DeepBot: a time-based botnet detection with deep learning

WC Shi, HM Sun - Soft Computing, 2020 - Springer
Over the decades, as the technology of Internet thrives rapidly, more and more kinds of
cyber-attacks are blasting out around the world. Among them, botnet is one of the most …

Tracking {DDoS} Attacks: Insights into the Business of Disrupting the Web

A Büscher, T Holz - 5th USENIX Workshop on Large-Scale Exploits and …, 2012 - usenix.org
Known for a long time, Distributed Denial-of-Service (DDoS) attacks are still prevalent today
and cause harm on the Internet on a daily basis. The main mechanism behind this kind of …

A novel reputation system to detect DGA-based botnets

R Sharifnya, M Abadi - ICCKE 2013, 2013 - ieeexplore.ieee.org
A botnet is a network of compromised hosts (bots) remotely controlled by a so-called bot
herder through one or more command and control (C&C) servers. New generation botnets …

Optimized random forest model for botnet detection based on DNS queries

A Moubayed, MN Injadat… - 2020 32nd international …, 2020 - ieeexplore.ieee.org
The Domain Name System (DNS) protocol plays a major role in today's Internet as it
translates between website names and corresponding IP addresses. However, due to the …

Botnet economics: uncertainty matters

Z Li, Q Liao, A Striegel - Managing information risk and the economics of …, 2009 - Springer
Botnets have become an increasing security concern in today's Internet. Thus far the
mitigation to botnet attacks is a never ending arms race focusing on technical approaches. In …

Detecting and destroying botnets

G Gross - Network Security, 2016 - Elsevier
Due to their limitless size and capacity, botnets are among the most powerful components of
a modern cyber-criminal's arsenal of attack techniques. They are made up of compromised …

A data-driven network intrusion detection model based on host clustering and integrated learning: a case study on botnet detection

L Ara, X Luo - Security, Privacy, and Anonymity in Computation …, 2019 - Springer
The traditional machine learning based network intrusion detection system (NIDS) is based
on training a model using known network traffic for selected attacks, and testing it on the …

Modelling influence of Botnet features on effectiveness of DDoS attacks

S Ramanauskaitė, N Goranin, A Čenys… - Security and …, 2015 - Wiley Online Library
The number of coordinated and targeted Distributed Denial of Service (DDoS) attacks in the
world used both as information warfare and as economic racket is increasing. It …

Botnets attack detection using machine learning approach for IoT environment

CS Htwe, YM Thant, MMS Thwin - Journal of Physics: Conference …, 2020 - iopscience.iop.org
The era of the Internet of Things (IoT) is very rapidly developing with millions of devices that
are useful in the smart home, smart city, and many other smart systems for education …

[PDF][PDF] BotXrayer: Exposing botnets by visualizing DNS traffic

I Kim, H Choi, H Lee - KSII the first International Conference on …, 2009 - ccs.korea.ac.kr
Botnets pose a major problem to Internet security. They can cause various online crimes
such as DDoS attacks, identity thefts and spam e-mails. While there have been many …