Botnet Detection using Clustering Algorithms
نویسندگان
چکیده
منابع مشابه
Botnet Detection using Clustering Algorithms
In this paper, some clustering techniques are analyzed to compare their ability to detect botnet traffic by selecting features that distinguish connections belonging to or not belonging to a botnet. By considering the history of network’s connections, some clustering algorithms are used to derive a set of rules to decide which should be considered as a botnet. Our main contribution is to evalua...
متن کاملBotnet Detection Using Passive DNS
The Domain Name System (DNS) is a distributed naming system fundamental for the normal operation of the Internet. It provides a mapping between user-friendly domain names and IP addresses. Cyber criminals use the flexibility provided by the DNS to deploy certain techniques that allow them to hide the Command and Control (CnC) servers used to manage their botnets and frustrate the detection effo...
متن کاملData clustering using community detection algorithms
One of the most important problems in science is that of inferring knowledge from data. The most challenging issue is the unsupervised classification of patterns (observations, measurements, or feature vectors) into groups (clusters) according to their similarity. The quantification of similarity is usually performed in terms of distances or correlations between pairs. The resulting similarity ...
متن کاملBOTNET Detection Approach by DNS Behavior and Clustering Analysis
Botnets are one of the most serious threats to internet security. A botnet is a network of computers on internet which are under the influence of a malware code, oblivious to the owner of that computer and sends out transmissions (virus or spam) to other computers on internet. Botnet can be utilized for DoS attacks, phishing, spamming and many other fraudulent activities. Therefore, it is impor...
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: Research in Computing Science
سال: 2016
ISSN: 1870-4069
DOI: 10.13053/rcs-118-1-6