標(biāo)題: Titlebook: Deployable Machine Learning for Security Defense; Second International Gang Wang,Arridhana Ciptadi,Ali Ahmadzadeh Conference proceedings 20 [打印本頁] 作者: 遠(yuǎn)見 時(shí)間: 2025-3-21 18:29
書目名稱Deployable Machine Learning for Security Defense影響因子(影響力)
書目名稱Deployable Machine Learning for Security Defense影響因子(影響力)學(xué)科排名
書目名稱Deployable Machine Learning for Security Defense網(wǎng)絡(luò)公開度
書目名稱Deployable Machine Learning for Security Defense網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deployable Machine Learning for Security Defense被引頻次
書目名稱Deployable Machine Learning for Security Defense被引頻次學(xué)科排名
書目名稱Deployable Machine Learning for Security Defense年度引用
書目名稱Deployable Machine Learning for Security Defense年度引用學(xué)科排名
書目名稱Deployable Machine Learning for Security Defense讀者反饋
書目名稱Deployable Machine Learning for Security Defense讀者反饋學(xué)科排名
作者: 單片眼鏡 時(shí)間: 2025-3-21 20:19 作者: 不規(guī)則的跳動(dòng) 時(shí)間: 2025-3-22 00:57 作者: 藐視 時(shí)間: 2025-3-22 04:33
: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Represee formats thus appear attractive to other fields such as malware detection, where deep learning on images alleviates the need for comprehensively hand-crafted features generalising to different malware variants. We postulate that this research direction could become the next frontier in Android malw作者: 光明正大 時(shí)間: 2025-3-22 09:18
Attacks on Visualization-Based Malware Detection: Balancing Effectiveness and Executabilitye detection. By converting binary code into images, researchers have shown satisfactory results in applying machine learning to extract features that are difficult to discover manually. Such visualization-based malware detection methods can capture malware patterns from many different malware famili作者: 譏笑 時(shí)間: 2025-3-22 13:52
A Survey on Common Threats in npm and PyPi Registriesveral frameworks to facilitate automation tasks further. Some of these frameworks are Node Manager Package (npm) and Python Package Index (PyPi), which are open source (OS) package libraries. The public registries npm and PyPi use to host packages allow any user with a verified email to publish code作者: 譏笑 時(shí)間: 2025-3-22 17:45 作者: 實(shí)施生效 時(shí)間: 2025-3-22 21:44
Communications in Computer and Information Sciencehttp://image.papertrans.cn/d/image/265762.jpg作者: 掙扎 時(shí)間: 2025-3-23 01:24 作者: 小教堂 時(shí)間: 2025-3-23 09:32 作者: DIS 時(shí)間: 2025-3-23 10:30
Deployable Machine Learning for Security Defense978-3-030-87839-9Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: RADE 時(shí)間: 2025-3-23 14:20
https://doi.org/10.1007/978-3-658-45233-9tic datasets. Organizations are reluctant to share such data, even internally, due to privacy reasons. An alternative is to use synthetically generated data but existing methods are limited in their ability to capture complex dependency structures, between attributes and across time. This paper pres作者: GEN 時(shí)間: 2025-3-23 18:26 作者: poliosis 時(shí)間: 2025-3-24 01:31 作者: ostrish 時(shí)間: 2025-3-24 04:31
Rameshnath Krishnasamy,Peter Vistisene formats thus appear attractive to other fields such as malware detection, where deep learning on images alleviates the need for comprehensively hand-crafted features generalising to different malware variants. We postulate that this research direction could become the next frontier in Android malw作者: 背帶 時(shí)間: 2025-3-24 06:37
Mariana Carvalho,Daniel Rocha,Vítor Carvalhoe detection. By converting binary code into images, researchers have shown satisfactory results in applying machine learning to extract features that are difficult to discover manually. Such visualization-based malware detection methods can capture malware patterns from many different malware famili作者: 細(xì)微的差異 時(shí)間: 2025-3-24 13:37
Design, User Experience, and Usabilityveral frameworks to facilitate automation tasks further. Some of these frameworks are Node Manager Package (npm) and Python Package Index (PyPi), which are open source (OS) package libraries. The public registries npm and PyPi use to host packages allow any user with a verified email to publish code作者: 摸索 時(shí)間: 2025-3-24 15:47 作者: 允許 時(shí)間: 2025-3-24 21:41 作者: 暗語 時(shí)間: 2025-3-25 02:42 作者: 五行打油詩 時(shí)間: 2025-3-25 06:19 作者: Parallel 時(shí)間: 2025-3-25 07:49 作者: Insubordinate 時(shí)間: 2025-3-25 13:14
https://doi.org/10.1007/978-3-658-45233-9. We evaluate the performance of . in terms of quality of data generated, by training it on both a simulated dataset and a real network traffic data set. Finally, to answer the question—can real network traffic data be substituted with synthetic data to train models of comparable accuracy?—we train 作者: arbiter 時(shí)間: 2025-3-25 16:36 作者: Brittle 時(shí)間: 2025-3-25 21:08
Rameshnath Krishnasamy,Peter Vistisenundational due to the exceedingly basic nature of the design choices, allowing to infer what could be a minimal performance that can be obtained with image-based learning in malware detection..The performance of . evaluated on over 158k apps demonstrates that, while simple, our approach is effective作者: Onerous 時(shí)間: 2025-3-26 00:42
Mariana Carvalho,Daniel Rocha,Vítor Carvalhor limitation of the first attack scenario is that a simple pre-processing step can remove the perturbations before classification. For the second attack scenario, it is hard to maintain the original malware’s executability and functionality. In this work, we provide literature review on existing mal作者: Galactogogue 時(shí)間: 2025-3-26 05:17 作者: choroid 時(shí)間: 2025-3-26 08:37
STAN: Synthetic Network Traffic Generation with Generative Neural Models. We evaluate the performance of . in terms of quality of data generated, by training it on both a simulated dataset and a real network traffic data set. Finally, to answer the question—can real network traffic data be substituted with synthetic data to train models of comparable accuracy?—we train 作者: Indebted 時(shí)間: 2025-3-26 16:21
Few-Sample Named Entity Recognition for Security Vulnerability Reports by?Fine-Tuning Pre-trained Lalar, we investigate the performance of fine-tuning several state-of-the-art pre-trained language models on our small training dataset. The results show that with pre-trained language models and carefully tuned hyperparameters, we have reached or slightly outperformed the state-of-the-art system?[.] 作者: 情感 時(shí)間: 2025-3-26 18:11
: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Represeundational due to the exceedingly basic nature of the design choices, allowing to infer what could be a minimal performance that can be obtained with image-based learning in malware detection..The performance of . evaluated on over 158k apps demonstrates that, while simple, our approach is effective作者: Firefly 時(shí)間: 2025-3-27 00:48 作者: micronized 時(shí)間: 2025-3-27 04:10
A Survey on Common Threats in npm and PyPi Registriese package reach. This project will illustrate a high-level overview of common risks associated with OS registries and the package dependency structure. There are several attack types, such as typosquatting and combosquatting, in the OS package registries. Outdated packages pose a security risk, and 作者: 浮雕 時(shí)間: 2025-3-27 05:43 作者: 充氣女 時(shí)間: 2025-3-27 12:01 作者: MERIT 時(shí)間: 2025-3-27 17:08
1876-1100 nted here share the latest findings in unmanned systems, robotics, automation, intelligent systems, control systems, integrated networks, modelling and simulation. This makes the book a valuable resource for researchers, engineers and students alike..978-981-97-1109-3978-981-97-1107-9Series ISSN 1876-1100 Series E-ISSN 1876-1119 作者: Haphazard 時(shí)間: 2025-3-27 17:59
Alexander Vasilevski,Vyacheslav Grishchenkoncreasing expectations fueled by fictional detectives. It follows the initial depictions of the Ripper crimes, the rise of detective fiction, and how real-life detectives and officials crafted their own memoirs and accounts, both to defend against charges of incompetence and to compare their own ski作者: 過剩 時(shí)間: 2025-3-28 01:55 作者: 6Applepolish 時(shí)間: 2025-3-28 03:37
eils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.978-3-662-24159-2978-3-662-26271-9
