標(biāo)題: Titlebook: Data Analytics and Decision Support for Cybersecurity; Trends, Methodologie Iván Palomares Carrascosa,Harsha Kumara Kalutarage Book 2017 Sp [打印本頁] 作者: Sediment 時(shí)間: 2025-3-21 18:35
書目名稱Data Analytics and Decision Support for Cybersecurity影響因子(影響力)
書目名稱Data Analytics and Decision Support for Cybersecurity影響因子(影響力)學(xué)科排名
書目名稱Data Analytics and Decision Support for Cybersecurity網(wǎng)絡(luò)公開度
書目名稱Data Analytics and Decision Support for Cybersecurity網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Analytics and Decision Support for Cybersecurity被引頻次
書目名稱Data Analytics and Decision Support for Cybersecurity被引頻次學(xué)科排名
書目名稱Data Analytics and Decision Support for Cybersecurity年度引用
書目名稱Data Analytics and Decision Support for Cybersecurity年度引用學(xué)科排名
書目名稱Data Analytics and Decision Support for Cybersecurity讀者反饋
書目名稱Data Analytics and Decision Support for Cybersecurity讀者反饋學(xué)科排名
作者: Consequence 時(shí)間: 2025-3-21 21:12 作者: placebo-effect 時(shí)間: 2025-3-22 02:35 作者: exhilaration 時(shí)間: 2025-3-22 05:09 作者: FLING 時(shí)間: 2025-3-22 11:15 作者: doxazosin 時(shí)間: 2025-3-22 14:51
https://doi.org/10.1057/9780230623781ork that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be e作者: doxazosin 時(shí)間: 2025-3-22 20:23 作者: 燈泡 時(shí)間: 2025-3-23 01:04
https://doi.org/10.1057/9780230623781hone platforms. “Total mobile malware has grown 151% over the past year”, according to McAfee?’s quarterly treat report in September 2016. By design, Android. is “open” to download apps from different sources. Its security depends on restricting apps by combining digital signatures, sandboxing, and 作者: interference 時(shí)間: 2025-3-23 01:59 作者: 光明正大 時(shí)間: 2025-3-23 07:01 作者: 名詞 時(shí)間: 2025-3-23 12:30 作者: DEBT 時(shí)間: 2025-3-23 15:34
Reem Wagdy Moustafa Kamel Abd El-Raoofification depends on various aspects. Though the data classification technique has a major impact on classification accuracy, the nature of the data also matters lot. One of the main concerns that can hinder the classification accuracy is the availability of noise. Therefore, both choosing the appro作者: giggle 時(shí)間: 2025-3-23 21:13
https://doi.org/10.1007/978-981-19-1376-1data to regulate power flow, shape demand with a plethora of pieces of information and ensure reliability at all times. However, the extensive use of information technologies in the power system may also form a Trojan horse for cyberattacks. Smart power systems where information is utilized to predi作者: 積云 時(shí)間: 2025-3-24 01:54
https://doi.org/10.1007/978-3-030-58035-3for cybersecurity. Current analytical time taken to identify zero-day attacks and respond with a patch or detection mechanism is unmeasurable. This is a current challenge and struggle for cybersecurity researchers. User- and data provenance-centric approaches are the growing trend in aiding defensiv作者: 不知疲倦 時(shí)間: 2025-3-24 05:21
A Toolset for Intrusion and Insider Threat Detectionork that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be e作者: 偏狂癥 時(shí)間: 2025-3-24 07:30
Human-Machine Decision Support Systems for Insider Threat Detectionvileged access and knowledge, are already in a position of great responsibility for contributing towards the security and operations of the organisation. Should an individual choose to exploit this privilege, perhaps due to disgruntlement or external coercion from a competitor, then the potential im作者: HAUNT 時(shí)間: 2025-3-24 14:23 作者: eczema 時(shí)間: 2025-3-24 18:48 作者: 欲望 時(shí)間: 2025-3-24 21:43 作者: 跳脫衣舞的人 時(shí)間: 2025-3-25 01:29 作者: Tartar 時(shí)間: 2025-3-25 04:15
Attribute Noise, Classification Technique, and Classification Accuracyification depends on various aspects. Though the data classification technique has a major impact on classification accuracy, the nature of the data also matters lot. One of the main concerns that can hinder the classification accuracy is the availability of noise. Therefore, both choosing the appro作者: Ganglion 時(shí)間: 2025-3-25 10:09 作者: Blasphemy 時(shí)間: 2025-3-25 15:09
Visualization and Data Provenance Trends in Decision Support for Cybersecurityfor cybersecurity. Current analytical time taken to identify zero-day attacks and respond with a patch or detection mechanism is unmeasurable. This is a current challenge and struggle for cybersecurity researchers. User- and data provenance-centric approaches are the growing trend in aiding defensiv作者: Commonplace 時(shí)間: 2025-3-25 15:52
https://doi.org/10.1057/9780230623781ithin a dynamic and ever-changing organisation? More recently, there has been interest in how visual analytics can be incorporated with machine-based approaches, to alleviate the data analytics challenges of anomaly detection and to support human reasoning through visual interactive interfaces. Furt作者: 文件夾 時(shí)間: 2025-3-25 21:22 作者: Pseudoephedrine 時(shí)間: 2025-3-26 02:26
https://doi.org/10.1007/978-3-030-14869-0ese data to improve the performance of the decision engine. Finally, the decision engine is designed based on the Dirichlet mixture model with a lower-upper interquartile range as decision engine. The performance of this framework is evaluated on two well-known datasets, the NSL-KDD and UNSW-NB15. T作者: 嚙齒動(dòng)物 時(shí)間: 2025-3-26 07:19 作者: 歡呼 時(shí)間: 2025-3-26 08:34
Reem Wagdy Moustafa Kamel Abd El-Raoof data about online credit-card transactions. According to the empirical outcomes, we find that the noise hinders the classification accuracy significantly. In addition, the results indicate that the accuracy of data classification depends on the quality of the data and the used classification techni作者: Arb853 時(shí)間: 2025-3-26 13:58
https://doi.org/10.1007/978-981-19-1376-1he overall goal of the intelligent system is to provide a degree of possibility as to whether the load demand is legitimate or it has been manipulated in a way that is a threat to the safety of the node and that of the grid in general. The proposed system is tested with real-world data.作者: 重疊 時(shí)間: 2025-3-26 20:12 作者: fastness 時(shí)間: 2025-3-26 22:47
Human-Machine Decision Support Systems for Insider Threat Detectionithin a dynamic and ever-changing organisation? More recently, there has been interest in how visual analytics can be incorporated with machine-based approaches, to alleviate the data analytics challenges of anomaly detection and to support human reasoning through visual interactive interfaces. Furt作者: 評(píng)論者 時(shí)間: 2025-3-27 01:10
Dynamic Analysis of Malware Using Run-Time Opcodesd as a means of enhancing the feature set. Feature selection was then investigated to tackle the feature explosion which resulted in more than 100,000 features in some cases. As the earliest detection of malware is the most favourable, run-length, i.e. the number of recorded opcodes in a trace, was 作者: GLUT 時(shí)間: 2025-3-27 06:07
Big Data Analytics for Intrusion Detection System: Statistical Decision-Making Using Finite Dirichleese data to improve the performance of the decision engine. Finally, the decision engine is designed based on the Dirichlet mixture model with a lower-upper interquartile range as decision engine. The performance of this framework is evaluated on two well-known datasets, the NSL-KDD and UNSW-NB15. T作者: 動(dòng)物 時(shí)間: 2025-3-27 12:35
Security of Online Examinationsr unauthorized access to sensitive information. In order to prevent such attacks and impersonation threats, we have employed smart techniques of continuous authentication. Therefore, we propose two schemes; Interactive and Secure E-Examination Unit (ISEEU) which is based on video monitoring, and Sma作者: STALL 時(shí)間: 2025-3-27 17:07
Attribute Noise, Classification Technique, and Classification Accuracy data about online credit-card transactions. According to the empirical outcomes, we find that the noise hinders the classification accuracy significantly. In addition, the results indicate that the accuracy of data classification depends on the quality of the data and the used classification techni作者: Genetics 時(shí)間: 2025-3-27 20:38
Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbanche overall goal of the intelligent system is to provide a degree of possibility as to whether the load demand is legitimate or it has been manipulated in a way that is a threat to the safety of the node and that of the grid in general. The proposed system is tested with real-world data.作者: archetype 時(shí)間: 2025-3-28 02:00
Visualization and Data Provenance Trends in Decision Support for Cybersecurity Security visualization showing provenance from a spectrum of data samples on an attack helps researchers to reconstruct the attack from source to destination. This helps identify possible attack patterns and behaviors which results in the creation of effective detection mechanisms and cyber-attacks作者: Congeal 時(shí)間: 2025-3-28 04:38 作者: collagen 時(shí)間: 2025-3-28 09:31 作者: compassion 時(shí)間: 2025-3-28 11:41
Book 2017ises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detecti作者: RADE 時(shí)間: 2025-3-28 16:48
Book 2017n Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision作者: Locale 時(shí)間: 2025-3-28 22:17 作者: 侵略者 時(shí)間: 2025-3-29 02:07
Detecting Malicious Collusion Between Mobile Software Applications: The Android, Case to carry out attacks. In this chapter we report on recent and ongoing research results from our ACID project which suggest a number of reliable means to detect collusion, tackling the aforementioned problems. We present our conceptual work on the topic of collusion and discuss a number of automated tools arising from it.作者: Gleason-score 時(shí)間: 2025-3-29 04:08
https://doi.org/10.1057/9780230623781ledge of domain experts and analyse the data from three different views. We argue that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods. This way, we try to detect novel attacks while simultaneously limiting the number of false positives.作者: 歡笑 時(shí)間: 2025-3-29 08:33
A Toolset for Intrusion and Insider Threat Detectionledge of domain experts and analyse the data from three different views. We argue that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods. This way, we try to detect novel attacks while simultaneously limiting the number of false positives.作者: 鍍金 時(shí)間: 2025-3-29 14:06
