Shigeaki Harada

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We investigate how to detect network anomalies using flow statistics obtained through packet sampling. First, we show that network anomalies generating a huge number of small flows, such as network scans or SYN flooding, become difficult to detect when we execute packet sampling. This is because such flows are more unlikely to be sampled than normal flows.(More)
—As a promising solution to manage the huge work-load of large-scale VoD services, managed peer-assisted CDN systems, such as P4P [25] has attracted attention. Although the approach works well in theory or in a controlled environment, to our best knowledge, there have been no general studies that address how actual peers can be incentivized in the wild(More)
—We present a method of detecting network anomalies , such as DDoS (distributed denial of service) attacks and flash crowds, automatically in real time. We evaluated this method using measured traffic data and found that it successfully differentiated suspicious traffic. In this paper, we focus on cyclic traffic, which has a daily and/or weekly cycle, and(More)
The transmission bandwidth consumed by delivering rich content, such as movie files, is enormous, so it is urgent for ISPs to design an efficient delivery system minimizing the amount of network resources consumed. To serve users rich content economically and efficiently, an ISP itself should provide servers with huge storage capacities at a limited number(More)