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دسته بندی:
محاسبات کوانتومی - Quantum-Computing
سال انتشار:
2022
عنوان انگلیسی مقاله:
A Quantum-Inspired Classifier for Early Web Bot Detection
ترجمه فارسی عنوان مقاله:
یک طبقه بندی الهام گرفته از کوانتومی برای تشخیص زودهنگام ربات وب
منبع:
ieee - ieee Transactions on Information Forensics and Security;2022;17; ;10:1109/TIFS:2022:3170237
نویسنده:
Alberto Cabri; Francesco Masulli; Stefano Rovetta; Grazyna Suchacka
چکیده انگلیسی:
This paper introduces a novel approach, inspired
by the principles of Quantum Computing, to address web bot
detection in terms of real-time classification of an incoming
data stream of HTTP request headers, in order to ensure the
shortest decision time with the highest accuracy. The proposed
approach exploits the analogy between the intrinsic correlation
of two or more particles and the dependence of each HTTP
request on the preceding ones. Starting from the a-posteriori
probability of each request to belong to a particular class, it is
possible to assign a Qubit state representing a combination of the
aforementioned probabilities for all available observations of the
time series. By leveraging the underlying mathematical details
of superposition and entanglement on specific subsequences,
it is possible to devise a measure of membership to each class,
thus enabling the system to take a reliable decision when a
sufficient level of confidence is met or to continue with additional
observations. The results reported in this paper objectively
show the effectiveness of our quantum-inspired algorithm which
outperforms other state-of-the-art approaches, including our own
one based on the Sequential Probability Ratio Test.
Index Terms— Quantum-inspired computing | bot detection | sequential classification | early decision | multinomial classification | multivariate sequence classification.
قیمت: رایگان
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