• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.157-165
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• 2024

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

• Journal of Korean Neurosurgical Society
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• v.30 no.3
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• pp.263-271
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• 2001

Objective : Glioblastomas, the most common type of primary brain tumors, are highly invasive and cause massive tissue destruction at both the tumor invading edges and in areas that are not in direct contact with glioma cells. As a result, patients with high-grade gliomas are faced with a poor prognosis. Such grim statistics emphasize the need to better understand the mechanisms that underlie glioma invasion, as these may lead to the identification of novel targets in the therapy of high grade gliomas. Protein kinase C(PKC) is a family of serine/threonine kinases and an important signal transduction enzyme that conveys signals generated by ligand-receptor interaction at the cell surface to the nucleus. PKC appears to be critical in regulating many aspects of glioma biology. The purpose of this study was to assess accurately the role of PKC in the invasion regulation of human gliomas based on hypothesis that protein kinase C(PKC) is functional in the process of glial tumor cell invasion. Method : To test this hypothesis, U-87 malignant glioma cell line intracellular PKC levels were up and down regulated and their invasiveness was tested. Intracellular PKC level was characterized using PKC activity assays. Invasion assays including barrier migration and spheroid confrontation were used to study the relationship between PKC concentration and invasiveness. Result : The cell line which were treated by PKC inhibitor tamoxifen and hypericin exhibited decreased PKC activity and decreased invasive abilities dose dependently both in matrigel invasion assay and tumor spheroid fetal rat brain aggregates(FRBA) confrontation assay. However, the cell line that was treated by PKC activator 12-O-tetradecanylphorbol-13acetate(TPA) did not exhibit increases in either PKC activity or invasive ability. Conclusion : These studies suggest that PKC may be a useful molecular target for the chemotherapy of glioblastoma and other malignancies and that a therapeutic approach based on the ability of PKC inhibitors may be helpful in preventing invasion.