• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.58-63
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• 2017

Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.889-896
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• 2006

ATM Forum has defined a guaranteed frame rate (GFR) service to serve Internet traffic efficiently. The GFR service provides virtual connections (VCs) for minimum cell rate (MCR) guarantees and allows them to fairly share the residual bandwidth. And ATM Forum has recommended a frame-based generic cell rate algorithm (F-GCRA) as a frame classifier, which determines whether an Am cell is eligible to use the guaranteed bandwidth in a frame level. An ATM switch accommodates cells in its buffer or drops them in a frame level according to current buffer occupancy. A FIFO shared buffer has so simple structure as to be feasibly implemented in switches, but has not been able to provide an MCR guarantee for each VC without buffer management based on per-VC accounting. In this paper, we enhance the F-GCRA frame classifier to guarantee an MCR of each VC without buffer management based on per-VC accounting. The enhanced frame classifier considers burstness of TCP traffic caused by congestion control algorithm so as to enable each VC to use its reserved bandwidth sufficiently. In addition, it is able to alleviate the unfairness problem in usage of the residual bandwidth. Simulation results show that the enhanced frame classifier satisfies quality of services (QoSs) of the GFR service for the TCP traffic.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.105-118
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• 2001

Incident detection rate and false alarm rate are the key measures tot estimating the performance of automatic incident detection algorithms. It is, however inherently very difficult to improve the two measures simultaneously. The main purpose of this study is to present some methods for solving the problem. For this, an incident detection algorithm has been designed in this study. The algorithm is consisted of two functions, one for detecting incident and another for detecting congestion. A logic for distinguishing non-recurrent congestion from recurrent congestion was employed in the algorithm. The new algorithm basically requires speed, flow, and occupancy data for defining incident situation, but the algorithm is able to perform this task without one of the three parameters. The performance of the algorithm has been evaluated by using the field data collected from Interstate Highway 880 in Bay Area, California. The empirical analysis results are very promising and thus, the algorithm proposed may be very useful for the analysts. This paper presents some empirical test results for the performance of California incident detection algorithm, only for the reference purpose.