Forecast techniques for predicting increase or decrease of attacks using bayesian inference

Chie Ishida, Yutaka Arakawa, Iwao Sasase, Keisuke Takemori

研究成果: 著書/レポートタイプへの貢献会議での発言

16 引用 (Scopus)

抄録

The analysis techniques of intrusion detection system (IDS) events are actively researched, since it is important to understand attack trends and devise countermeasures against incidents. To aim at a quick response in security operation, it is necessary to forecast a fluctuation of attacks. However, there is no approach for predicting the fluctuation of attacks, since the fluctuation of attacks seems to be random. In this paper, we propose forecast techniques for predicting increase or decrease of the attacks by using the Bayesian Inference for calculating the conditional probability based on past-observed event, counts. We consider two algorithms by focusing on an attack cycle and a fluctuation range of the event counts. We implement a forecasting system and evaluate it with real IDS events. As a result, our proposed technique can forecast increase or decrease of the event counts, and be effective to various types of attacks.

元の言語英語
ホスト出版物のタイトル2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings
ページ450-453
ページ数4
DOI
出版物ステータス出版済み - 12 1 2005
外部発表Yes
イベント2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Victoria, BC, カナダ
継続期間: 8 24 20058 26 2005

出版物シリーズ

名前IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings
2005

会議

会議2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM
カナダ
Victoria, BC
期間8/24/058/26/05

Fingerprint

Intrusion detection

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

これを引用

Ishida, C., Arakawa, Y., Sasase, I., & Takemori, K. (2005). Forecast techniques for predicting increase or decrease of attacks using bayesian inference. : 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings (pp. 450-453). [1517323] (IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings; 巻数 2005). https://doi.org/10.1109/PACRIM.2005.1517323

Forecast techniques for predicting increase or decrease of attacks using bayesian inference. / Ishida, Chie; Arakawa, Yutaka; Sasase, Iwao; Takemori, Keisuke.

2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings. 2005. p. 450-453 1517323 (IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings; 巻 2005).

研究成果: 著書/レポートタイプへの貢献会議での発言

Ishida, C, Arakawa, Y, Sasase, I & Takemori, K 2005, Forecast techniques for predicting increase or decrease of attacks using bayesian inference. : 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings., 1517323, IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings, 巻. 2005, pp. 450-453, 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM, Victoria, BC, カナダ, 8/24/05. https://doi.org/10.1109/PACRIM.2005.1517323
Ishida C, Arakawa Y, Sasase I, Takemori K. Forecast techniques for predicting increase or decrease of attacks using bayesian inference. : 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings. 2005. p. 450-453. 1517323. (IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings). https://doi.org/10.1109/PACRIM.2005.1517323
Ishida, Chie ; Arakawa, Yutaka ; Sasase, Iwao ; Takemori, Keisuke. / Forecast techniques for predicting increase or decrease of attacks using bayesian inference. 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings. 2005. pp. 450-453 (IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings).
@inproceedings{cfd4e518866744d99419f6714fce0b65,
title = "Forecast techniques for predicting increase or decrease of attacks using bayesian inference",
abstract = "The analysis techniques of intrusion detection system (IDS) events are actively researched, since it is important to understand attack trends and devise countermeasures against incidents. To aim at a quick response in security operation, it is necessary to forecast a fluctuation of attacks. However, there is no approach for predicting the fluctuation of attacks, since the fluctuation of attacks seems to be random. In this paper, we propose forecast techniques for predicting increase or decrease of the attacks by using the Bayesian Inference for calculating the conditional probability based on past-observed event, counts. We consider two algorithms by focusing on an attack cycle and a fluctuation range of the event counts. We implement a forecasting system and evaluate it with real IDS events. As a result, our proposed technique can forecast increase or decrease of the event counts, and be effective to various types of attacks.",
author = "Chie Ishida and Yutaka Arakawa and Iwao Sasase and Keisuke Takemori",
year = "2005",
month = "12",
day = "1",
doi = "10.1109/PACRIM.2005.1517323",
language = "English",
isbn = "0780391950",
series = "IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings",
pages = "450--453",
booktitle = "2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings",

}

TY - GEN

T1 - Forecast techniques for predicting increase or decrease of attacks using bayesian inference

AU - Ishida, Chie

AU - Arakawa, Yutaka

AU - Sasase, Iwao

AU - Takemori, Keisuke

PY - 2005/12/1

Y1 - 2005/12/1

N2 - The analysis techniques of intrusion detection system (IDS) events are actively researched, since it is important to understand attack trends and devise countermeasures against incidents. To aim at a quick response in security operation, it is necessary to forecast a fluctuation of attacks. However, there is no approach for predicting the fluctuation of attacks, since the fluctuation of attacks seems to be random. In this paper, we propose forecast techniques for predicting increase or decrease of the attacks by using the Bayesian Inference for calculating the conditional probability based on past-observed event, counts. We consider two algorithms by focusing on an attack cycle and a fluctuation range of the event counts. We implement a forecasting system and evaluate it with real IDS events. As a result, our proposed technique can forecast increase or decrease of the event counts, and be effective to various types of attacks.

AB - The analysis techniques of intrusion detection system (IDS) events are actively researched, since it is important to understand attack trends and devise countermeasures against incidents. To aim at a quick response in security operation, it is necessary to forecast a fluctuation of attacks. However, there is no approach for predicting the fluctuation of attacks, since the fluctuation of attacks seems to be random. In this paper, we propose forecast techniques for predicting increase or decrease of the attacks by using the Bayesian Inference for calculating the conditional probability based on past-observed event, counts. We consider two algorithms by focusing on an attack cycle and a fluctuation range of the event counts. We implement a forecasting system and evaluate it with real IDS events. As a result, our proposed technique can forecast increase or decrease of the event counts, and be effective to various types of attacks.

UR - http://www.scopus.com/inward/record.url?scp=33746813204&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33746813204&partnerID=8YFLogxK

U2 - 10.1109/PACRIM.2005.1517323

DO - 10.1109/PACRIM.2005.1517323

M3 - Conference contribution

AN - SCOPUS:33746813204

SN - 0780391950

SN - 9780780391956

T3 - IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings

SP - 450

EP - 453

BT - 2005 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, PACRIM - Proceedings

ER -