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Detecting IoT Botnet in 5G Core Network Using Machine Learning

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Computers, Materials & Continua 2022年第9期72卷 4467-4488页

作者： Ye-Eun Kim Min-Gyu Kim Hwankuk Kim department of Electronics information and System engineering Sangmyung UniversityCheonan-siKorea Department of Information Security Engineering Sangmyung UniversityCheonan-siKorea

As Internet of Things(IoT)devices with security issues are connected to 5G mobile networks,the importance of IoT Botnet detection research in mobile network environments is increasing.However,the existing research focused on AI-based IoT Botnet detection research in wired network environments.In addition,the existing research related to IoT Botnet detection in ML-based mobile network environments have been conducted up to 4G.Therefore,this paper conducts a study on ML-based IoT Botnet traffic detection in the 5G core network.The binary and multiclass classification was performed to compare simple normal/malicious detection and normal/threetype IoT Botnet malware detection.In both classification methods,the IoT Botnet detection performance using only 5GC’s GTP-U packets decreased by at least 22.99%of accuracy compared to detection in wired network environment.In addition,by conducting a feature importance experiment,the importance of feature study for IoT Botnet detection considering 5GC network characteristics was confirmed.Since this paper analyzed IoT botnet traffic passing through the 5GC network using ML and presented detection results,think it will be meaningful as a reference for research to link AI-based security to the 5GC network.

关键词： IoT botnet 5G B5G malware machine learning

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 U.S.oil pipeline company),showed that security threats by malware have become serious enough to affect industries and social infrastructure rather than individuals alone.The agents and characteristics of attacks should be identified,and appropriate strategies should be established accordingly in order to respond to such attacks.For this purpose,the first task that must be performed is malware classification.Malware creators are well aware of this and apply various concealment and avoidance techniques,making it difficult to classify malware.This study focuses on new features and classification techniques to overcome these difficulties.We 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 programs.We extracted the usage patterns of the system resources for ransomware to performbehavioral performance visualization.The results of the classification performance evaluation using the visualization results indicate an accuracy of at least 98.94%with a 3.69%loss rate.Furthermore,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

Identifying and Verifying Vulnerabilities through PLC Network Protocol and Memory Structure Analysis

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Computers, Materials & Continua 2020年第10期65卷 53-67页

作者： Joo-Chan Lee Hyun-Pyo Choi Jang-Hoon Kim Jun-Won Kim Da-Un Jung Ji-Ho Shin Jung-Taek Seo Department of Information Security Engineering Soonchunhyang UniversityAsan31538Korea

Cyberattacks on the Industrial Control System(ICS)have recently been increasing,made more intelligent by advancing technologies.As such,cybersecurity for such systems is attracting attention.As a core element of control devices,the Programmable Logic Controller(PLC)in an ICS carries out on-site control over the ICS.A cyberattack on the PLC will cause damages on the overall ICS,with Stuxnet and Duqu as the most representative cases.Thus,cybersecurity for PLCs is considered essential,and many researchers carry out a variety of analyses on the vulnerabilities of PLCs as part of preemptive efforts against attacks.In this study,a vulnerability analysis was conducted on the XGB PLC.security vulnerabilities were identified by analyzing the network protocols and memory structure of PLCs and were utilized to launch replay attack,memory modulation attack,and FTP/Web service account theft for the verification of the results.Based on the results,the attacks were proven to be able to cause the PLC to malfunction and disable it,and the identified vulnerabilities were defined.

关键词： Industrial control system programmable logic controller cybersecurity network protocol vulnerability

RECTANGLE: a bit-slice lightweight block cipher suitable for multiple platforms

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Science China(information Sciences) 2015年第12期58卷 89-103页

作者： ZHANG WenTao BAO ZhenZhen LIN DongDai Vincent RIJMEN YANG Bo Han Ingrid VERBAUWHEDE State Key Laboratory of information security Institute of Information EngineeringChinese Academy of Sciences department of Electrical engineering ESAT COSIC and i Minds Security Department

In this paper, we propose a new lightweight block cipher named RECTANGLE. The main idea of the design of RECTANGLE is to allow lightweight and fast implementations using bit-slice techniques. RECTANGLE uses an SP-network. The substitution layer consists of 16 4 × 4 S-boxes in parallel. The permutation layer is composed of 3 rotations. As shown in this paper, RECTANGLE offers great performance in both hardware and software environment, which provides enough flexibility for different application scenario. The following are3 main advantages of RECTANGLE. First, RECTANGLE is extremely hardware-friendly. For the 80-bit key version, a one-cycle-per-round parallel implementation only needs 1600 gates for a throughput of 246 Kbits/s at100 k Hz clock and an energy efficiency of 3.0 p J/bit. Second, RECTANGLE achieves a very competitive software speed among the existing lightweight block ciphers due to its bit-slice style. Using 128-bit SSE instructions,a bit-slice implementation of RECTANGLE reaches an average encryption speed of about 3.9 cycles/byte for messages around 3000 bytes. Last but not least, we propose new design criteria for the RECTANGLE S-box.Due to our careful selection of the S-box and the asymmetric design of the permutation layer, RECTANGLE achieves a very good security-performance tradeoff. Our extensive and deep security analysis shows that the highest number of rounds that we can attack, is 18(out of 25).

关键词： lightweight cryptography block cipher design bit-slice hardware efficiency software efficiency

A Model Training Method for DDoS Detection Using CTGAN under 5GC Traffic

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Computer Systems Science & engineering 2023年第10期47卷 1125-1147页

作者： Yea-Sul Kim Ye-Eun Kim Hwankuk Kim department of Electronics information and System engineering Sangmyung UniversityCheonan31066Korea Department of Information Security Engineering Sangmyung UniversityCheonan31066Korea

With the commercialization of 5th-generation mobile communications(5G)networks,a large-scale internet of things(IoT)environment is being built.security is becoming increasingly crucial in 5G network environments due to the growing risk of various distributed denial of service(DDoS)attacks across vast IoT devices.Recently,research on automated intrusion detection using machine learning(ML)for 5G environments has been actively conducted.However,5G traffic has insufficient data due to privacy protection problems and imbalance problems with significantly fewer attack data.If this data is used to train an ML model,it will likely suffer from generalization errors due to not training enough different features on the attack data.Therefore,this paper aims to study a training method to mitigate the generalization error problem of the ML model that classifies IoT DDoS attacks even under conditions of insufficient and imbalanced 5G traffic.We built a 5G testbed to construct a 5G dataset for training to solve the problem of insufficient data.To solve the imbalance problem,synthetic minority oversampling technique(SMOTE)and generative adversarial network(GAN)-based conditional tabular GAN(CTGAN)of data augmentation were used.The performance of the trained ML models was compared and meaningfully analyzed regarding the generalization error problem.The experimental results showed that CTGAN decreased the accuracy and f1-score compared to the Baseline.Still,regarding the generalization error,the difference between the validation and test results was reduced by at least 1.7 and up to 22.88 times,indicating an improvement in the problem.This result suggests that the ML model training method that utilizes CTGANs to augment attack data for training data in the 5G environment mitigates the generalization error problem.

关键词： 5G core traffic machine learning SMOTE GAN-CTGAN IoT DDoS detection tabular form cyber security B5G mobile network security

Quantum Private Comparison of Equality Based on Five-Particle Cluster State

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Communications in Theoretical Physics 2016年第12期65卷 621-628页

作者：昌燕张文博张仕斌王海春闫丽丽韩桂华盛志伟黄源源索望熊金鑫 Department of Information Security Engineering Chengdu University of Information Technology School of Economics Sichuan University

A protocol for quantum private comparison of equality(QPCE) is proposed based on five-particle cluster state with the help of a semi-honest third party(TP). In our protocol, TP is allowed to misbehave on its own but can not conspire with either of two parties. Compared with most two-user QPCE protocols, our protocol not only can compare two groups of private information(each group has two users) in one execution, but also compare just two private information. Compared with the multi-user QPCE protocol proposed, our protocol is safer with more reasonable assumptions of TP. The qubit efficiency is computed and analyzed. Our protocol can also be generalized to the case of 2N participants with one TP. The 2N-participant protocol can compare two groups(each group has N private information)in one execution or just N private information.

关键词：量子效率粒子团簇私人信息多用户参与者协议第三方

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Review of Public-Key Cryptosystem Based on the Error Correcting Code

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Wuhan University Journal of Natural Sciences 2014年第6期19卷 489-496页

作者： LI Zhongyuan QU Chengqin ZHOU Xueguang ZHUO Lifeng department of information security Naval University of Engineering

The paper review the public-key cryptosystems based on the error correcting codes such as Goppa code, BCH code, RS code, rank distance code, algebraic geometric code as well as LDPC code, and made the comparative analyses of the merits and drawbacks of them. The cryptosystem based on Goppa code has high security, but can be achieved poor. The cryptosystems based on other error correcting codes have higher performance than Goppa code. But there are still some disadvantages to solve. At last, the paper produce an assumption of the Niederreiter cascade combination cryptosystem based on double public-keys under complex circumstances, which has higher performance and security than the traditional cryptosystems.

关键词： error correcting code public-key cryptosystem cascaded code safety

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SecBCS: a secure and privacy-preserving blockchain-based crowdsourcing system

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Science China(information Sciences) 2020年第3期63卷 20-33页

作者： Chao LIN Debiao HE Sherali ZEADALLY Neeraj KUMAR Kim-Kwang Raymond CHOO Key Laboratory of Aerospace information security and Trusted Computing Ministry of EducationSchool of Cyber Science and Engineering Wuhan University State Key Laboratory of Cryptology College of Communication and information University of Kentucky department of Computer Science and engineering Thapar University department of information Systems and Cyber security and department of Electrical and Computer engineering University of Texas at San Antonio

A robust and scalable crowd management infrastructure is crucial in addressing operational challenges when deploying high-density sensors and actuators in a smart city. While crowdsourcing is widely used in crowd management, conventional solutions, such as Upwork and Amazon Mechanical Turk, generally depend on a trusted third-party platform. There exist several potential security concerns(e.g., sensitive leakage, single point of failure and unfair judgment) in such a centralized paradigm. Hence, a recent trend in crowdsourcing is to leverage blockchain(a decentralized ledger technology) to address some of the existing limitations. A small number of blockchain-based crowdsourcing systems(BCSs) with incentive mechanisms have been proposed in the literature, but they are generally not designed with security in mind. Thus, we study the security and privacy requirements of a secure BCS and propose a concrete solution(i.e., SecBCS)with a prototype implementation based on JUICE.

关键词： crowdsourcing blockchain secure privacy-preserving smart contract

A more compact multi-id identity-based FHE scheme in the standard model and its applications

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Science China(information Sciences) 2019年第3期62卷 190-192页

作者： Xueqing WANG Biao WANG Bei LIANG Rui XUE State Key Laboratory of information security Institute of Information EngineeringChinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences department of Computer Science and engineering Chalmers University of Technology

Dear editor,Fully homomorphic encryption (FHE) is a cryptographic primitive that allows anyone, even those without a secret key, to perform arbitrary computation on encrypted data. Since Gentry’s breakthrough realization of FHE in 2009 [1], the research on FHE has been blown out. Furthermore,López-Alt et al.[2] proposed a new notion of multi-

关键词： IBE CPA A more compact multi-id identity-based FHE scheme in the standard model and its applications IND