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Unfortunately there is no reliable technique to detect spoofed IP packets.
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This paper presents a new methodology to detect spoofing attacks concerning Generic Object Oriented Substation Event (GOOSE) messages in IEC 61850 communication systems.
Some authors [31, 32] use air monitors (AM) as an additional hardware device that sniffs the traffic passively to detect spoofing attacks on the MAC layer.
This paper introduces a novel and appealing approach to detect face spoofing using the spatiotemporal (dynamic texture) extensions of the highly popular local binary pattern operator.
The future work involves the enhancement of this model in terms of security via a partial network topology to detect attacks like spoofing attack, invalid MPR attack, disruption attack, and hop limit attack.
The second approach is to detect signal abnormality during spoofing.
Anti-spoofing refers to the operation of employing a certain measure or technology to detect and eliminate a GNSS spoofing signal or to hinder the ability of an attacker to spoof a target.
We monitor the inter-arrival time samples at each node in order to detect the presence of IP spoofing in wireless mesh networks thereby providing a way to mitigate collaborative flooding attacks.
It is a difficult task for the listener to detect and filter the spoofing attacks with multiple source addresses than detecting spoofing attacks with single source address.
Furthermore, the intelligent defense system is capable of detecting spoofing and regular flooding attacks.
Our paper focuses on detecting spoof-based collaborative flooding attacks (i.e., detecting collaborative flooding attacks that occur through IP spoofing).
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