… of attacks on binary, multiclass and multilabel classification by applying four machine
learning … In summation to this the parameter tuning for proposed SVM based attack type label …

… attack to multi-label classification, extending existing attacks … the problem of generating an
attack to a linear programming … ] propose a multi-label attack procedure with an additional …

… the attack, it … rank and the detection using some machine learning algorithms to balance
the dimensionality of data and the accuracy. We focus on detecting the PortMap DDoS attack as …

… This survey focuses on various rank attacks and their proposed detection … the details on
how an attacker triggers rank attack, how rank attack affects … KNN machine learning algorithm …

… attack against deep ranking systems, ie, the Order Attack, … infeasible in a real-world attack
scenario due to various black… attacks: Reliable attacks against black-box machine learning …

… Building on this result, we design attack algorithms against UCB-… attack strategy against
any algorithm under the general click model. Each attack algorithm manipulates the learning …

… an alternative attack graph ranking scheme based on a recent approach to machine learning
in a … for the task of ranking attack graphs by learning a ranking function from examples and …

… In this section, we report the result of ranking attack experiments based on the ranking …
Practical black-box attacks against machine learning. In Proceedings of the 2017 ACM on …

… In this paper, we proposed a machine learning model for detecting decreased rank attacks.
The proposed model consists of three steps, namely data collection, feature extraction using …

… However, the vulnerability of DNN-based image ranking … attacks against deep ranking
systems, i.e., Candidate Attack … Second, our attacks can be extended to universal ranking attacks …