Botnet Detection via mining of network traffic flow

Effective and scalable botnet detection in network traffic

An Enhanced Model for Network Flow Based Botnet Detection

The botnet is a group of hijacked computers, which are employed under command and control mechanism administered by a botmaster. Botnet evolved from IRC based centralized botnet to employing common protocols such as HTTP with decentralized architectures and then peer-to-peer designs. As Botnets have become more sophisticated, the need for advanced techniques and research against botnets has gro...

DGA-Based Botnet Detection Using DNS Traffic

In recent years, an increasing number of botnets use Domain Generation Algorithms (DGAs) to bypass botnet detection systems. DGAs, also referred as “domain fluxing”, has been used since 2004 for botnet controllers, and now become an emerging trend for malware. It can dynamically and frequently generate a large number of random domain names which are used to prevent security systems from detecti...

Http Botnet Detection Using Frequent Patternset Mining

Among the diverse forms of malware, Botnet is the most widespread and serious threat which occurs commonly in today's cyberattacks. A botnet is a group of compromised computers which are remotely controlled by hackers to launch various network attacks, such as DDoS attack, spam, click fraud, identity theft and information phishing. The defining characteristic of botnets is the use of command an...

Towards Flow - based Abnormal Network Traffic Detection

One recent trend in network security attacks is an increasing number of indirect attacks which influence network traffic negatively, instead of directly entering a system and damaging it. In future, damages from this type of attack are expected to become more serious. In addition, the bandwidth consumption by these attacks influences the entire network performance. This paper presents an abnorm...