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Titlebook: Network Science and Cybersecurity; Robinson E. Pino Book 2014 Springer Science+Business Media New York 2014 Alert Aggregation.Anomaly Dete

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發(fā)表于 2025-3-21 16:06:57 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Network Science and Cybersecurity
編輯Robinson E. Pino
視頻videohttp://file.papertrans.cn/663/662845/662845.mp4
概述Introduces new research and development efforts for cybersecurity solutions and applications.Presents Memristor-based technologies for cybersecurity.Covers anomaly detection and algorithms for network
叢書名稱Advances in Information Security
圖書封面Titlebook: Network Science and Cybersecurity;  Robinson E. Pino Book 2014 Springer Science+Business Media New York 2014 Alert Aggregation.Anomaly Dete
描述.Network Science and Cybersecurity. introduces new research and development efforts for cybersecurity solutions and applications taking place within various U.S. Government Departments of? Defense, industry and academic laboratories. .This book examines new algorithms and tools, technology platforms and reconfigurable technologies for cybersecurity systems. Anomaly-based intrusion detection systems (IDS) are explored as a key component of any general network intrusion detection service, complementing signature-based IDS components by attempting to identify novel attacks.? These attacks? may not yet be known or have well-developed signatures.? Methods are also suggested to simplify the construction of metrics in such a manner that they retain their ability to effectively cluster data, while simultaneously easing human interpretation of outliers..This is a professional book for practitioners or government employees working in cybersecurity, and can also be used as a reference.? Advanced-level students in computer science or electrical engineering studying security will also find this book useful .? .
出版日期Book 2014
關(guān)鍵詞Alert Aggregation; Anomaly Detection; Big Data; Cyber Intelligence; Cybersecurity; Hardware Security; Huma
版次1
doihttps://doi.org/10.1007/978-1-4614-7597-2
isbn_softcover978-1-4899-9065-5
isbn_ebook978-1-4614-7597-2Series ISSN 1568-2633 Series E-ISSN 2512-2193
issn_series 1568-2633
copyrightSpringer Science+Business Media New York 2014
The information of publication is updating

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Design of Neuromorphic Architectures with Memristors,lar, the memristor models, synapse circuits, fundamental processing units (neural logic blocks) for the neuromorphic architectures, and hybrid CMOS/memristor neural network (CMHNN) topologies using supervised learning will be presented for different benchmarks.
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User Classification and Authentication for Mobile Device Based on Gesture Recognition,quely recognize a user during their normal interaction with the device while accommodating hardware and biometric features that are constantly changing. Our experimental results demonstrate a great possibility for our gesture-based security scheme to reach sufficient detection accuracy with an undetectable impact on user experience.
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發(fā)表于 2025-3-22 17:06:38 | 只看該作者
Hardware-Based Computational Intelligence for Size, Weight, and Power Constrained Environments,designs for size, weight, and power constrained environments and briefly reviews some of the trends that are influencing the development of solid-state neuromorphic systems. Later sections provide high level examples of selected approaches to hardware design and fabrication.
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Detecting Kernel Control-Flow Modifying Rootkits, execution of a system call. Our technique leverages the Hardware Performance Counters (HPCs) to securely and efficiently count the monitored hardware events. By using HPCs, the checking cost is significantly reduced and the temper-resistance is enhanced.
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發(fā)表于 2025-3-23 07:47:00 | 只看該作者
Bridging the Semantic Gap: Human Factors in Anomaly-Based Intrusion Detection Systems,rule construction similar to those first discussed by Vaccaro and Liepins in 1989 in light of modern results in ensemble learning, and suggest how such constructions could be used generate anomaly-based intrusion detection systems that retain acceptable performance while producing output that is more actionable for human analysts.
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