• Journal of the Korea Society for Simulation
• /
• v.17 no.3
• /
• pp.95-105
• /
• 2008

In this paper, we propose the DAMMC(Distributed Authentication Model using Multi-level Cluster) for wireless sensor networks. The proposed model is that one cluster header in m-layer has a role of CA(Certificate Authority) but it just authenticates sensor nodes in lower layer for providing an efficient authentication without authenticating overhead among clusters. In here, the m-layer for authentication can be properly predefined by user in consideration of various network environments. And also, the DAMMC uses certificates based on the threshold cryptography scheme for more reliable configuration of WSN. Experimental results show that the cost of generation and reconfiguration certification are decreased but the security performance are increased compared to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.7
• /
• pp.1493-1500
• /
• 2004

Today's Commercial security server system which provide secrecy, integrity and availability may still be vulnerable to denial-of-service attacks. Authentication system whith use a public key cryptography and process RSA encryption is relatively slow and the slowness has become a major security threat specifically in service flooding attacks caused by authentication requests. The service flooding attacks render the server incapable of providing its service to legitimitive clients. Therefore the importance of implementing systems that prevent denial of service attacks and provide service to legitimitive users cannot be overemphasized. In this paper, we propose a puzzle protocol which applies to authentication model. our gradually strengthening authentication model improves the availability and continuity of services and prevent denial of service attacks and we implement flooding of service tolerance system to verify the efficiency of our model. This system is expected to be ensure in the promotion of reliability.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.6
• /
• pp.1045-1053
• /
• 2014

In this paper, we assume that the information leakage through side-channel signal may occur from the card payment terminal and newly introduce a real application attack model. The attack model is a side channel attack based on vibration signals, which are detected by a small sensor attached on card terminal by attacker. This study is similar to some other studies regarding side channel attack. However, this paper is different in that it is based on the non-language model. Because the financial transaction information such as a card number, password, mobile phone number and etc cannot have a constant pattern. In addition, there was no study about card terminal. Therefore, this new study is meaningful. We collected vibration signals on card terminal with a small wireless sensor and analyzed signal data with statistical signal processing techniques using spectrum of frequency domain and principal component analysis and pattern recognition algorithms. Finally, we evaluated the performances by using real data from the sensor.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.5
• /
• pp.981-991
• /
• 2024

Adversarial attacks, which induce malfunctions in AI technologies, can be applied to various domains and models, easily compromising SOTA (State-of-the-Art) models. Although adversarial defense techniques have been developed to counter these attacks, their applicability is limited due to constraints. Consequently, not only is the adoption of AI technology delayed, but also advanced research is restricted. To address this issue, this paper introduces a novel concept of adversarial data by reversing the sign of the loss function update in adversarial attacks. Experiments were conducted by applying the reverse-update adversarial data to data poisoning and adversarial training environments, showing that it can reduce the model's performance up to 72% and is most effective in enhancing robustness in 6 out of 9 environments. Ultimately, the proposed data can stimulate extensive research on adversarial attacks and defenses, further promoting the advancement of defense technology and contributing to the safe adoption of AI.

• Journal of Internet Computing and Services
• /
• v.20 no.1
• /
• pp.1-10
• /
• 2019

Since big-data text mining extracts many features and data, clustering and classification can result in high computational complexity and low reliability of the analysis results. In particular, a term document matrix obtained through text mining represents term-document features, but produces a sparse matrix. We designed an advanced genetic algorithm (GA) to extract features in text mining for detection model. Term frequency inverse document frequency (TF-IDF) is used to reflect the document-term relationships in feature extraction. Through a repetitive process, a predetermined number of features are selected. And, we used the sparsity score to improve the performance of detection model. If a spam mail data set has the high sparsity, detection model have low performance and is difficult to search the optimization detection model. In addition, we find a low sparsity model that have also high TF-IDF score by using s(F) where the numerator in fitness function. We also verified its performance by applying the proposed algorithm to text classification. As a result, we have found that our algorithm shows higher performance (speed and accuracy) in attack mail classification.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.3
• /
• pp.135-142
• /
• 2017

DDoS (Distributed Denial of Service) exhausts the target server's resources using the large number of zombie pc, As a result normal users don't access to server. DDoS Attacks steadly increase by many attacker, and almost target of the attack is critical system such as IT Service Provider, Government Agency, Financial Institution. In this paper, We will introduce the CNN (Convolutional Neural Network) of deep learning based real-time detection system for DNS amplification Attack (DNS DDoS Attack). We use the dataset which is mixed with collected data in the real environment in order to overcome existing research limits that use only the data collected in the experiment environment. Also, we build a deep learning model based on Convolutional Neural Network (CNN) that is used in pattern recognition.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.411-422
• /
• 2021

The autonomous driving system mounted on the unmanned vehicle recognizes the external environment through several sensors and derives the optimum control value through it. Recently, studies on physical level attacks that maliciously manipulate sensor data by performing signal-injection attacks have been published. signal-injection attacks are performed at the physical level and are difficult to detect at the software level because the sensor measures erroneous data by applying physical manipulations to the surrounding environment. In order to detect a signal-injection attack, it is necessary to verify the dependability of the data measured by the sensor. As so far, various methods have been proposed to attempt physical level attacks against sensors mounted on autonomous driving systems. However, it is still insufficient that methods for defending and detecting the physical level attacks. In this paper, we demonstrate signal-injection attacks targeting MEMS sensors that are widely used in unmanned vehicles, and propose a method to detect the attack. We present a signal-injection detection model to analyze the accuracy of the proposed method, and verify its effectiveness in a laboratory environment.

• Journal of KIISE:Software and Applications
• /
• v.31 no.9
• /
• pp.1218-1225
• /
• 2004

S/KEY system was proposed to guard against intruder's password replay attack. But S/KEY system has vulnerability that if an attacker derive passphrase from his dictionary file, he can acquire one-time password required for user authentication. In this paper, we propose a correct S/KEY system mixed with EKE to solve the problem. Also, we specify a new S/KEY system with Casper and CSP, verify its secrecy and authentication requirements using FDR model checking tool.

• Convergence Security Journal
• /
• v.19 no.4
• /
• pp.77-85
• /
• 2019

As the Internet continues to evolve, cyber attacks are becoming more precise and covert. Anonymous communication, which is used to protect personal privacy, is also being used for cyber attacks. Not only it hides the attacker's IP address but also encrypts traffic, which allows users to bypass the information protection system that most organizations and institutions are using to defend cyber attacks. For this reason, anonymous communication can be used as a means of attacking malicious code or for downloading additional malware. Therefore, this study aims to suggest a method to detect and block encrypted anonymous communication as quickly as possible through artificial intelligence. Furthermore, it will be applied to the defense to detect malicious communication and contribute to preventing the leakage of important data and cyber attacks.

• Convergence Security Journal
• /
• v.6 no.4
• /
• pp.171-177
• /
• 2006

The hacking aspect of recent times is changing, the phishing attack which uses a social engineering technique is becoming the threat which is serious in Information Security. It cheats the user and it acquires a password or financial information of the individual and organization. The phishing attack uses the home page which is fabrication and E-mail and acquires personal information which is sensitive and financial information. This study proposes the establishment of National Fishing Response Center, complement of relation legal system Critical intelligence distribution channel of individual and enterprise.