SSH Traffic Identification Using EM Clustering
نویسندگان
چکیده
منابع مشابه
Transformation-Invariant Clustering Using the EM Algorithm
Clustering is a simple, effective way to derive useful representations of data, such as images and videos. Clustering explains the input as one of several prototypes, plus noise. In situations where each input has been randomly transformed (e.g., by translation, rotation, and shearing in images and videos), clustering techniques tend to extract cluster centers that account for variations in the...
متن کاملThe Risks of Using SSH
Executive Summary This paper deals with security issues surrounding the use of Secure Shell (SSH). SSH is a replacement for telnet, rlogin, ftp, rsh, rcp, rdist, and other r*-based programs. It offers a secure communication channel between computers on an insecure network. Authenticity, confidentiality, and integrity are provided. Despite these features, SSH has several weaknesses that render i...
متن کاملGeneration of SSH Network Traffic Data for IDS Testbeds
We develop an algorithm for generating secure shell (ssh) network traffic that can find use as a part of a testbed for evaluating anomaly detection and intrusion detection systems in cyber security. Given an initial dataset describing real network traffic, the generator produces synthetic traffic with characteristics close to the original. The objective is to match parameters of the original tr...
متن کاملAdaptive EM Clustering
Mining data efficiently is usually a difficult problem due to the size of the datasets involved, the time complexity of the mining operations, and the interactivity in the mining process. Moreover, any solution needs to take into account the available computational and memory resources, available I/O resources (disk and network), and the interaction requirements of the operation. We define algo...
متن کاملHTTP Traffic Graph Clustering using Markov Clustering Algorithm
Graph-based techniques and analysis have been used for IP network traffic analysis. The objective of this paper is to study the hosts' interaction behavior and use graph clustering algorithm, the Markov clustering algorithm, to group (cluster) hosts which have interaction using the HTTP protocol. Using real network traces, the clustering results show that MCL algorithm successfully group t...
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: The Journal of Korea Information and Communications Society
سال: 2012
ISSN: 1226-4717
DOI: 10.7840/kics.2012.37b.12.1160