ki-Woong SysCore Lab Department of Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of SysCore Lab Sejong University Seoul05006 Korea Republic of Department of Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of

ISBN: (纸本)9789819616237

The supply chain attack, which targets open-source software, is currently the most discussed cyberattack. This is due to the recent open-source XZ utils and PyPI projects based attacks where the attackers employed similar strategies. A backdoor was injected in the libraries developed by these projects for future exploitation when software users installed them on systems. These attacks were executed by the trusted developers of these projects and influenced by unknown promoters. Therefore, there is a need to scrutinize Open Source Software (OSS) security to protect the legacy of Open Software development for the future. This paper provides an overview of these two attack strategies through their case studies, which aid in the creation of a generic attack framework for supply chain attacks on OSS. We present the existing detection methods for OSS security in this work and their lacunas taking into account at various stages of a supply chain attack. This makes it necessary to build platforms that allow the current OSS security detection modules to be utilized in sequence. Therefore, we introduce an OSS security Detection platform that does not completely address the limitations of the detection technique, but when combined, they can maximize the effectiveness of an OSS security quality check. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cyber attacks

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