• Fire Science and Engineering
• /
• v.32 no.6
• /
• pp.40-45
• /
• 2018

The omnidirectional surveillance camera uses the object detection algorithm to level the object by unit so that broadband surveillance can be performed using a fisheye lens and then, it was a field experiment with a system composed of an omnidirectional surveillance camera and a tracking (PTZ) camera. The omnidirectional surveillance camera accurately detects the moving object, displays the squarely, and tracks it in close cooperation with the tracking camera. In the field test of flame detection and temperature of the sensing camera, when the flame is detected during the auto scan, the detection camera stops and the temperature is displayed by moving the corresponding spot part to the central part of the screen. It is also possible to measure the distance of the flame from the distance of 1.5 km, which exceeds the standard of calorific value of 1 km 2,340 kcal. In the performance test of detecting the flame along the distance, it is possible to be 1.5 km in width exceeding $56cm{\times}90cm$ at a distance of 1km, and so it is also adaptable to forest fire. The system is expected to be very useful for safety such as prevention of intrinsic or surrounding fire and intrusion monitoring if it is installed in a petroleum gas storage facility or a storing place for oil in the future.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.3
• /
• pp.395-404
• /
• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• Convergence Security Journal
• /
• v.15 no.4
• /
• pp.35-41
• /
• 2015

Internet of Things has a wide range of vulnerabilities are exposed to information security threats. However, this does not deal with the basic solution, the vaccine does not secure encryption for the data transmission. The encryption and authentication message transmitted from one node to the construction of the secure wireless sensor networks is required. In order to satisfy the constraint, and security requirements of the sensor network, lightweight encryption and authentication technologies, the light key management technology for the sensor environment it is required. Mandatory sensor network security technology, privacy protection technology subchannel attack prevention, and technology. In order to establish a secure wireless sensor networks encrypt messages sent between the nodes and it is important to authenticate. Lightweight it shall apply the intrusion detection mechanism functions to securely detect the presence of the node on the network. From the sensor node is not involved will determine the authenticity of the terminal authentication technologies, there is a need for a system. Network security technology in an Internet environment objects is a technique for enhancing the security of communication channel between the devices and the sensor to be the center.

• Convergence Security Journal
• /
• v.22 no.2
• /
• pp.9-19
• /
• 2022

As the expansion of digital transformation, we are more exposed to the threat of cyber attacks, and many institution or company is operating a signature-based intrusion prevention system at the forefront of the network to prevent the inflow of attacks. However, in order to provide appropriate services to the related ICT system, strict blocking rules cannot be applied, causing many false events and lowering operational efficiency. Therefore, many research projects using artificial intelligence are being performed to improve attack detection accuracy. Most researches were performed using a specific research data set which cannot be seen in real network, so it was impossible to use in the actual system. In this paper, we propose a technique for classifying major attack keywords in the security event log collected from the actual system, assigning a weight to each key keyword, and then performing a similarity check using TF-IDF to determine whether an actual attack has occurred.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.1
• /
• pp.27-37
• /
• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Journal of Internet Computing and Services
• /
• v.17 no.6
• /
• pp.1-8
• /
• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.