• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1773-1795
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• 2020

Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

• Knowledge Management Research
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• v.13 no.4
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• pp.83-100
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• 2012

Given the prevalence of mobile social network services (SNS) such as Facebook and Kakaotalk, it has become important to understand user's continuance behavior in a mobile SNS environment. Although trust and privacy concerns play a key role in SNS users' decision-making processes, most studies on SNS have shed little light on the effects of trust and privacy concerns on SNS continuance intention. In this regard, this paper developed an integrated model to deeply understand the key antecedents of user's continuance intention to use mobile SNS by incorporating trust and privacy concerns into extended expectation-confirmation model. The proposed research model was tested by using survey data collected from 170 users who have experience with Kakaotalk. The findings of this study found that the proposed theoretical framework provides a statistically significant explanation of the variance in continuance intention of mobile SNS. The analysis results indicate that trust serves as the salient antecedent of continuance intention to use mobile SNS. However, it was found that privacy concerns negatively influence trust, whereas it is not significantly related to continuance intention of mobile SNS. The theoretical and practical implications of the findings were described.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.149-160
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• 2016

The purpose of this paper is to examine the relationship between the social interactions on the social network and the purchase intention. And the trust propensity of a trustor, the ability of a trustee, and the sincerity of a trustee are selected as the antecedents of social interactions. This paper also examines the effect of type of product as a moderating variable. The result of this paper reveals that social interactions(in terms of closeness, familiarity, and interpersonal trust) have a positive(+) effect on the purchase intention. The more social interactions, the more trustors have intentions to purchase the recommended products by trustees. In addition, the study reveals that the trust propensity of a trustor and the ability of a trustee directly and indirectly influenced on the intention to purchase the recommended product. The findings also suggest that the trust propensity of a trustor and the ability of a trustee have an effect on the closeness, familiarity, and interpersonal trust resulting from social interactions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1113-1135
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• 2018

Existing trust evaluation models for wireless sensor networks can accurately and objectively evaluate trust value of nodes, but the nodes' energy saving problem was ignored. Especially when there are a few malicious nodes in a network, the overall trust value calculation for all nodes would waste lots of energy. Beside that, the network failure caused by nodes death was also not considered. In this paper, we proposed a method for avoiding energy hole which applied trust evaluation models and a trust evaluation method based on information entropy, so as to achieve the purpose of improving nodes utilization. Simulation results show that the proposed method can effectively improve nodes utilization, and it has reasonable detection rate and lower false alert rate compared to other classical methods.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.91-98
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• 2021

Peer to Peer Networks play an increasing role in today's networks, also it's expected that this type of communication networks evolves more in the future. Since the number of users that is involved in Peer to Peer Networks is huge and will be increased more in the future, security issues will appear and increase as well. Thus, providing a sustainable solution is needed to ensure the security of Peer to Peer Networks. This paper is presenting a new protocol called Malicious Trust Managers Identification (MTMI). This protocol is used to ensure anonymity of trust manager, that computes and stores the trust value for another peer. The proposed protocol builds a secure connection between trust managers by using public key infrastructure. As well as experimental testing has been conducted to validate the proposed protocol.

• Convergence Security Journal
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• v.10 no.2
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• pp.51-57
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• 2010

This paper proposes extended trust evaluation mechanism which is able to become the standard of the node selection which provides a better service by using the basic transaction message which occurs from within the mobile Ad-hoc network and the additional transaction message and add confidence value. Furthermore, throughout the simulation shows the efficiency of the proposed trust evaluation mechanism.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.179-192
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• 2012

This paper presents novel statistical algorithms for protecting the iTrust information retrieval network against malicious attacks. In iTrust, metadata describing documents, and requests containing keywords, are randomly distributed to multiple participating nodes. The nodes that receive the requests try to match the keywords in the requests with the metadata they hold. If a node finds a match, the matching node returns the URL of the associated information to the requesting node. The requesting node then uses the URL to retrieve the information from the source node. The novel detection algorithm determines empirically the probabilities of the specific number of matches based on the number of responses that the requesting node receives. It also calculates the analytical probabilities of the specific numbers of matches. It compares the observed and the analytical probabilities to estimate the proportion of subverted or non-operational nodes in the iTrust network using a window-based method and the chi-squared statistic. If the detection algorithm determines that some of the nodes in the iTrust network are subverted or non-operational, then the novel defensive adaptation algorithm increases the number of nodes to which the requests are distributed to maintain the same probability of a match when some of the nodes are subverted or non-operational as compared to when all of the nodes are operational. Experimental results substantiate the effectiveness of the detection and defensive adaptation algorithms for protecting the iTrust information retrieval network against malicious attacks.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.34-50
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• 2017

This study delved into the effects of labor union members' social media utilization for the formation of labor union social capital. Specifically, this study aimed to identify the effects of labor union-related social media use and participation on the labor union's social capital formation through quantitative and qualitative research. It set up trust, network, and participation as social capital components and as dependent variables. Network, in particular, was divided into bonding and bridging aspect. There is the correlation between labor union-related social media use and the formation of labor union social capital. As participation in the group type social media operated by a labor union becomes more active, evaluation on labor union social capital throughout trust, network, and participation is higher. Especially, the correlation between bonding network and bridging network was high. This proves that a labor union's bond enhancement does not result in the labor union's selfishness, but it can build a cooperative system with an external network.

• ETRI Journal
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• v.43 no.4
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• pp.674-683
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• 2021

A trust-aware secure routing protocol (TSRP) for wireless sensor networks is proposed in this paper to defend against varieties of attacks. First, each node calculates the comprehensive trust values of its neighbors based on direct trust value, indirect trust value, volatilization factor, and residual energy to defend against black hole, selective forwarding, wormhole, hello flood, and sinkhole attacks. Second, any source node that needs to send data forwards a routing request packet to its neighbors in multi-path mode, and this continues until the sink at the end is reached. Finally, the sink finds the optimal path based on the path's comprehensive trust values, transmission distance, and hop count by analyzing the received packets. Simulation results show that TSRP has lower network latency, smaller packet loss rate, and lower average network energy consumption than ad hoc on-demand distance vector routing and trust based secure routing protocol.