scholarly journals Unsupervised detection of botnet activities using frequent pattern tree mining

Author(s):  
Siqiang Hao ◽  
Di Liu ◽  
Simone Baldi ◽  
Wenwu Yu

AbstractA botnet is a network of remotely-controlled infected computers that can send spam, spread viruses, or stage denial-of-service attacks, without the consent of the computer owners. Since the beginning of the 21st century, botnet activities have steadily increased, becoming one of the major concerns for Internet security. In fact, botnet activities are becoming more and more difficult to be detected, because they make use of Peer-to-Peer protocols (eMule, Torrent, Frostwire, Vuze, Skype and many others). To improve the detectability of botnet activities, this paper introduces the idea of association analysis in the field of data mining, and proposes a system to detect botnets based on the FP-growth (Frequent Pattern Tree) frequent item mining algorithm. The detection system is composed of three parts: packet collection processing, rule mining, and statistical analysis of rules. Its characteristic feature is the rule-based classification of different botnet behaviors in a fast and unsupervised fashion. The effectiveness of the approach is validated in a scenario with 11 Peer-to-Peer host PCs, 42063 Non-Peer-to-Peer host PCs, and 17 host PCs with three different botnet activities (Storm, Waledac and Zeus). The recognition accuracy of the proposed architecture is shown to be above 94%. The proposed method is shown to improve the results reported in literature.

2019 ◽  
pp. 1952-1983
Author(s):  
Pourya Shamsolmoali ◽  
Masoumeh Zareapoor ◽  
M.Afshar Alam

Distributed Denial of Service (DDoS) attacks have become a serious attack for internet security and Cloud Computing environment. This kind of attacks is the most complex form of DoS (Denial of Service) attacks. This type of attack can simply duplicate its source address, such as spoofing attack, which defending methods do not able to disguises the real location of the attack. Therefore, DDoS attack is the most significant challenge for network. In this chapter we present different aspect of security in Cloud Computing, mostly we concentrated on DDOS Attacks. The Authors illustrated all types of Dos Attacks and discussed the most effective detection methods.


2013 ◽  
Vol 13 (3) ◽  
pp. 334-342 ◽  
Author(s):  
Jiang-Hui Cai ◽  
Xu-Jun Zhao ◽  
Shi-Wei Sun ◽  
Ji-Fu Zhang ◽  
Hai-Feng Yang

Author(s):  
Pourya Shamsolmoali ◽  
Masoumeh Zareapoor ◽  
M.Afshar Alam

Distributed Denial of Service (DDoS) attacks have become a serious attack for internet security and Cloud Computing environment. This kind of attacks is the most complex form of DoS (Denial of Service) attacks. This type of attack can simply duplicate its source address, such as spoofing attack, which defending methods do not able to disguises the real location of the attack. Therefore, DDoS attack is the most significant challenge for network. In this chapter we present different aspect of security in Cloud Computing, mostly we concentrated on DDOS Attacks. The Authors illustrated all types of Dos Attacks and discussed the most effective detection methods.


Author(s):  
Padmavathi .S ◽  
M. Chidambaram

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.


2017 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
Hanane Bennasar ◽  
Mohammad Essaaidi ◽  
Ahmed Bendahmane ◽  
Jalel Benothmane

Cloud computing cyber security is a subject that has been in top flight for a long period and even in near future. However, cloud computing permit to stock up a huge number of data in the cloud stockage, and allow the user to pay per utilization from anywhere via any terminal equipment. Among the major issues related to Cloud Computing security, we can mention data security, denial of service attacks, confidentiality, availability, and data integrity. This paper is dedicated to a taxonomic classification study of cloud computing cyber-security. With the main objective to identify the main challenges and issues in this field, the different approaches and solutions proposed to address them and the open problems that need to be addressed.


Sign in / Sign up

Export Citation Format

Share Document