• Title/Summary/Keyword: 사이버위협정보

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VPN-Filter Malware Techniques and Countermeasures in IoT Environment (사물인터넷 환경에서의 VPN-Filter malware 기술과 대응방법)

  • Kim, Seung-Ho;Lee, Keun-Ho
    • Journal of Convergence for Information Technology
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    • v.8 no.6
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    • pp.231-236
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    • 2018
  • Recently, a wide variety of IoT environment is being created due to the rapid development of information and communication technology. And accordingly in a variety of network structures, a countless number of attack techniques and new types of vulnerabilities are producing a social disturbance. In May of 2018, Talos Intelligence, the Cisco threat intelligence team has newly discovered 'VPN-Filter', which constitutes a large-scale IoT-based botnet, is infecting consumer routers in over 54 countries around the world. In this paper, types of IoT-based botnets and the attack techniques utilizing botnet will be examined and the countermeasure technique through EXIF metadata removal method which is the cause of connection method of C & C Server will be proposed by examining the characteristics of attack vulnerabilities and attack scenarios of VPN-Filter.

A Study on Human Vulnerability Factors of Companies : Through Spam Mail Simulation Training Experiments (스팸메일 모의훈련 현장실험을 통한 기업의 인적 취약요인 연구)

  • Lee, Jun-hee;Kwon, Hun-yeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.4
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    • pp.847-857
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    • 2019
  • Recently, various cyber threats such as Ransomware and APT attack are increasing by e-mail. The characteristic of such an attack is that it is important to take administrative measures by improving personal perception of security because it bypasses technological measures such as past pattern-based detection The purpose of this study is to investigate the human factors of employees who are vulnerable to spam mail attacks through field experiments and to establish future improvement plans. As a result of sending 7times spam mails to employees of a company and analyzing training report, It was confirmed that factors such as the number of training and the recipient 's gender, age, and workplace were related to the reading rate. Based on the results of this analysis, we suggest ways to improve the training and to improve the ability of each organization to carry out effective simulation training and improve the ability to respond to spam mail by awareness improvement.

A Home Management System Using Smart Devices in an IoT Environment (IoT 환경에서의 스마트디바이스를 활용한 주택관리시스템)

  • Ryu, Chang-Su
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.807-808
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    • 2016
  • With the recent rise in nuclear families and single-member families, there is a need for the kind of home management unaffected by neither space nor time. Moreover, electronic devices in and around the home need to be managed efficiently and prevented from overheating, and there is an increasing risk of fire, theft, and leak of personal data with these devices, which is leading to an increase in the economic costs. Accordingly, there is a growing need for an efficient and secure smart home management system. This paper proposes a home management system that uses smart devices. This system has addressed the shortcomings of a conventional Internet-based home network. Furthermore, it communicates with IoT-enabled devices and features intelligent information home appliances that are isolated from personally identifiable information and which are secure against advanced persistent threats, a type of cyber-attack.

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A Study on the Security Enhancement for Personal Healthcare Information of CloudHIS (CloudHIS의 개인 의료정보를 위한 보안강화에 관한 연구)

  • Cho, Young-Sung;Chung, Ji-Moon;Na, Won-Shik
    • Journal of Convergence for Information Technology
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    • v.9 no.9
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    • pp.27-32
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    • 2019
  • Along with the growth of u-Healthcare, we propose a security enhancement based on network separation for CloudHIS with for handling healthcare information to cope with cyber attack. To protect against all security threats and to establish clear data security policies, we apply desktop computing servers to cloud computing services for CloudHIS. Use two PCs with a hypervisor architecture to apply physical network isolation and select the network using KVM switched controller. The other is a logical network separation using one PC with two OSs, but the network is divided through virtualization. Physical network separation is the physical connection of a PC to each network to block the access path from both the Internet and the business network. The proposed system is an independent desktop used to access an intranet or the Internet through server virtualization technology on a user's physical desktop computer. We can implement an adaptive solution to prevent hacking by configuring the CloudHIS, a cloud system that handles medical hospital information, through network separation for handling security enhancement.

User Behavior Analysis for Online Game Bot Detection (온라인 게임 봇 탐지를 위한 사용자 행위 분석)

  • Kang, Ah-Reum;Woo, Ji-young;Park, Ju-yong;Kim, Huy-Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.2
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    • pp.225-238
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    • 2012
  • Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users' main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.

Efficient Coverage Guided IoT Firmware Fuzzing Technique Using Combined Emulation (복합 에뮬레이션을 이용한 효율적인 커버리지 가이드 IoT 펌웨어 퍼징 기법)

  • Kim, Hyun-Wook;Kim, Ju-Hwan;Yun, Joobeom
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.5
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    • pp.847-857
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    • 2020
  • As IoT equipment is commercialized, Bluetooth or wireless networks will be built into general living devices such as IP cameras, door locks, cars and TVs. Security for IoT equipment is becoming more important because IoT equipment shares a lot of information through the network and collects personal information and operates the system. In addition, web-based attacks and application attacks currently account for a significant portion of cyber threats, and security experts are analyzing the vulnerabilities of cyber attacks through manual analysis to secure them. However, since it is virtually impossible to analyze vulnerabilities with only manual analysis, researchers studying system security are currently working on automated vulnerability detection systems, and Firm-AFL, published recently in USENIX, proposed a system by conducting a study on fuzzing processing speed and efficiency using a coverage-based fuzzer. However, the existing tools were focused on the fuzzing processing speed of the firmware, and as a result, they did not find any vulnerability in various paths. In this paper, we propose IoTFirmFuzz, which finds more paths, resolves constraints, and discovers more crashes by strengthening the mutation process to find vulnerabilities in various paths not found in existing tools.

A Study of Worm Propagation Modeling extended AAWP, LAAWP Modeling (AAWP와 LAAWP를 확장한 웜 전파 모델링 기법 연구)

  • Jun, Young-Tae;Seo, Jung-Taek;Moon, Jong-Sub
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.5
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    • pp.73-86
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    • 2007
  • Numerous types of models have been developed in recent years in response to the cyber threat posed by worms in order to analyze their propagation and predict their spread. Some of the most important ones involve mathematical modeling techniques such as Epidemic, AAWP (Analytical Active Worm Propagation Modeling) and LAAWP (Local AAWP). However, most models have several inherent limitations. For instance, they target worms that employ random scanning in the entire nv4 network and fail to consider the effects of countermeasures, making it difficult to analyze the extent of damage done by them and the effects of countermeasures in a specific network. This paper extends the equations and parameters of AAWP and LAAWP and suggests ALAAWP (Advanced LAAWP), a new worm simulation technique that rectifies the drawbacks of existing models.

Data Modeling for Cyber Security of IoT in Artificial Intelligence Technology (인공지능기술의 IoT 통합보안관제를 위한 데이터모델링)

  • Oh, Young-Taek;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.57-65
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    • 2021
  • A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

Threat Diagnostic Checklists of Security Service in 5G Communication Network Virtualization Environment (5G 통신 네트워크 가상화 환경에서 보안 서비스의 위협 진단 체크리스트)

  • Hong, Jin-Keun
    • Journal of Convergence for Information Technology
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    • v.11 no.10
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    • pp.144-150
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    • 2021
  • The purpose of this paper is to review the direction of the slicing security policy, which is a major consideration in the context of standardization in 5G communication network security, to derive security vulnerability diagnosis items, and to present about analyzing and presenting the issues of discussion for 5G communication network virtualization. As for the research method, the direction of virtualization security policy of 5G communication network of ENISA (European Union Agency for Cybersecurity), a European core security research institute, and research contents such as virtualization security policy and vulnerability analysis of 5G communication network from related journals were used for analysis. In the research result of this paper, the security structure in virtualization security of 5G communication network is arranged, and security threats and risk management factors are derived. In addition, vulnerability diagnosis items were derived for each security service in the risk management area. The contribution of this study is to summarize the security threat items in 5G communication network virtualization security that is still being discussed, to be able to gain insights of the direction of European 5G communication network cybersecurity, and to derive vulnerabilities diagnosis items to be considered for virtualization security of 5G communication network. In addition, the results of this study can be used as basic data to develop vulnerability diagnosis items for virtualization security of domestic 5G communication networks. In the future, it is necessary to study the detailed diagnosis process for the vulnerability diagnosis items of 5G communication network virtualization security.

A Study on Automatic Classification Technique of Malware Packing Type (악성코드 패킹유형 자동분류 기술 연구)

  • Kim, Su-jeong;Ha, Ji-hee;Lee, Tae-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.5
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    • pp.1119-1127
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    • 2018
  • Most of the cyber attacks are caused by malicious codes. The damage caused by cyber attacks are gradually expanded to IoT and CPS, which is not limited to cyberspace but a serious threat to real life. Accordingly, various malicious code analysis techniques have been appeared. Dynamic analysis have been widely used to easily identify the resulting malicious behavior, but are struggling with an increase in Anti-VM malware that is not working in VM environment detection. On the other hand, static analysis has difficulties in analysis due to various packing techniques. In this paper, we proposed malware classification techniques regardless of known packers or unknown packers through the proposed model. To do this, we designed a model of supervised learning and unsupervised learning for the features that can be used in the PE structure, and conducted the results verification through 98,000 samples. It is expected that accurate analysis will be possible through customized analysis technology for each class.