• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.41-49
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• 2009

In ubiquitous sensor networks, sensor nodes can be compromised by an adversary since they are deployed in hostile environments. False sensing reports can be injected into the network through these compromised nodes, which may cause not only false alarms but also the depletion of limited energy resource in the network. In the security solutions for the filtering of false reports, the choice of a security threshold value which determines the security level is important. In the existing adaptive solutions, a newly determined threshold value is broadcasted to the whole nodes, so that extra energy resource may be consumed unnecessarily. In this paper, we propose an application of the recursive contract net protocol to determine the threshold value which can provide both energy efficiency and sufficient security level. To manage the network more efficiently, the network is hierarchically grouped, and the contract net protocol is applied to each group. Through the protocol, the threshold value determined by the base station using a fuzzy logic is applied only where the security attack occurs on.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.447-452
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• 2013

Berkley Media Access Control (B-MAC) protocol is one of the well-known MAC protocols, which uses adaptive preamble sampling scheme and is designed for wireless sensor networks (WSN). In this paper, we are reviewed about security vulnerability in B-MAC, and analyzed the power which is consumed at each stage of B-MAC protocol according to vulnerability of denial of sleep(DoS) and replay problem. From our analytical results, it can be considered the need of power efficient authentication scheme which provides the reliability, efficiency, and security for a general B-MAC communication. This is the case study of possible DoS vulnerability and its power consumption in B-MAC.

• ETRI Journal
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• v.34 no.1
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• pp.76-86
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• 2012

The block cipher ARIA has been threatened by side-channel analysis, and much research on countermeasures of this attack has also been produced. However, studies on countermeasures of ARIA are focused on software implementation, and there are no reports about hardware designs and their performance evaluation. Therefore, this article presents an advanced masking algorithm which is strong against second-order differential power analysis (SODPA) and implements a secure ARIA hardware. As there is no comparable report, the proposed masking algorithm used in our hardware module is evaluated using a comparison result of software implementations. Furthermore, we implement the proposed algorithm in three types of hardware architectures and compare them. The smallest module is 10,740 gates in size and consumes an average of 47.47 ${\mu}W$ in power consumption. Finally, we make ASIC chips with the proposed design, and then perform security verification. As a result, the proposed module is small, energy efficient, and secure against SODPA.

• Convergence Security Journal
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• v.8 no.1
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• pp.91-100
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• 2008

The previous works in sensor networks security have focused on the aspect of confidentiality, authentication and integrity based on cryptographic primitives. There has been no prior work to assess the survivability in systematic way. Accordingly, this paper presents a survivability model of wireless sensor networks using software rejuvenation for dual adaptive cluster head. The survivability model has state transition to reflect status of real wireless sensor networks. In this paper, we only focus on a survivability model which is capable of describing cluster head compromise in the networks and able to switch over the redundant cluster head in order to increase the survivability of that cluster. Second, this paper presents how to enhance the survivability of sensor networks using software rejuvenation methodology for dual cluster head in wireless sensor network. We model and analyze each cluster as a stochastic process based on Semi Markov Process (SMP) and Discrete Time Markov Chain (DTMC). The proof of example scenarios and numerical analysis shows the feasibility of our approach.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1402-1411
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• 2014

Buyer-seller watermarking protocol is defined as the practice of imperceptible altering a digital content to embed a message using watermarking in the encryption domain. This protocol is acknowledged as one kind of copyright protection techniques in electronic commerce. Buyer-seller watermarking protocol is fundamentally based on public-key cryptosystem that is operating using the algebraic property of an integer. However, in general usage, digital contents which are handled in watermarking scheme mostly exist as real numbers in frequency domain through DCT, DFT, DWT, etc. Therefore, in order to use the watermarking scheme in a cryptographic protocol, digital contents that exist as real number must be transformed into integer type through preprocessing beforehand. In this paper, we presented a new watermarking scheme in an encrypted domain in an image that is based on the block-DCT framework and homomorphic encryption method for buyer-seller watermarking protocol. We applied integral-processing in order to modify the decimal layer. And we designed a direction-adaptive watermarking scheme by analyzing distribution property of the frequency coefficients in a block using JND threshold. From the experimental results, the proposed scheme was confirmed to have a good robustness and invisibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6243-6259
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• 2019

As a foundation of next-generation air transportation systems, automatic dependent surveillance-broadcast (ADS-B) helps pilots and air traffic controllers create a safer and more efficient national airspace system. Owing to the open communication environment, it is easy to insert fake aircraft into the system via spoofing or the insertion of false messages. Efforts have thus been made in academic research and practice in the aviation industry to ensure the security of transmission of messages of the ADS-B system. An identity-based batch verification (IBV) scheme was recently proposed to enhance the security and efficiency of the ADS-B system, but current IBV schemes are often too resource intensive because of the application of complex hash-to-point operations or bilinear pairing operations. In this paper, we propose a lightweight IBV signature scheme for the ADS-B system that is robust against adaptive chosen message attacks in the random oracle model, and ensures the security of batch message verification and against the replaying attack. The proposed IBV scheme needs only a small and constant number of point multiplication and point addition computations instead of hash-to-point or pairing operations. Detailed performance analyses were conducted to show that the proposed IBV scheme has clear advantages over prevalent schemes in terms of computational cost and transmission overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3104-3123
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• 2022

The development of Vehicular Ad hoc Network (VANET) has greatly improved the efficiency and safety of social transportation, and the routing strategy for VANET has also received high attention from both academia and industry. However, studies on dynamic matching of routing policies with the message types of VANET are in short supply, which affects the operational efficiency and security of VANET to a certain extent. This paper studies the message types in VANET and fully considers the urgency and reliability requirements of message forwarding under various types. Based on the diversified types of messages to be transmitted, and taking the diversified message forwarding strategies suitable for VANET scenarios as behavioral candidates, an adaptive routing method for the VANET message types based on reinforcement learning (RL) is proposed. The key parameters of the method, such as state, action and reward, are reasonably designed. Simulation and analysis show that the proposed method could converge quickly, and the comprehensive performance of the proposed method is obviously better than the comparison methods in terms of timeliness and reliability.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.1-13
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• 2022

With the development of network technologies, the security to protect organizational resources from internal and external intrusions and threats becomes more important. Therefore in recent years, the anomaly detection algorithm that detects and prevents security threats with respect to various security log events has been actively studied. Security anomaly detection algorithms that have been developed based on rule-based or statistical learning in the past are gradually evolving into modeling based on machine learning and deep learning. In this study, we propose a deep-autoencoder model that transforms LSTM-autoencoder as an optimal algorithm to detect insider threats in advance using various machine learning analysis methodologies. This study has academic significance in that it improved the possibility of adaptive security through the development of an anomaly detection algorithm based on unsupervised learning, and reduced the false positive rate compared to the existing algorithm through supervised true positive labeling.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.333-348
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• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.486-494
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• 2014

Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.