Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comp...
Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.
In the purview of most educational sectors today, numerous reviews regarding data mining have been the primary focus, with goals of discovering vast knowledge patterns for students' data. This paper focuses on bui...
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The aggregation operator is a popular tool for dealing with multi-criteria decision-making (MCDM) problems. An MCDM technique based on the modified picture fuzzy weighted geometric operator (MPFWGO) is proposed in thi...
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The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simulta...
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An analysis of the signaling systems used in the Intelligent Communication Network has been carried out. The main probabilistic characteristics of signal information delay are determined. A method for calculating thes...
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The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets...
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In this paper, we developed and investigated some four-dimensional profit maximization transportation problems considering damageablity and substitutability, where the parameters are of a type-2 normal uncertain varia...
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In response to the growing imperative of addressing environmental concerns and aligning with governmental regulations in supply chain management, this study navigates the optimization landscape of closed-loop supply c...
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The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern searc...
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ISBN:
(纸本)9781665476249
The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care; molecular biology & immunology; and phylogenetic & epidemiological studies.
The research results of the Love wave propagation in the semi-space contact area and in a thin layer are presented. The dependences, which allow analyzing the effect of various conditions on the Love wave dispersion, ...
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