• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.6018-6033
• /
• 2018

Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.1-10
• /
• 2021

The purpose of the study is to contribute to the positive development of blockchain technology by providing data to examine security vulnerabilities and threats to blockchain-based services and review countermeasures. The findings of this study are as follows. Threats to the security of blockchain-based services can be classified into application security threats, smart contract security threats, and network (P2P) security threats. First, application security threats include wallet theft (e-wallet stealing), double spending (double payment attack), and cryptojacking (mining malware infection). Second, smart contract security threats are divided into reentrancy attacks, replay attacks, and balance increasing attacks. Third, network (P2P) security threats are divided into the 51% control attack, Sybil attack, balance attack, eclipse attack (spread false information attack), selfish mining (selfish mining monopoly), block withholding attack, DDoS attack (distributed service denial attack) and DNS/BGP hijacks. Through this study, it is possible to discuss the future plans of the blockchain technology-based ecosystem through understanding the functional characteristics of transparency or some privacy that can be obtained within the blockchain. It also supports effective coping with various security threats.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.6
• /
• pp.1153-1166
• /
• 2011

Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose the variable precision rough sets based misbehavior detection scheme which detects false alert message and misbehaving nodes by observing their action after sending out the alert messages. In the proposed scheme, the alert information system, alert profile is constructed from valid actions of moving nodes in vehicular ad-hoc networks. Once a moving vehicle receives an alert message from another vehicle, it finds out the alert type from the alert message. When the vehicle later receives a beacon from alert raised vehicle after an elapse of time, then it computes the relative classification error by using variable precision rough sets from the alert information system. If the relative classification error is lager than the maximum allowable relative classification error of the alert type, the vehicle decides the message as false alert message. Th performance of the proposed scheme is evaluated as two metrics: correct ratio and incorrect ratio through a simulation.

• Korean Journal of Cognitive Science
• /
• v.27 no.3
• /
• pp.469-499
• /
• 2016

The present study investigated the cognitive mechanism underlying online processing of Korean syntactic (for example, A bed/a clock belongs to/doesn't belong to the furniture "침대는/시계는 가구에 속한다/속하지 않는다") and lexical negation (for example, A tiger/a butterfly has/doesn't have a tail "호랑이는/나비는 꼬리가 있다/없다") using an ERP(Event-related potentials) technique and a truth-value verification task. 23 Korean native speakers were employed for the whole experiment and 15's brain responses (out of 23) were recorded for the ERP analysis. The behavioral results (i.e. verification task scores) show that there is universal pattern of the accuracy and response time for verification process: True-Affirmative (high accuracy and short latency) > False-Affirmative > False-Negated > True-Negated. However, the components (early N400 & P600) reflecting the immediate processing of a negation operator were observed only in lexical negation. Moreover, the ERP patterns reflecting an effect of truth value were not identical: N400 effect was observed in the true condition compared to the false condition in the lexically negated sentences, whereas Positivity effect (like early P600) was observed in the false condition compared to the true condition in the syntactically negated sentences. In conclusion, the form and location of negation operator varied by languages and negation types influences the strategy and pattern of online negation processing, however, the final representation resulting from different computational processing of negation appears to be language universal and is not directly affected by negation types.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.6
• /
• pp.9-15
• /
• 2010

Cognitive radio is a technology, which automatically recognizes and searches for temporally and spatially unused frequency spectrum, then actively determines the communication method, bandwidth, etc. according to the environment, thus utilizing the limited spectrum resources efficiently. In this paper, with the imperfect sensing of misdetection and false alarm, we quantitatively investigate the effects of primary and secondary user's queue on the primary and secondary users' spectrum usage through the analysis of continuous time Markov Chain. With the queue primary user's spectrum usage improved up to 18%, and the secondary user's spectrum usage improved up to 50%.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.6
• /
• pp.1-8
• /
• 2010

Wireless multimedia service through the access to mobile telephone network or data network is a vital part of contemporary life, and the demand for frequency spectrum for new services is expected to explode as the ubiquitous computing proliferate. Cognitive radio is a technology, which automatically recognizes and searches for temporally and spatially unused frequency spectrum, then actively determines the communication method, bandwidth, etc. according to the environment, thus utilizing the limited spectrum resources efficiently. In this paper, we investigate the effects of imperfect sensing, misdetection and false alarm, on the primary and secondary users' spectrum usage through the analysis of continuous time Markov Chain. We analyzed the effects of the parameters such as sensing error, offered load on the system performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.6
• /
• pp.1-7
• /
• 2016

As new information and communication technologies evolve, security threats are also becoming increasingly intelligent and advanced. In this paper, we analyze the time series data continuously entered through a series of periods from the network device or lightweight IoT (Internet of Things) devices by using the statistical technique and propose a system to detect abnormal behaviors of the device or abnormality based on the analysis results. The proposed system performs the first level abnormal detection by using previously entered data set, thereafter performs the second level anomaly detection according to the trust bound configured by using stored time series data based on time attribute or group attribute. Multi-level analysis is able to improve reliability and to reduce false positives as well through a variety of decision data set.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2013.07a
• /
• pp.11-13
• /
• 2013

무선 센서 네트워크는 개방된 환경에서 무작위로 배치되어 악의적인 공격자들에게 쉽게 노출된다. 센서 노드는 한정된 에너지 자원과 손쉽게 훼손된다는 단점을 통해 허위 보고서와 투표 삽입 공격이 발생한다. Li와 Wu는 두 공격을 대응하기 위해 확률적 투표기반 여과기법을 제안하였다. 확률적 투표기반 여과기법은 고정적인 검증 경로를 결정하기 때문에 특정 노드의 에너지 자원고갈 위험이 있다. 본 논문에서는 센서 네트워크에서 보고서 여과 확률 향상을 위하여 퍼지 시스템을 기반으로 다음 노드 선택을 약 6% 효율적인 경로 선택 방법을 제안한다. 제안 기법은 전달 경로 상의 노드 중 상태정보가 높은 노드를 검증 노드로 선택하고, 선택된 검증 노드는 허용 범위 경계 값을 기준으로 공격 유형을 판별하고 여과한다. 실험결과를 통해 제안기법은 기존기법과 비교하였을 때 에너지 효율이 향상되었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.2
• /
• pp.77-83
• /
• 2010

Vehicular Ad Hoc Networks are self-organizing Peer-to-Peer networks that typically have highly mobile vehicle nodes, moving at high speeds, very short-lasting and unstable communication links. VANETs are formed without fixed infrastructure, central administration, and dedicated routing equipment, and network nodes are mobile, joining and leaving the network over time. So, VANET-security is very vulnerable for the intrusion of malicious and misbehaving nodes in the network, since VANETs are mostly open networks, allowing everyone connect, without centralized control. In this paper, we propose a rough set based anomaly detection method that efficiently identify malicious behavior of vehicle node activities in these VANETs, and the performance of a proposed scheme is evaluated by a simulation in terms of anomaly detection rate and false alarm rate for the threshold ${\epsilon}$.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.9
• /
• pp.4271-4294
• /
• 2018

Communication cost is the most important factor in Wireless Sensor Networks (WSNs), as exchanging control keying messages consumes a large amount of energy from the constituent sensor nodes. Time-based Dynamic Keying and En-Route Filtering (TICK) can reduce the communication costs by utilizing local time values of the en-route nodes to generate one-time dynamic keys that are used to encrypt reports in a manner that further avoids the regular keying or re-keying of messages. Although TICK is more energy efficient, it employs no re-encryption operation strategy that cannot determine whether a healthy report might be considered as malicious if the clock drift between the source node and the forwarding node is too large. Secure SOurce-BAsed Loose Synchronization (SOBAS) employs a selective encryption en-route in which fixed nodes are selected to re-encrypt the data. Therefore, the selection of encryption nodes is non-adaptive, and the dynamic network conditions (i.e., The residual energy of en-route nodes, hop count, and false positive rate) are also not focused in SOBAS. We propose an energy efficient selection of re-encryption nodes based on fuzzy logic. Simulation results indicate that the proposed method achieves better energy conservation at the en-route nodes along the path when compared to TICK and SOBAS.