The Experts below are selected from a list of 66 Experts worldwide ranked by ideXlab platform
Shirmen Sodbileg - One of the best experts on this subject based on the ideXlab platform.
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classification of artificial intelligence ids for Smurf Attack
2012Co-Authors: N Ugtakhbayar, D Battulga, Shirmen SodbilegAbstract:Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network Attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf Attack with much reliable accuracy.
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Classification of artificial intelligence ids for Smurf Attack
2012Co-Authors: Ugtakhbayar N., Battulga D., Shirmen SodbilegAbstract:Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network Attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf Attack with much reliable accuracy.Comment: 6 pages, 5 figures, 1 tabl
Camacho Cáceres, Nicolás Alfonso - One of the best experts on this subject based on the ideXlab platform.
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Sistema de prevención de intrusos (IPS) para un entorno de red SDN
2016Co-Authors: Camacho Cáceres, Nicolás AlfonsoAbstract:Se presentan las fases de estudio y diseño que sirven para la creación de un prototipo de software de una aplicación de red, la cual cumple funciones de seguridad basada en el funcionamiento de un Sistema de Prevención de Intrusos. Este prototipo de aplicación de red, ejecuta acciones con el fin de prevenir y mitigar dos tipos de ataques de inundación de tráfico. Estos dos ataques son Ping Flood y Smurf Attack, ataques del tipo DoS (Denial of Service). Al mismo tiempo, el prototipo de la aplicación de red, es diseñado para trabajar bajo un entorno que sigue la arquitectura propuesta por la tecnología SDN (Software Defined Networking), utilizando la solución propuesta por Hewlett Packard Enterprise.This Degree Work presents the study and the design phases in the creation of a software prototype about a network application which realizes security functions, based on an Intrusion Prevention System (IPS). This prototype of a network application, execute a preventive action against two different flood Attacks, whose names are Ping Flood and Smurf Attack, both are Denial of Service Attacks. At the same time, this network application prototype is designed to work over a complete SDN (Software Defined Networking) environment with the technology provided by the Hewlett Packard Enterprise (HPE) SDN solution
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Sistema de prevención de intrusos (IPS) para un entorno de red SDN
2016Co-Authors: Camacho Cáceres, Nicolás AlfonsoAbstract:Se presentan las fases de estudio y diseño que sirven para la creación de un prototipo de software de una aplicación de red, la cual cumple funciones de seguridad basada en el funcionamiento de un Sistema de Prevención de Intrusos. Este prototipo de aplicación de red, ejecuta acciones con el fin de prevenir y mitigar dos tipos de ataques de inundación de tráfico. Estos dos ataques son Ping Flood y Smurf Attack, ataques del tipo DoS (Denial of Service). Al mismo tiempo, el prototipo de la aplicación de red, es diseñado para trabajar bajo un entorno que sigue la arquitectura propuesta por la tecnología SDN (Software Defined Networking), utilizando la solución propuesta por Hewlett Packard Enterprise.This Degree Work presents the study and the design phases in the creation of a software prototype about a network application which realizes security functions, based on an Intrusion Prevention System (IPS). This prototype of a network application, execute a preventive action against two different flood Attacks, whose names are Ping Flood and Smurf Attack, both are Denial of Service Attacks. At the same time, this network application prototype is designed to work over a complete SDN (Software Defined Networking) environment with the technology provided by the Hewlett Packard Enterprise (HPE) SDN solution.Ingeniero (a) ElectrónicoPregrad
N Ugtakhbayar - One of the best experts on this subject based on the ideXlab platform.
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classification of artificial intelligence ids for Smurf Attack
2012Co-Authors: N Ugtakhbayar, D Battulga, Shirmen SodbilegAbstract:Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network Attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf Attack with much reliable accuracy.
D Battulga - One of the best experts on this subject based on the ideXlab platform.
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classification of artificial intelligence ids for Smurf Attack
2012Co-Authors: N Ugtakhbayar, D Battulga, Shirmen SodbilegAbstract:Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network Attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf Attack with much reliable accuracy.
Sari Zamah - One of the best experts on this subject based on the ideXlab platform.
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PENERAPAN HYBRID HONEYPOT DAN PHAD UNTUK PENANGANAN SERANGAN DDoS PADA CLOUD COMPUTING
2016Co-Authors: Gagan Dodik, Faiqurahman Mahar, Sari ZamahAbstract:Cloud computing merupakan sebuah teknologi yang memungkinkan para pengguna komputer dapat melakukan komputasi dan berbagi semua sumber daya untuk beberapa layanan melalui internet. Seperti halnya sistem yang lain, cloud computing ini juga sangat rentan terhadap celah keamanan. Serangan DDOS merupakan salah satu ancaman utama yang dapat merusak dan berpengaruh signifikan terhadap kinerja cloud computing. Hal ini dikarenakan cloud computing yang memanfaatkan virtualisasi merupakan sistem yang multi pengguna , dimana serangan pada satu pengguna sama dengan serangan terhadap semua pengguna. Hybrid honeypot dan Packet Header Anomaly Detection (PHAD) merupakan dua metode keamanan yang dapat saling melengkapi untuk mendeteksi serangan pada cloud computing. Hybrid honeypot akan memproses serangan berdasarkan tingkat interaksi serangan yaitu low dan high interaction. Sedangkan PHAD akan mendeteksi serangan berdasarkan pola dari header setiap paket data serta menjadi traffic controller untuk meneruskan paket data (packet forwarder) menuju hybrid honeypot maupun production system. Dalam penelitian ini dua buah metode keamanan tersebut berhasil diterapkan pada cloud computing yang memanfaatkan arsitektur virtual machine, untuk mendeteksi serangan ICMP Flood, TCPSYN Flood, Smurf Attack, Land Attack, Null Scan dan Xmas Scan. Namun, dari hasil pengujian didapatkan hasil bahwa performa sistem sedikit mengalami penurunan, yang dibuktikan dengan kenaikan time response oleh server dan request lost pada paket data
