Approaches for Anomaly Detection in Network : A Survey

被引:0
作者
Sawant, Anuja A. [1 ]
Game, Pravin S. [1 ]
机构
[1] Pune Inst Comp Technol, Dept Comp Engn, Pune, Maharashtra, India
来源
2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2018年
关键词
Anomaly detection; Classification; Clustering; Feature selection; network communication;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years there is a constant rise in cyber attacks. These attacks affect not only the individuals but the organizations at large also. To detect these attacks requires high-end systems, since there is continuous flow of data to-and-from the network. This huge data flow makes it difficult to analyze traffic and identify anomalous communication. Rule based engines are capable of identifying sophisticated attacks, but it fails to identify unknown and new attacks as the rules are always based on prior knowledge of the administrators. It is virtually impossible to code all the rules beforehand that may capture all the attacks. Most of the attacks have common characteristics, i.e. abnormal or anomalous network communication, authentication attempts or access attempts on objects. This work surveys different approaches to detect anomalies in network communication.
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页数:6
相关论文
共 33 条
[11]  
Chitrakar R, 2012, INT C WIREL COMM NET
[12]  
Foley S., 2018, SEX DRUGS BITCOIN MU, P1
[13]  
Haq NF, 2015, 2015 SAI INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS), P989, DOI 10.1109/IntelliSys.2015.7361264
[14]   Flow-Based Anomaly Detection Using Neural Network Optimized with GSA Algorithm [J].
Jadidi, Zahra ;
Muthukkumarasamy, Vallipuram ;
Sithirasenan, Elankayer ;
Sheikhan, Mansour .
2013 33RD IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS WORKSHOPS (ICDCSW 2013), 2013, :76-81
[15]  
Jyothsna V., 2011, International Journal of Computer Applications, V28, P26
[16]  
Kibirige G., 2015, Int J Comput Sci Inf Secur, V13, P1
[17]   A network intrusion detection system based on a Hidden Naive Bayes multiclass classifier [J].
Koc, Levent ;
Mazzuchi, Thomas A. ;
Sarkani, Shahram .
EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (18) :13492-13500
[18]  
Krishnan R., 2016, INT J PHARM TECHNOLO, P23139
[19]  
Kumar R, 2016, INT CONF IND INF SYS, P1, DOI 10.1109/ICIINFS.2016.8262896
[20]  
Lin Y., 2015, RES ARTICLE SECURITY, V8, P1