• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.5
• /
• pp.1059-1070
• /
• 2018

The block cipher Zorro is designed to reduce the implementation cost for side-channel countermeasure. It has a structure similar to AES, but the number of S-Boxes used is small. However, since the master key is used as the round key, it can be vulnerable to related key attacks. In this paper, we show key recovery attacks on Zorro using related-key differential characteristics. In addition, the related key differential characteristics are fatal when Zorro is used as the base block cipher of the hash function. In this paper, we describe how these characteristics can be linked to collision attacks in the PGV models.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.5
• /
• pp.1247-1258
• /
• 2018

The Cyber Kill Chain originally proposed by Lockheed Martin defines the standard procedure of general cyber attacks and suggests tailored defensive actions per each step, eventually neutralizing the intent of the attackers. Defenders can effectively deal with Advanced Persistent Threat(APT)s which are difficult to be handled by other defensive mechanisms under the Cyber Kill Chain. Recently, however, social engineering techniques that exploits the vulnerabilities of humans who manage the target systems are prevail rather than the technical attacks directly attacking the target systems themselves. Under the circumstance, the Cyber Kill Chain model should evolve to encompass social engineering attacks for the improved effectiveness. Therefore, this paper aims to establish a definite concept of Cyber Kill Chain for social engineering based cyber attacks, called Social Engineering Cyber Kill Chain, helping future researchers in this literature.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.5
• /
• pp.14-21
• /
• 2020

In order to provide confidential services between two communicating parties, block data encryption using a symmetric secret key is applied. A power analysis attack on a cryptosystem is a side channel-analysis method that can extract a secret key by measuring the power consumption traces of the crypto device. In this paper, we propose an attack model that can recover the secret key using a power analysis attack based on a deep learning convolutional neural network (CNN) algorithm. Considering that the CNN algorithm is suitable for image analysis, we particularly adopt the recurrence plot (RP) signal processing method, which transforms the one-dimensional power trace into two-dimensional data. As a result of executing the proposed CNN attack model on an XMEGA128 experimental board that implemented the AES-128 encryption algorithm, we recovered the secret key with 22.23% accuracy using raw power consumption traces, and obtained 97.93% accuracy using power traces on which we applied the RP processing method.

• Convergence Security Journal
• /
• v.19 no.5
• /
• pp.47-53
• /
• 2019

Network-based sharing of information has evolved into a cloud service environment today, increasing its number of users rapidly, but has become a major target for network-based illegal attackers.. In addition, IP spoofing among attackers' various attack techniques generally involves resource exhaustion attacks. Therefore, fast detection and response techniques are required. The existing detection method for IP spoofing attack performs the final authentication process according to the analysis and matching of traceback information of the client who attempted the connection request. However, the simple comparison method of traceback information may require excessive OTP due to frequent false positives in an environment requiring service transparency. In this paper, symmetric key cryptography based on traceback information is used as mutual authentication information to improve this problem. That is, after generating a traceback-based encryption key, mutual authentication is possible by performing a normal decryption process. In addition, this process could improve the overhead caused by false positives.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.4C
• /
• pp.451-457
• /
• 2006

A peer-to-peer(P2P) network is inherently vulnerable to malicious attacks from participating peers because of its open, flat, and autonomous nature. This paper addresses the problem of effectively defending from active attacks of malicious peers at bootstrapping phase and at online phase, respectively. We propose a secure membership handling protocol to protect the assignment of ID related things to a newly joining peer with the aid of a trusted entity in the network. The trusted entities are only consulted when new peers are joining and are otherwise uninvolved in the actions of the P2P networks. For the attacks in online phase, we present a novel message structure applied to each message transmitted on the P2P overlay. It facilitates the detection of message alteration, replay attack and a message with wrong information. Taken together, the proposed techniques deter malicious peers from cheating and encourage good peers to obey the protocol of the network. The techniques assume a basic P2P overlay network model, which is generic enough to encompass a large class of well-known P2P networks, either unstructured or not.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.3
• /
• pp.27-35
• /
• 2011

Design of Sensor nodes in Wireless Sensor Network(WSN) should be considered some properties as electricity consumption, transmission speed, range, etc., and also be needed the protection against various attacks (e.g., eavesdropping, hacking, leakage of customer's secret data, and denial of services). The stream cipher Rabbit, selected for the final eSTREAM portfolio organized by EU ECRYPT and selected as algorithm in part of ISO/IEC 18033-4 Stream Ciphers on ISO Security Standardization recently, is a high speed stream cipher suitable for WSN. Since the stream cipher Rabbit was evaluated the complexity of side-channel analysis attack as 'Medium' in a theoretical approach, thus the method of power analysis attack to the stream cipher Rabbit and the verification of our method by practical experiments were described in this paper. We implemented the stream cipher Rabbit without countermeasures of power analysis attack on IEEE 802.15.4/ZigBee board with 8-bit RISC AVR microprocessor ATmega128L chip, and performed the experiments of power analysis based on difference of means and template using a Hamming weight model.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.57-64
• /
• 2022

In this paper, the definition and overview of digital health care that has emerged recently, core technology, and We would like to propose a plan to establish a next-generation information protection system that can protect digital healthcare devices and data from cyber attacks. Various vulnerabilities exist for digital healthcare devices and data, and cyber attacks are possible for those vulnerabilities. Through an attack on digital health care devices and information and communication networks, it can directly adversely affect human life and health, Since digital healthcare data contains sensitive and personal information, it is essential to safely protect it from cyber attacks. In the case of this proposal, for continuous safe management of data and cyber attacks on equipment and communication networks for digital health devices, It is expected to be able to respond more effectively and continuously through the establishment of the next-generation information protection system.

• Journal of KIISE:Information Networking
• /
• v.32 no.3
• /
• pp.279-290
• /
• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.6
• /
• pp.75-85
• /
• 2010

This paper presents a robust 3D model hashing based on object feature vector for 3D content authentication. The proposed 3D model hashing selects the feature objects with highest area in a 3D model with various objects and groups the distances of the normalized vertices in the feature objects. Then we permute groups in each objects by using a permutation key and generate the final binary hash through the binary process with the group coefficients and a random key. Therefore, the hash robustness can be improved by the group coefficient from the distance distribution of vertices in each object group and th hash uniqueness can be improved by the binary process with a permutation key and a random key. From experimental results, we verified that the proposed hashing has both the robustness against various mesh and geometric editing and the uniqueness.

• Journal of KIISE:Computing Practices and Letters
• /
• v.12 no.6
• /
• pp.339-348
• /
• 2006

Recently, many researches on detecting and responding worms due to the fatal infrastructural damages explosively damaged by automated attack tools, particularly worms. Network service vulnerability exploiting worms have high propagation velocity, exhaust network bandwidth and even disrupt the Internet. Previous worm researches focused on signature-based approaches however these days, approaches based on behavioral features of worms are more highlighted because of their low false positive rate and the attainability of early detection. In this paper, we propose a Distributed Worm Detection Model based on packet marking. The proposed model detects Worm Cycle and Infection Chain among which the behavior features of worms. Moreover, it supports high scalability and feasibility because of its distributed reacting mechanism and low processing overhead. We virtually implement worm propagation environment and evaluate the effectiveness of detecting and responding worm propagation.