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您的检索式：作者名="Sakir Sezer"
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| 1 | LSTM RNN:detecting exploit kits using redirection chain sequences显示文摘While consumers use the web to perform routine activities,they are under the constant threat of attack from malicious websites.Even when visiting‘trusted’sites,there is always a risk that site is compromised,and,hosting a malicious script.In this scenario,the injected script would typically force the victim’s browser to undergo a series of redirects before reaching an attacker-controlled domain,which,delivers the actual malware.Although these malicious redirection chains aim to frustrate detection and analysis efforts,they could be used to help identify web-based attacks.Building upon previous work,this paper presents the first known application of a Long Short-Term Memory(LSTM)network to detect Exploit Kit(EK)traffic,utilising the structure of HTTP redirects.Samples are processed as sequences,where each timestep represents a redirect and contains a unique combination of 48 features.The experiment is conducted using a ground-truth dataset of 1279 EK and 5910 benign redirection chains.Hyper-parameters are tuned via K-fold cross-validation(5f-CV),with the optimal configuration achieving an F1 score of 0.9878 against the unseen test set.Furthermore,we compare the results of isolated feature categories to assess their importance. | Jonah Burgess Philip O’Kane Sakir Sezer Domhnall Carlin | 2021 | Cybersecurity2021，4，1： | 4 |
| 2 | Analysis of Bayesian classification based approaches for Android malware detection显示文摘 | Suleiman Y Yerima Sakir Sezer Gavin Mc Williams | 2014 | 8(1):25-362014，8，1： | 1 |
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