Titlebook: Machine Intelligence and Big Data Analytics for Cybersecurity Applications; Yassine Maleh,Mohammad Shojafar,Youssef Baddi Book 2021 The Ed

Lethargic

Machine Learning and Deep Learning Models for Big Data Issuesng. We also regroup the most sensitive security aspects that should be addressed to protect valuable data. All the contributions and dimensions were addressed through a set of security use cases, namely, malware detection, intrusion, anomaly, access control, and data ingestion controls. Furthermore,

施魔法

exclamation

Toward a Knowledge-Based Model to Fight Against Cybercrime Within Big Data Environments: A Set of Keopose a knowledge-based approach to support the fight against cybercrime in the big data context. But, we will answer, at the beginning, a large number of comprehension questions to facilitate as best as possible, to those interested in the subject of “big data and cybercrime”, the understanding of

Optic-Disk

Spam Emails Detection Based on Distributed Word Embedding with Deep Learningre utilized to transform emails into email word vectors, as an essential step for machine learning algorithms. Moreover, optimal parameters are identified for many deep learning architectures and email representation by following the hyper-parameter tuning approach. The performance of many classical

Bph773

AndroShow: A Large Scale Investigation to Identify the Pattern of Obfuscated Android Malwareaset named Android PRAGuard Dataset. Finally, the patterns in a matrix form have been found and stored in a Comma Separated Values (CSV) file which will be the base of detecting the obfuscated malware in future.

有节制

Polydipsia

DAMN

Presentation Attack Detection Frameworkhis type of attack. Existing approaches relying on static features of the iris are not suitable to prevent presentation attacks. Feature from live Iris (or liveness detection) is a promising approach. Further, additional layer of security from iris feature can enable hardening the security of authen

cleaver

Classifying Common Vulnerabilities and Exposures Database Using Text Mining and Graph Theoretical An possible to discover groups of contents, thus, the CVE items which have similarities. Moreover, lacking some concepts pointed out the problems related to CVE such as delays in the review CVE process or not being preferred by some user groups.

Offstage

Secure Data Sharing Framework Based on Supervised Machine Learning Detection System for Future SDN-Bonstructed data set dedicated to SDN context. The simulation results show that our framework can effectively and efficiently address sniffing attacks that can be detected and stopped quickly. Finally, we observe high accuracy with a low false-positive for attack detection.