• ETRI Journal
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• v.42 no.6
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• pp.965-975
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• 2020

This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the existing taxonomies governing the development and deployment of honeypots are inadequate for evolving malicious programs and their variants. Malware-propagation and compromise methods are highly automated and repetitious. These automated and repetitive characteristics can be exploited by using embedded reinforcement learning within a honeypot. A honeypot for automated and repetitive malware (HARM) can be adaptive so that the best responses may be learnt during its interaction with attack sequences. HARM deployments can be agile through periodic policy evaluation to optimize redeployment. The necessary enhancements for adaptive, agile honeypots require a new development and deployment framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1659-1673
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• 2019

Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.

• Convergence Security Journal
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• v.21 no.1
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• pp.93-100
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• 2021

Damage caused by intelligent cyber attacks not only disrupts system operations and leaks information, but also entails massive economic damage. Recently, cyber attacks have a distinct goal and use advanced attack tools and techniques to accurately infiltrate the target. In order to minimize the damage caused by such an intelligent cyber attack, it is necessary to block the cyber attack at the beginning or during the attack to prevent it from invading the target's core system. Recently, technologies for predicting cyber attack paths and analyzing risk level of cyber attack using big data or artificial intelligence technologies are being studied. In this paper, a cyber attack path analysis method using attack tree and RFI is proposed as a basic algorithm for the development of an automated cyber attack path prediction system. The attack path is visualized using the attack tree, and the priority of the path that can move to the next step is determined using the RFI technique in each attack step. Based on the proposed mechanism, it can contribute to the development of an automated cyber attack path prediction system using big data and deep learning technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.531-539
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• 2017

CAPTCHA is a verification scheme whether or not a human user has made a service request. Most CAPTCHAs that are based on text, image, or simple game suffer from vulnerability that can be compromised by automated attacks and stream relay attacks. To resist such attacks, CAPTCHA that utilizes human recognition as been suggested but it show poor usability for deploying in the Internet. We propose an Emerging Image Cue CAPTCHA that offers improved usability and resists stream relay attacks, as well. We also examine the usability of the proposed CAPTCHA and investigate the attack resistance by conducting user study and experiments on simulated network environment.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3011-3019
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• 1999

Denial of service is about knocking off services, without permission for example through crashing the whole system. This kind of attacks are easy to launch and it is hard to protect a system against them. The basic problem is that Unix assumes that users on the system or on other systems will be well behaved. This paper analyses system-based inside denial of services attack(DoS) and system metric for performance of each machine provided. And formalize the conclusions results in ways that clearly expose the performance impact of those observations. So, we present new approach. It is detecting DoS attack using performance signature for system and program behavior. We present new approach. It is detecting DoS attack using performance signature for system and program behavior. We believe that metric will be to guide to automated development of a program to detect the attack. As a results, we propose the AIDPS(Architecture for Intrusion Detection using Performance Signature) model to detect DoS attack using performance signature.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.79-92
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• 2020

As the number of systems increases and the network size increases, automated attack prediction systems are urgently needed to respond to cyber attacks. In this study, we developed four types of information gathering sensors for collecting asset and vulnerability information, and developed technology to automatically generate attack graphs and predict attack targets. To improve performance, the attack graph generation method is divided into the reachability calculation process and the vulnerability assignment process. It always keeps up to date by starting calculations whenever asset and vulnerability information changes. In order to improve the accuracy of the attack target prediction, the degree of asset risk and the degree of asset reference are reflected. We refer to CVSS(Common Vulnerability Scoring System) for asset risk, and Google's PageRank algorithm for asset reference. The results of attack target prediction is displayed on the web screen and CyCOP(Cyber Common Operation Picture) to help both analysts and decision makers.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.249-257
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• 2005

In this paper proposed automated attack reaction tool based on IPv6. Currently, much researches are performing focused on application program and standardization for IPv6. But, It is not enough for future IPv6 security. The proposed method detect attacks on IPv6 and conventional IPv4, therefore it is possible to protect personal information using automated reaction method. Usually, IDS just perform detection, therefore damages may be repeated. However, this paper considered the problems described above, and suggested solution for this problems. The proposed algorithm suggested in this paper is simulated on IPv6 network based on Linux. As a simulation result, it is proved that proposed algorithm can detect attacks efficiently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1079-1090
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• 2012

As the number of information asset and their vulnerabilities are increasing, it becomes more difficult for network security administrators to assess security vulnerability of their system and network. There are several researches for vulnerability analysis based on quantitative approach. However, most of them are based on experts' subjective evaluation or they require a lot of manual input for deriving quantitative assessment results. In this paper, we propose HRMS(Hacking and Response Measurement System) for enumerating attack path using automated vulnerability measurement automatically. HRMS can estimate exploitability of systems or applications based on their known vulnerability assessment metric, and enumerate attack path even though system, network and application's information are not fully given for vulnerability assessment. With this proposed method, system administrators can do proactive security vulnerability assessment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1913-1920
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• 2017

Software Defined Networking creates totally new concept of networking and its applications which is based on separating the application and control layer from the networking infrastructure as a result it yields new opportunities in improving the network security and making it more automated in robust way, one of these applications is Denial of Service attack mitigation but due to the dynamic nature of Denial of Service attack it would require dynamic response which can mitigate the attack with the minimum false positive. In this paper we will propose a new mitigation Framework for DDoS attacks using Software Defined Networking technology to protect online services e.g. websites, DNS and email services against DoS and DDoS attacks.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.199-202
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• 2023

Carriage return (CR) and line feed (LF), also known as CRLF injection is a type of vulnerability that allows a hacker to enter special characters into a web application, altering its operation or confusing the administrator. Log poisoning and HTTP response splitting are two prominent harmful uses of this technique. Additionally, CRLF injection can be used by an attacker to exploit other vulnerabilities, such as cross-site scripting (XSS). Email injection, also known as email header injection, is another way that can be used to modify the behavior of emails. The Open Web Application Security Project (OWASP) is an organization that studies vulnerabilities and ranks them based on their level of risk. According to OWASP, CRLF vulnerabilities are among the top 10 vulnerabilities and are a type of injection attack. Automated testing can help to quickly identify CRLF vulnerabilities, and is particularly useful for companies to test their applications before releasing them. However, CRLF vulnerabilities can also lead to the discovery of other high-risk vulnerabilities, and it fosters a better approach to mitigate CRLF vulnerabilities in the early stage and help secure applications against known vulnerabilities. Although there has been a significant amount of research on other types of injection attacks, such as Structure Query Language Injection (SQL Injection). There has been less research on CRLF vulnerabilities and how to detect them with automated testing. There is room for further research to be done on this subject matter in order to develop creative solutions to problems. It will also help to reduce false positive alerts by checking the header response of each request. Security automation is an important issue for companies trying to protect themselves against security threats. Automated alerts from security systems can provide a quicker and more accurate understanding of potential vulnerabilities and can help to reduce false positive alerts. Despite the extensive research on various types of vulnerabilities in web applications, CRLF vulnerabilities have only recently been included in the research. Utilizing automated testing as a recurring task can assist companies in receiving consistent updates about their systems and enhance their security.