• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.63-66
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• 2019

Recently, as the technology of drones develops, a malicious attack using a drones becomes a problem, and an anti-drone technology for detecting an attack dron for a malicious attack is required. However, currently used drone detection systems are expensive and require a lot of manpower. Therefore, in this paper, we propose an anti - drone method using the analysis and algorithms of the anti - drone that can monitor the attack drones. In this paper, we identify and detect attack drones using sniffing, and propose capture and deception algorithm through spoofing using current GPS based detection system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.113-120
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• 2022

In this paper, we analyze the feasibility of the IP spoofing attack exploiting null security algorithms in 5G networks based on 3GPP standard specifications. According to 3GPP standard specifications, the initial Registration Request message is not protected by encryption and integrity. The IP spoofing attack exploits the vulnerability that allows a malicious gNB (next generation Node B) to modify the contents of the initial Registration Request message of a victim UE (User Equipment) before forwarding it to AMF (Access and Mobility Management Function). If the attack succeeds, the victim UE is disconnected from the 5G network and a malicious UE gets Internet services, while the 5G operator will charge the victim UE. In this paper, we analyze the feasibility of the IP spoofing attack by analyzing whether each signaling message composing the attack conforms to the 3GPP Rel-17 standard specifications. As a result of the analysis, it is determined that the IP spoofing attack is not feasible in the 5G system implemented according to the 3GPP Rel-17 standard specifications.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.51-59
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• 2015

JavaScript is a popular technique for activating static HTML. JavaScript has drawn more attention following the introduction of HTML5 Standard. In proportion to JavaScript's growing importance, attacks (ex. DDos, Information leak using its function) become more dangerous. Since these attacks do not create a trail, whether the JavaScript code is malicious or not must be decided. The real attack action is completed while the browser runs the JavaScript code. For these reasons, there is a need for a real-time classification and determination technique for malicious JavaScript. This paper proposes the Analysis Engine for detecting malicious JavaScript by adopting the requirements above. The analysis engine performs static analysis using signature-based detection and dynamic analysis using behavior-based detection. Static analysis can detect malicious JavaScript code, whereas dynamic analysis can detect the action of the JavaScript code.

• Journal of KIISE
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• v.41 no.9
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• pp.617-624
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• 2014

Malicious traffic, such as DDoS attack and botnet communications, refers to traffic that is generated for the purpose of disturbing internet networks or harming certain networks, servers, or hosts. As malicious traffic has been constantly evolving in terms of both quality and quantity, there have been many researches fighting against it. In this paper, we propose an effective malicious traffic detection method that exploits the X-means clustering algorithm. We also suggest how to analyze statistical characteristics of malicious traffic and to define metrics that are used when clustering. Finally, we verify effectiveness of our method by experiments with two released traffic data.

• Journal of Platform Technology
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• v.9 no.2
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• pp.26-37
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• 2021

E-mail is one of the important tools for communicating with people in everyday life. With COVID-19 (Coronavirus) increasing non-face-to-face activity, security incidents through e-mail such as spam, phishing, and ransomware are increasing. E-mail security incidents are increasing as social engineering attack using human psychology rather than arising from technological weaknesses that e-mails have. Security incidents using human psychology can be prevented and defended by improving security awareness. This study empirically studies the analysis of changes in response to malicious e-mail due to improved security awareness through malicious e-mail simulations on executives and employees of domestic and foreign company. In this study, the factors of security training, top-down security management, and security issue sharing are found to be effective in safely responding to malicious e-mail. This study presents a new study by conducting empirical analysis of theoretical research on security awareness in relation to malicious e-mail responses, and results obtained from simulations in a practical setting may help security work.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.405-414
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• 2010

According to the statistics of SecurityFocus in 2008, client-side attacks through the Microsoft Internet Explorer have increased by more than 50%. In this paper, we have implemented a behavior-based malicious web page detection system and a blacklist-based malicious web page filtering system. To do this, we first efficiently collected the target URLs by constructing a crawling system. The malicious URL detection system, run on a specific server, visits and renders actively the collected web pages under virtual machine environment. To detect whether each web page is malicious or not, the system state changes of the virtual machine are checked after rendering the page. If abnormal state changes are detected, we conclude the rendered web page is malicious, and insert it into the blacklist of malicious web pages. The malicious URL filtering system, run on the web client machine, filters malicious web pages based on the blacklist when a user visits web sites. We have enhanced system performance by automatically handling message boxes at the time of ULR analysis on the detection system. Experimental results show that the game sites contain up to three times more malicious pages than the other sites, and many attacks incur a file creation and a registry key modification.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.203-216
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• 2019

The nature of wireless transmission has made wireless sensor networks defenseless against various attacks. This paper presents warning message counter method (WMC) to detect blackhole attack, grayhole attack and sinkhole attack in wireless sensor networks. The objective of these attackers are, to draw the nearby network traffic by false routing information and disrupt the network operation through dropping all the received packets (blackhole attack), selectively dropping the received packets (grayhole and sinkhole attack) and modifying the content of the packet (sinkhole attack). We have also attempted light weighted symmetric key cryptography to find data modification by the sinkhole node. Simulation results shows that, WMC detects sinkhole attack, blackhole attack and grayhole attack with less false positive 8% and less false negative 6%.

• Convergence Security Journal
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• v.6 no.2
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• pp.21-29
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• 2006

Recently, illegal manipulation and forgery threats on computer softwares are increasing. Specially, forge the code of program and disrupt normal operation using a malicious loader program against the Internet application client. In this paper, we first analyze and generate signatures of malicious loader detection. And, we propose a method to secure the application client based on profiling which can detect and filter out abnormal malicious loader requests.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.538-547
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• 2016

Cloud computing is a new style of computing in which dynamically scalable and reconfigurable resources are provided as a service over the internet. The MapReduce framework is currently the most dominant programming model in cloud computing. It is necessary to protect the integrity of MapReduce data processing services. Malicious workers, who can be divided into collusive workers and non-collusive workers, try to generate bad results in order to attack the cloud computing. So, figuring out how to efficiently detect the malicious workers has been very important, as existing solutions are not effective enough in defeating malicious behavior. In this paper, we propose a security protection framework to detect the malicious workers and ensure computation integrity in the map phase of MapReduce. Our simulation results show that our proposed security protection framework can efficiently detect both collusive and non-collusive workers and guarantee high computation accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.89-96
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• 2014

MANET has been applied to a wide variety of areas because it has advantages which can build a network quickly in a difficult situation to build a network. However, it is become a victim of malicious nodes because of characteristics such as mobility of nodes consisting MANET, limited resources, and the wireless network. Therefore, it is required to lightweight attack detection technique which can accurately detect attack without causing a large burden to the mobile node. In this paper, we propose a multistage attack detection techniques that attack detection takes place in routing phase and data transfer phase in order to increase the accuracy of attack detection. The proposed attack detection technique is composed of four modules at each stage in order to perform accurate attack detection. Flooding attack and packet discard or modify attacks is detected in the routing phase, and whether the attack by modification of data is detected in the data transfer phase. We assume that nodes have a public key and a private key in pairs in this paper.