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Towards minimizing efforts for Morphing Attacks-Deep embeddings for morphing pair selection and improved Morphing Attack Detection. [PDF]
PLoS OneKessler R, Raja K, Tapia J, Busch C.
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Detection Efficiency Mismatch and Finite-Key-Size Attacks on Practical Quantum Cryptography Systems
, 2016 Poompong Chaiwongkhot
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Large-scale IoT attack detection scheme based on LightGBM and feature selection using an improved salp swarm algorithm. [PDF]
Sci RepChen W, Yang H, Yin L, Luo X.
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2021
The major network security problems faced by many internet users is the DDoS (distributed denial of service) attack. This attack makes the service inaccessible by exhausting the network and resources with high repudiation and economic loss. It denies the network services to the potential users.
Megala G. +2 more
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The major network security problems faced by many internet users is the DDoS (distributed denial of service) attack. This attack makes the service inaccessible by exhausting the network and resources with high repudiation and economic loss. It denies the network services to the potential users.
Megala G. +2 more
openaire +1 more source
Proceedings of the third ACM conference on Recommender systems, 2009
It has been shown in recent years that effective profile injection or shilling attacks can be mounted on standard recommendation algorithms. These attacks consist of the insertion of bogus user profiles into the system database in order to manipulate the recommendation output, for example to promote or demote the predicted ratings for a particular ...
Neil Hurley, Zunping Cheng, Mi Zhang
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It has been shown in recent years that effective profile injection or shilling attacks can be mounted on standard recommendation algorithms. These attacks consist of the insertion of bogus user profiles into the system database in order to manipulate the recommendation output, for example to promote or demote the predicted ratings for a particular ...
Neil Hurley, Zunping Cheng, Mi Zhang
openaire +1 more source
Detection by Attack: Detecting Adversarial Samples by Undercover Attack
2020The safety of artificial intelligence systems has aroused great concern due to the vulnerability of deep neural networks. Studies show that malicious modifications to the inputs of a network classifier, can fool the classifier and lead to wrong predictions. These modified inputs are called adversarial samples.
Qifei Zhou +4 more
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Statistical Analysis and Data Mining: The ASA Data Science Journal, 2015
AbstractA targeted network intrusion typically evolves through multiple phases, termed the attack chain. When appropriate data are monitored, these phases will generate multiple events across the attack chain on a compromised host. It is shown empirically that events in different parts of the attack chain are largely independent under nonattack ...
Sexton, Joseph +2 more
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AbstractA targeted network intrusion typically evolves through multiple phases, termed the attack chain. When appropriate data are monitored, these phases will generate multiple events across the attack chain on a compromised host. It is shown empirically that events in different parts of the attack chain are largely independent under nonattack ...
Sexton, Joseph +2 more
openaire +1 more source
New Electronics, 2020
ULTRASOC AND AGILE ANALOG WORK TO DETECT PHYSICAL CYBER-ATTACKS.
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ULTRASOC AND AGILE ANALOG WORK TO DETECT PHYSICAL CYBER-ATTACKS.
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