Andere Kunden interessierten sich auch für
![Intrusion Detection for IP-Based Multimedia Communications over Wireless Networks]( "Intrusion Detection for IP-Based Multimedia Communications over Wireless Networks")
Intrusion Detection for IP-Based Multimedia Communications over Wireless Networks37,99 €![Outlook Voice-over-IP Integration]( "Outlook Voice-over-IP Integration")
Outlook Voice-over-IP Integration59,00 €![Privacy-Respecting Intrusion Detection]( "Privacy-Respecting Intrusion Detection")
Privacy-Respecting Intrusion Detection75,99 €![Constructing Predictive Model for Network Intrusion Detection]( "Constructing Predictive Model for Network Intrusion Detection")
Constructing Predictive Model for Network Intrusion Detection38,99 €![Cloud Computing Paradigm]( "Cloud Computing Paradigm")
Cloud Computing Paradigm41,99 €![Trust Based Genetic Neuro-fuzzy System for Intrusion Detection]( "Trust Based Genetic Neuro-fuzzy System for Intrusion Detection")
Trust Based Genetic Neuro-fuzzy System for Intrusion Detection46,99 €![Watchdog based Intrusion detection system in WSN]( "Watchdog based Intrusion detection system in WSN")
Watchdog based Intrusion detection system in WSN26,99 €
Voice over IP (VoIP) has become a major paradigm for
providing flexible telecommunication
services and reducing operational costs. The
large-scale deployment of VoIP has been leveraged
by the high-speed broadband access to the Internet
and the standardization of dedicated protocols.
However, VoIP faces multiple security issues
including vulnerabilities inherited from the
IP layer as well as specific ones. Our objective is
to design, implement and validate new models
and architectures for performing proactive defense,
monitoring and intrusion detection in VoIP
networks. Our work combines two domains: network
security and artificial intelligence. We reinforce
existent security mechanisms by working on three
axes: a machine learning approach for VoIP
signaling traffic monitoring, a VoIP specific
honeypot and a security event correlation model for
intrusion detection.
providing flexible telecommunication
services and reducing operational costs. The
large-scale deployment of VoIP has been leveraged
by the high-speed broadband access to the Internet
and the standardization of dedicated protocols.
However, VoIP faces multiple security issues
including vulnerabilities inherited from the
IP layer as well as specific ones. Our objective is
to design, implement and validate new models
and architectures for performing proactive defense,
monitoring and intrusion detection in VoIP
networks. Our work combines two domains: network
security and artificial intelligence. We reinforce
existent security mechanisms by working on three
axes: a machine learning approach for VoIP
signaling traffic monitoring, a VoIP specific
honeypot and a security event correlation model for
intrusion detection.