… user profiles for their utility in attack detection. We show that a machine learning classification
approach that includes attributes derived from attack models is more successful than more …

… In the first row, ieresults for a “Machine Learning” textbook query, the similarity score of the
5-th to 7-th candidates are 0.9242. The score of the 9-th to 11-th candidates are 0.9240. That …

… attacks aimed at ranking improvement, we denote πn(q, di) = πy(q, di) − 1 as the neighborhood
rank … Finally, we evaluate the defense performance of ranking models using the attacked …

… attack detection of some topological & identity attacks like rank attack, wormhole attack and
Sybil attack … IDS based on machine learning to indentify and prevent these attacks to make …

… l in lth layer is performed through gradient ranking. With the … Then, we descendingly rank
the vulnerability of bits by the absolute value of their gradients ∂L/∂b and elect the bits whose …

… of attacks including rank attacks, version attacks, flood attacks and so forth. Rank attack is a
major attack … Since rank attacks have a significant adverse effect on the network, an effort has …

… impact of combined rank and blackhole attacks is studied by … devices attack the RPL-based
network by advertising false rank … Therefore, a machine learning approach would be more …

… definition as shown in the research from the machine learning (ML) community [80… Then,
we analyze the defensive ability of different ranking models against the word-level query attack. …

… To evaluate our method under attribution attack, the iterative feature importance attacks (IFIA)
using top-k intersection as dissimilarity function (top-k) [8] is adapted. IFIA generates …

… The goal of this work was to study rank attack as one of the more dangerous attacks that
affect the RPL routing protocol. We measured the RPL rank attack with the standard RPL and …