• Journal of Korean Society of Environmental Engineers
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• v.31 no.12
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• pp.1161-1168
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• 2009

This research was conducted on characteristic of offensive odors in Shihwa industrial complex. Result of blocks distribution of TVOC indicates that mechanic block, site D, was the highest concentration (74 ppb). Chemistry block, site A, was the second highest concentration (50 ppb). Also, mixed blocks, metal blocks and park etc. were measured almost similar concentration about 30 ppb, but mixed block, site F, was the place where concentrations were the smallest. Average of TVOC was shown about 35 ppb concentration. Aldehydes including acetaldehyde, butyraldehyde and hydrogen sulfide concentrations were prevalent among offensive odors in Shihwa industrial complex. Comparing the offensive odor intensity mostly about acetaldehyde, butyraldehyde and hydrogen sulfide which contain high offensive odor intensity showed results that sites A, B (chemistry block) and site D, I (mechanic block) site H (metal block) have showed the intensity over 1. In the case of acetaldehyde, relatively the high odor intensities over '2' were able to obtain in many cases. The correlation coefficient (r) for hydrogen sulfide was 0.91, so that high positive correlation exists between offensive odor intensity and the hydrogen sulfide element. Butyraldehyde also showed high positive correlation coefficient, as 0.82. Correlation coefficient of acetaldehyde that had the highest value as offensive odor substance was 0.62, had somewhat correlation with offensive odor intensity.

• Smart Media Journal
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• v.4 no.4
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• pp.24-32
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• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.