A supervised clustering algorithm for computer intrusion detection
نویسندگان
چکیده
منابع مشابه
ahp algorithm and un-supervised clustering in auto insurance fraud detection
this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...
15 صفحه اولA clustering algorithm for intrusion detection
In this paper, we introduce a new clustering algorithm, FCC, for intrusion detection based on the concept of fuzzy connectedness. This concept was introduced by Rosenfeld in 1979 and used with success in image segmentation; here we extend this approach to clustering and demonstrate its effectiveness in intrusion detection. Starting with a single or a few seed points in each cluster, all the dat...
متن کاملAn Unsupervised Clustering Algorithm for Intrusion Detection
As the Internet spreads to each corner of the world, computers are exposed to miscellaneous intrusions from the World Wide Web. Thus, we need effective intrusion detection systems to protect our computers from the intrusions. Traditional instance-based learning methods can only be used to detect known intrusions since these methods classify instances based on what they have learned. They rarely...
متن کاملTCM-KNN Algorithm for Supervised Network Intrusion Detection
As network attacks have increased in number and severity over the past few years, intrusion detection is increasingly becoming a critical component of secure information systems and supervised network intrusion detection has been an active and difficult research topic in the field of intrusion detection for many years. However, it hasn’t been widely applied in practice due to some inherent issu...
متن کاملA Rough-Fuzzy Hybrid Algorithm for Computer Intrusion Detection
In this paper, we propose an intrusion detection method that combines rough sets theory and fuzzy c-means for anomaly detection. The first step consists of attribute selection which is based on rough set theory for each of the 5 classes of intrusions in the Defense Advanced Research Projects Agency (DARPA) data is identified. The next phase is clustering by using fuzzy c-means; we are using rou...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Knowledge and Information Systems
سال: 2005
ISSN: 0219-1377,0219-3116
DOI: 10.1007/s10115-005-0195-8