• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.53-62
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• 2023

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4552-4567
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• 2014

A (n,t,n) secret sharing scheme is to share a secret among n group members, where each member also plays a role of a dealer,and any t shares can be used to recover the secret. In this paper, we propose a strong (k,t,n) verifiable multi-secret sharing scheme, where any k out of n participants operate as dealers. The scheme realizes both threshold structure and adversary structure simultaneously, and removes a trusted third party. The secret reconstruction phase is performed using an additive homomorphism for decreasing the storage cost. Meanwhile, the scheme achieves the pre-verification property in the sense that any participant doesn't need to reveal any information about real master shares in the verification phase. We compare our proposal with the previous (n,t,n) secret sharing schemes from the perspectives of what kinds of access structures they achieve, what kinds of functionalities they support and whether heavy storage cost for secret share is required. Then it shows that our scheme takes the following advantages: (a) realizing the adversary structure, (b) allowing any k out of n participants to operate as dealers, (c) small sized secret share. Moreover, our proposed scheme is a favorable candidate to be used in many applications, such as secure multi-party computation and privacy preserving data mining, etc.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.115-123
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• 2019

White-box cryptography is an implementation technique in order to protect secret keys of cryptographic algorithms in the white-box attack model, which is the setting that an adversary has full access to the implementation of the cryptographic algorithm and full control over their execution. This concept was introduced in 2002 by Chow et al., and since then, there have been many proposals for secure implementations. While there have been many approaches to construct a secure white-box implementation for the ciphers with SPN structures, there was no notable result about the white-box implementation for the block ciphers with Feistel structure after white-box DES implementation was broken. In this paper, we propose a secure white-box implementation for a block cipher SEED with Feistel structure, which can prevent the previous known attacks for white-box implementations. Our proposal is simple and practical: it is performed by only 3,376 table lookups during each execution and the total size of tables is 762.5 KB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2629-2650
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• 2019

It is important to construct fully homomorphic encryption with ciphertext matrix that makes fully homomorphic encryption become very nature and simple. We present a general design method of constructing fully homomorphic encryption whose ciphertext is matrix. By using this design method, we can deduce a fully homomorphic encryption scheme step by step based on a basic encryption scheme. The process of deduction is similar to solving equation and the final output result is a fully homomorphic encryption scheme with ciphertext matrix. The idea of constructing ciphertext matrix is ciphertexts stack, which don't simply stack ciphertexts together but is to obtain the desired homomorphic property. We use decryption structure as tool to analyze homomorphic property and noise growth during homomorphic evaluation. By using this design method, we obtain three corresponding fully homomorphic encryption schemes. Our obtained fully homomorphic encryption schemes are more efficient. Finally, we introduce the adversary advantage and improve the previous method of estimating concert parameters of fully homomorphic encryption. We give the concert parameters of these schemes.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.517-520
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• 2013

In construction operation, the temporary structure is used to support designed facilities or to provide work spaces for construction activities. Since the structure is used only during the construction operation, the operation may be given insufficient attention. The contractor is likely to try to save cost on the material and labor cost. This contractor's behavior frequently leads to construction accidents. In order to prevent accidents from the failure, the operation should be carefully monitored for identifying the effect of dynamics in the surrounding site area. Otherwise, any unexpected adversary effect could result in a very costly construction failure. This study presents the feasibility of the ubiquitous sensor network (USN) technology in collecting construction data during the construction operation of earth retaining walls. The study is based on the result at the Construction System Integration Laboratory (CSIL) at the Pusan National University. A USN-based system has been developed for monitoring the behavior of the temporary structure of earth retaining walls. The data collected from the sensors were used to understand the behavior of the temporary structure. The result of this study will be used in increasing the safety during the construction operation of retaining walls.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1661-1668
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• 2020

A physical protection system (PPS) is used for the protection of critical facilities. This paper proposes a structure analytic hierarchy approach (SAHA) for the hierarchical evaluation of the PPS effectiveness in critical infrastructure. SAHA is based on the traditional analysis methods "estimate of adversary sequence interruption, EASI". A community algorithm is used in the building of the SAHA model. SAHA is applied to cluster the associated protection elements for the topological design of complicated PPS with graphical vertexes equivalent to protection elements.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.197-209
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• 2011

The increasing popularity of graph data, such as social and online communities, has initiated a prolific research area in knowledge discovery and data mining. As more real-world graphs are released publicly, there is growing concern about privacy breaching for the entities involved. An adversary may reveal identities of individuals in a published graph, with the topological structure and/or basic graph properties as background knowledge. Many previous studies addressing such attacks as identity disclosure, however, concentrate on preserving privacy in simple graph data only. In this paper, we consider the identity disclosure problem in weighted graphs. The motivation is that, a weighted graph can introduce much more unique information than its simple version, which makes the disclosure easier. We first formalize a general anonymization model to deal with weight-based attacks. Then two concrete attacks are discussed based on weight properties of a graph, including the sum and the set of adjacent weights for each vertex. We also propose a complete solution for the weight anonymization problem to prevent a graph from both attacks. In addition, we also investigate the impact of the proposed methods on community detection, a very popular application in the graph mining field. Our approaches are efficient and practical, and have been validated by extensive experiments on both synthetic and real-world datasets.

• ETRI Journal
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• v.37 no.6
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• pp.1108-1119
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• 2015

Multicast communication of mobile ad hoc networks is vulnerable to internal attacks due to its routing structure and high scalability of its participants. Though existing intrusion detection systems (IDSs) act smartly to defend against attack strategies, adversaries also accordingly update their attacking plans intelligently so as to intervene in successful defending schemes. In our work, we present a novel indirect internal stealthy attack on a tree-based multicast routing protocol. Such an indirect stealthy attack intelligently makes neighbor nodes drop their routing-layer unicast control packets instead of processing or forwarding them. The adversary targets the collision avoidance mechanism of the Medium Access Control (MAC) protocol to indirectly affect the routing layer process. Simulation results show the success of this attacking strategy over the existing "stealthy attack in wireless ad hoc networks: detection and countermeasure (SADEC)" detection system. We design a cross-layer automata-based stealthy attack on multicast routing protocols (SAMRP) attacker detection system to identify and isolate the proposed attacker. NS-2 simulation and analytical results show the efficient performance, against an indirect internal stealthy attack, of SAMRP over the existing SADEC and BLM attacker detection systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.621-631
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• 2023

Adversarial training improves the robustness of deep neural networks for adversarial examples. However, the previous adversarial training method focuses only on the adversarial loss function, ignoring that even a small perturbation of the input layer causes a significant change in the hidden layer features. Consequently, the accuracy of a defended model is reduced for various untrained situations such as clean samples or other attack techniques. Therefore, an architectural perspective is necessary to improve feature representation power to solve this problem. In this paper, we apply an attention module that generates an attention map of an input image to a general model and performs PGD adversarial training upon the augmented model. In our experiments on the CIFAR-10 dataset, the attention augmented model showed higher accuracy than the general model regardless of the network structure. In particular, the robust accuracy of our approach was consistently higher for various attacks such as PGD, FGSM, and BIM and more powerful adversaries. By visualizing the attention map, we further confirmed that the attention module extracts features of the correct class even for adversarial examples.