• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3076-3092
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• 2020

An IKPCA-ELM-based intrusion detection method is developed to address the problem of the low accuracy and slow speed of intrusion detection caused by redundancies and high dimensions of data in the network. First, in order to reduce the effects of uneven sample distribution and sample attribute differences on the extraction of KPCA features, the sample attribute mean and mean square error are introduced into the Gaussian radial basis function and polynomial kernel function respectively, and the two improved kernel functions are combined to construct a hybrid kernel function. Second, an improved particle swarm optimization (IPSO) algorithm is proposed to determine the optimal hybrid kernel function for improved kernel principal component analysis (IKPCA). Finally, IKPCA is conducted to complete feature extraction, and an extreme learning machine (ELM) is applied to classify common attack type detection. The experimental results demonstrate the effectiveness of the constructed hybrid kernel function. Compared with other intrusion detection methods, IKPCA-ELM not only ensures high accuracy rates, but also reduces the detection time and false alarm rate, especially reducing the false alarm rate of small sample attacks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2171-2180
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• 2011

Security is a significant concern for many sensor network applications. Intrusion detection is one method of defending against attacks. However, standard intrusion detection techniques are not suitable for sensor networks with limited resources. In this paper, propose a new method for selecting and managing the detect nodes in IDS(intrusion detection system) for anomaly detection in sensor networks and the node scheduling technique for maximizing the IDS's lifetime. Using the genetic algorithm, developed the solutions for suggested optimization equation and verify the effectiveness of proposed methods by simulations.

• 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 Korea Society of Digital Industry and Information Management
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• v.16 no.3
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• pp.37-47
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• 2020

The In the 4^th industrial revolution, cyber space will evolve into hyper-connectivity, super-convergence, and super-intelligence due to the development of advanced information and communication technologies, which will connect the nation's core infrastructure into a single network. As applying the 4^th industrial revolution technology to the cyber attack technique, it is evolving in an intelligent and sophisticate method. In order to response intelligent cyber attacks, it is difficult to guarantee self-defense in cyberspace by policy-oriented, preplanned-centric and hierarchical cyber response strategies. Therefore, this research aims to propose a situation-flexible & action-oriented cyber response mechanism that can respond flexibly by selecting the most optimal smart security solution according to changes in the cyber attack steps. The proposed cyber response mechanism operates the smart security solutions according to the action-oriented detailed strategies. In addition, artificial intelligence-based decision-making systems are used to select the smart security technology with the best responsiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6121-6144
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• 2019

Numerous privacy-preserving authentication schemes have been proposed but vehicular ad hoc networks (VANETs) still suffer from security and privacy issues as well as computation and communication overheads. In this paper, we proposed a robust conditional privacy-preserving authentication scheme based on pseudonym root with cuckoo filter to meet security and privacy requirements and reduce computation and communication overheads. In our proposed scheme, we used a new idea to generate pseudonyms for vehicles where each on-board unit (OBU) saves one pseudonym, named as "pseudonym root," and generates all pseudonyms from the same pseudonym. Therefore, OBU does not need to enlarge its storage. In addition, the scheme does not use bilinear pairing operation that causes computation overhead and has no certification revocation list that leads to computation and communication overheads. The proposed scheme has lightweight mutual authentication among all parties and just for once. Moreover, it provides strong anonymity to preserve privacy and resists ordinary attacks. We analyzed our proposed scheme and showed that it meets security and privacy requirements of VANETs and is more efficient than traditional schemes. The communication and computation overheads were also discussed to show the cost-effectiveness of the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.914-934
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• 2016

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way. This paper improves the outstanding Certified Reputation (CR) model and proposes a Lightweight Cross-domain Trust (LCT) model for the mobile distributed environment in a fully distributed way. The trust certifications, in which the trust ratings contain various trust aspects with different interest preference weights, are collected and provided by the trustees. Furthermore, three factors are comprehensively considered to ease the issue of collusion attacks and make the trust certifications more accurate. Finally, a cross-domain scenario is deployed and implemented, and the comprehensive experiments and analysis are conducted. The results demonstrate that our LCT model obviously outperforms the Bayesian Network (BN) model and the CR model in our cross-domain scenario, and significantly improves the successful interaction rates of the honest entities without increasing the risks of interacting with the malicious entities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1801-1816
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• 2014

Because HTTP-related ports are allowed through firewalls, they are an obvious point for launching cyber attacks. In particular, malware uses HTTP protocols to communicate with their master servers. We call this an HTTP-based command and control (C&C) server. Most previous studies concentrated on the behavioral pattern of C&Cs. However, these approaches need a well-defined white list to reduce the false positive rate because there are many benign applications, such as automatic update checks and web refreshes, that have a periodic access pattern. In this paper, we focus on finding new discriminative features of HTTP-based C&Cs by analyzing HTTP activity sets. First, a C&C shows a few connections at a time (low density). Second, the content of a request or a response is changed frequently among consecutive C&Cs (high content variability). Based on these two features, we propose a novel C&C analysis mechanism that detects the HTTP-based C&C. The HAS-Analyzer can classify the HTTP-based C&C with an accuracy of more than 96% and a false positive rate of 1.3% without using any white list.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2660-2679
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• 2017

Crypton is a SP-network block cipher that attracts much attention because of its excellent performance on hardware. Based on Crypton, mCrypton is designed as a lightweight block cipher suitable for Internet of Things (IoT) and Radio Frequency Identification (RFID). The security of Crypton and mCrypton under meet-in-the-middle attack is analyzed in this paper. By analyzing the differential properties of cell permutation, several differential characteristics are introduced to construct generalized ${\delta}-sets$. With the usage of a generalized ${\delta}-set$ and differential enumeration technique, a 6-round meet-in-the-middle distinguisher is proposed to give the first meet-in-the-middle attack on 9-round Crypton-192 and some improvements on the cryptanalysis of 10-round Crypton-256 are given. Combined with the properties of nibble permutation and substitution, an improved meet-in-the-middle attack on 8-round mCrypton is proposed and the first complete attack on 9-round mCrypton-96 is proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4576-4598
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• 2018

In big data age, flexible and affordable cloud storage service greatly enhances productivity for enterprises and individuals, but spontaneously has their outsourced data susceptible to integrity breaches. Provable Data Possession (PDP) as a critical technology, could enable data owners to efficiently verify cloud data integrity, without downloading entire copy. To address challenging integrity problem on multiple clouds for multiple owners, an identity-based batch PDP scheme was presented in ProvSec 2016, which attempted to eliminate public key certificate management issue and reduce computation overheads in a secure and batch method. In this paper, we firstly demonstrate this scheme is insecure so that any clouds who have outsourced data deleted or modified, could efficiently pass integrity verification, simply by utilizing two arbitrary block-tag pairs of one data owner. Specifically, malicious clouds are able to fabricate integrity proofs by 1) universally forging valid tags and 2) recovering data owners' private keys. Secondly, to enhance the security, we propose an improved scheme to withstand these attacks, and prove its security with CDH assumption under random oracle model. Finally, based on simulations and overheads analysis, our batch scheme demonstrates better efficiency compared to an identity based multi-cloud PDP with single owner effort.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.154-155
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• 2013

This paper presents a user authentication scheme for healthcare application using wireless sensor networks, where wireless sensors are used for patients monitoring. These medical sensors' sense the patient body data and transmit it to the professionals. Since, the data of an individual are highly vulnerable; it must ensures that patients medical vital signs are secure, and are not exposed to an unauthorized person. In this regards, we propose a user authentication scheme for healthcare application using medical sensor networks. The proposed scheme includes: a novel two-factor user authentication, where the healthcare professionals are authenticated before access the patient's body data; a secure session key is establish between the patient sensor node and the professional at the end of user authentication. Furthermore, the analysis shows that the proposed scheme is safeguard to various practical attacks and achieves efficiency at low computation cost.