• Journal of the Korea Society for Simulation
• /
• v.18 no.3
• /
• pp.83-90
• /
• 2009

Since wireless sensor networks are deployed in open environments, an attacker can physically capture some sensor nodes. Using information of compromised nodes, an attacker can launch false data injection attacks that report nonexistent events. False data can cause false alarms and draining the limited energy resources of the forwarding nodes. In order to detect and discard such false data during the forwarding process, various security solutions have been proposed. But since they are prevention-based solutions that involve additional operations, they would be energy-inefficient if the corresponding attacks are not launched. In this paper, we propose a detection method that can detect false data injection attacks without extra overheads. The proposed method is designed based on the signature of false data injection attacks that has been derived through simulation. The proposed method detects the attacks based on the number of reporting nodes, the correctness of the reports, and the variation in the number of the nodes for each event. We show the proposed method can detect a large portion of attacks through simulation.

• The Journal of Society for e-Business Studies
• /
• v.17 no.4
• /
• pp.17-37
• /
• 2012

The evolution of the IT facilitated the social actions of the consumers by supporting social communication of the online users. At the same time it help for the consumer to post malicious comments on the Internet or to spread the unproven news for distorting the public opinion in the SNSs. Although the number of the consumer unethical behaviors and the estimated damage of the innocent companies have been increased, a few studies had investigate on this issue. Based on the Literature on the consumer unethical behaviors and the institution based trust, we had developed the defense strategies against the consumer unethical behaviors. This study would introduce the new perspective that the consumer could always not be innocent. Also, the defense strategy developed in this study could contribute to make the guideline for consumer service manual.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.7
• /
• pp.9-16
• /
• 2020

In this paper, we propose a prototype design and implementation of a fire detection algorithm using multiple sensors. The proposed topic detection system determines fire by applying rules based on data from multiple sensors. The fire takes about 3 to 5 minutes, which is the optimal time for fire detection. This means that timely identification of potential fires is important for fire management. However, current fire detection devices are very vulnerable to false alarms because they rely on a single sensor to detect smoke or heat. Recently, with the development of IoT technology, it is possible to integrate multiple sensors into a fire detector. In addition, the fire detector has been developed with a smart technology that can communicate with other objects and perform programmed tasks. The prototype was produced with a success rate of 90% and a false alarm rate of 10% based on 10 actual experiments.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.2
• /
• pp.119-126
• /
• 2012

Local monitoring is an effective technique in securing data of wireless sensor networks. Existing solutions require high communication cost for detecting false data and this results in a network lifetime being shortened. This paper proposes novel techniques of monitoring based secure data aggregation and filtering false data in wireless sensor networks. The aim is to reduce energy consumption in securing data aggregation. An aggregator and its monitoring node perform data aggregation in a 60o sextant cluster. By checking Message Authentication Codes (MAC), aggregation data will be dropped by a forward aggregator if data aggregated by the aggregator and data monitored by the monitoring node are inconsistent. The simulation shows that the proposed protocol can reduce the amount of average energy consumption about 64% when comparing with the Data Aggregation and Authentication protocol (DAA)[1]. Additionally, the network lifetime of the proposed protocol is 283% longer than that of DAA without any decline in data integrity.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.12
• /
• pp.207-215
• /
• 2013

The general opinion about the notion of cyberbullying hasn't existed yet, but in related laws it is defined as the entire behavior causing the counterpart to suffer the pain by continuously and repeatedly psychologic offending toward specific students with information and telecommunication products such as the Internet and mobile phones, and spreading the private information or false facts related with specific students. Recently a number of accidents related with abuse of cyberbullying are being broadcast on a variety of mass media, and the argument about the severity and countermeasures against cyberbullying is moving onward. This study has a purpose as suggesting the practical alternatives to prevent cyberbullying victim of middle school students by arguing cyberbullying of middle school students and analyzing the relationship between the general features such as victimized experience and frequency and the emotional behaviors according to victimized experience. As the result of this study, cyberbullying victimized experience has a significant effect on the emotional behavior such as depression, aggression, and academic stress. As political implication, this study suggests the practical alternatives to prevent cyberbullying of middle school students based on the analysis result.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.4
• /
• pp.179-188
• /
• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of Navigation and Port Research
• /
• v.42 no.4
• /
• pp.245-252
• /
• 2018

A method of transmitting an alert signal in case of man-overboard (MOB) systems in a small fishing vessel navigating within coastal area is being operated as VHF-DSC equipment via a distress alert button and V-P ass Equipment via alert button or beacon separation. However, a small fishing vessel with a couple of crews on board is an inappropriate way to alert a man-overboard condition. However, internationally, MOB equipment using VHF-DSC, AIS, and Bluetooth technologies is used to transmit alert signals directly to the mother ship and other radio stations. In order to analyze the performance and technology of the MOB equipment operating in foreign countries, it was confirmed that the alarm signal can be received within a maximum of one nautical mile when the MOB device is on the water surface. An MOB device that meets domestic conditions needs to send an alarm signal to a station within the VHF communication range. However, in order to reduce the false alert signal, it is most appropriate to operate the VHF-DSC radio equipment installed on the ship remotely. Analysis of various technologies connecting the MOB and the VHF-DSC revealed that the Bluetooth system has advantages such as device miniaturization. When an emergency signal is transmitted from the MOB device, it can be received by a dedicated receiver and recognized through an external input terminal of the VHF-DSC equipment generating its own alarm. If the emergency situation cannot be processed at the mother ship, a distress alert is sent to all radio stations via VHF-DSC for response under emergencies faced by small fishing vessels.