• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.25-32
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• 2019

In this paper, we propose a method to apply the attack surface expansion through decoy traps to a protected server network. The network consists of a large number of decoys and protected servers. In the network, each protected server dynamically mutates its IP address and port numbers based on Hidden Tunnel Networking that is a network-based moving target defense scheme. The moving target defense is a new approach to cyber security and continuously changes system's attack surface to prevent attacks. And, the attack surface expansion is an approach that uses decoys and decoy groups to protect attacks. The proposed method modifies the NAT table of the protected server with a custom chain and a RETURN target in order to make attackers waste all their time and effort in the decoy traps. We theoretically analyze the attacker success rate for the protected server network before and after applying the proposed method. The proposed method is expected to significantly reduce the probability that a protected server will be identified and compromised by attackers.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.101-108
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• 2021

In this paper, we analyze Shin's proposed dynamic ID-based user authentication scheme for TMIS(Telecare Medicine Information System), and Shin's authentication scheme is vulnerable to smart card loss attacks, allowing attackers to acquire user IDs, which enables user impersonation attack. In 2019, Shin's proposed authentication scheme attempted to generate a strong random number using ECC, claiming that it is safe to lose a smart card because it is impossible to calculate random number r'i due to the difficulty of the ECC algorithm without knowing random number ri. However, after analyzing Shin's authentication scheme in this paper, the use of transmission messages and smart cards makes it easy to calculate random numbers r'i, which also enables attackers to generate session keys. In addition, Shin's authentication scheme were analyzed to have significantly greater overhead than other authentication scheme, including vulnerabilities to safety analysis, the lack of a way to pass the server's ID to users, and the lack of biometric characteristics with slightly different templates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1481-1488
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• 2018

As female gamers are rapidly increasing, the misogyny and the misandry in game playing situation are also increasing. Recent #Gamergate and GodGunbae incident exhibit that such discriminative/hate behaviour in game playing can be developed into real physical threat or crime. In this paper, we investigate and analyze young Korean game players on how the attackers group, victims group, and gender-issue-indifferent group behave differently in game playing through survey. We found that male gamers had high hostile sexism against female gamers especially on females' game attitude and streotyped hatred with respect to the gender ${\times}$ group interaction. In big-5 personality test, however, it is not clear if attackers and victims had a noticeable different personality patterns. In result, we verify that there exist gender stereotype and high hostile sexism among young Korean gamers. Active gender-equality education on their adolescent period is necessary to avoid such destructive hatred in game playing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.691-705
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• 2012

Buffer overflow vulnerability is the most representative one that an attack method and its countermeasure is frequently developed and changed. This vulnerability is still one of the most critical threat since it was firstly introduced in middle of 1990s. Shellcode is a machine code which can be used in buffer overflow attack. Attackers make the shellcode for their own purposes and insert it into target host's memory space, then manipulate EIP(Extended Instruction Pointer) to intercept control flow of the target host system. Therefore, a lot of research to defend have been studied, and attackers also have done many research to bypass security measures designed for the shellcode defense. In this paper, we investigate shellcode defense and attack techniques briefly and we propose our new methodology which can hide shellcode in the 24bit BMP image. With this proposed technique, we can easily hide any shellcode executable and we can bypass the current detection and prevention techniques.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.667-677
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• 2012

Vulnerable web applications have been the primary method used by the attackers to spread their malware to a large number of victims. Such attacks commonly make use of malicious links to remotely execute a rather advanced malicious code. The attackers often deploy malwares that utilizes unknown vulnerabilities so-called "zero-day vulnerabilities." The existing computer vaccines are mostly signature-based and thus are effective only against known attack patterns, but not capable of detecting zero-days attacks. To mitigate such limitations of the current solutions, there have been a numerous works that takes a behavior-based approach to improve detection against unknown malwares. However, behavior-based solutions arbitrarily introduced a several limitations that made them unsuitable for real-life situations. This paper proposes an advanced web browser based malicious behavior detection system that solves the problems and limitations of the previous approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2074-2093
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• 2022

RSA is known as one of the best techniques for securing secret information across an unsecured network. The private key which is one of private parameters is the aim for attackers. However, it is exceedingly impossible to derive this value without disclosing all unknown parameters. In fact, many methods to recover the private key were proposed, the performance of each algorithm is acceptable for the different cases. For example, Wiener's attack is extremely efficient when the private key is very small. On the other hand, Fermat's factoring can quickly break RSA when the difference between two large prime factors of the modulus is relatively small. In general, if all private parameters are not disclosed, attackers will be able to confirm that the private key is unquestionably inside the scope [3, n - 2], where n is the modulus. However, this scope has already been reduced by increasing the greatest lower bound to [d_il, n - 2], where d_il ≥ 3. The aim of this paper is to decrease the least upper bound to narrow the scope that the private key will remain within this boundary. After finishing the proposed method, the new scope of the private key can be allocated as [d_il, d_ir], where d_ir ≤ n - 2. In fact, if the private key is extremely close to the new greatest lower bound, it can be retrieved quickly by performing a brute force attack, in which d_ir is decreased until it is equal to the private key. The experimental results indicate that the proposed method is extremely effective when the difference between prime factors is close to each other and one of two following requirement holds: the first condition is that the multiplier of Euler totient function is very close to the public key's small value whereas the second condition is that the public key should be large whenever the multiplier is far enough.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.817-826
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• 2022

AI technology is being successfully introduced in many fields, and models deployed as a service are deployed with black box environment that does not expose the model's information to protect intellectual property rights and data. In a black box environment, attackers try to steal data or parameters used during training by using model output. This paper proposes a method of inferring the type of model to directly find out the composition of layer of the target model, based on the fact that there is no attack to infer the information about the type of model from the deep learning model. With ResNet, VGGNet, AlexNet, and simple convolutional neural network models trained with MNIST datasets, we show that the types of models can be inferred using the output values in the gray box and black box environments of the each model. In addition, we inferred the type of model with approximately 83% accuracy in the black box environment if we train the big and small relationship feature that proposed in this paper together, the results show that the model type can be infrerred even in situations where only partial information is given to attackers, not raw probability vectors.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• Convergence Security Journal
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• v.23 no.1
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• pp.19-25
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• 2023

The current network environment provides a real-time interactive service from an initial one-way information prov ision service. Depending on the form of web-based information sharing, it is possible to provide various knowledge a nd services between users. However, in this web-based real-time information sharing environment, cases of damage by illegal attackers who exploit network vulnerabilities are increasing rapidly. In particular, for attackers who attempt a phishing attack, a link to the corresponding web page is induced after actively generating a forged web page to a user who needs a specific web page service. In this paper, we analyze whether users directly and actively forge a sp ecific site rather than a passive server-based detection method. For this purpose, it is possible to prevent leakage of important personal information of general users by detecting a disguised webpage of an attacker who induces illegal webpage access using traceback information

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.295-297
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• 2008

Session Initiation Protocol (SIP) has become the call control protocol of choice for Voice over IP (VoIP) networks because of its open and extensible nature. However, the integrity of call signaling between sites is of utmost importance, and SIP is vulnerable to attackers when left unprotected. Currently a hop-by-hop security model is prevalent, wherein intermediaries forward a request towards the destination user agent server (UAS) without a user agent client (UAC) knowing whether or not the intermediary behaved in a trusted manner. This paper presents an integrated security model for SIP-based VoIP network by combining hop-by-hop security and end-to-end security.