Titlebook: Machine Learning Approaches in Cyber Security Analytics; Tony Thomas,Athira P. Vijayaraghavan,Sabu Emmanuel Book 2020 Springer Nature Sing

苦惱

Applications of Decision Trees, data points in a dataset by constructing tree structures. These tree-like structures are used to make accurate predictions about unseen data. The dataset is split into multiple subsets, thereby resulting in each decision node branching to more decision nodes. The very first decision node from which

使熄滅

Adversarial Machine Learning in Cybersecurity, machine learning model. For instance, attributes of a goodware can be added to a malware executable to make the classifier identify a malicious sample as benign. As the name suggests, “adversary” means opponent or enemy. If you are thinking what an enemy has got to do in machine learning, this chap

殺死

https://doi.org/10.1007/978-981-15-1706-8Malware; Anomaly Detection; Biometrics; Machine Intelligence; Cyber Security; data structures

Expurgate

978-981-15-1708-2Springer Nature Singapore Pte Ltd. 2020

lethal

悠然

Clustering and Malware Classification,alling malware without the user’s knowledge or authorization. In such a situation where the user’s data and privacy are always at threat, it is necessary to build a resilient system so as to curb such attacks. The system should undergo a learning–decision-making process to early detect and defend malware attacks.

傳染

Nearest Neighbor and Fingerprint Classification, data point in the test dataset and then assign it to a class that is most represented by the neighbors. NN classifier works by taking into consideration the maximum number of nearest neighbors belonging to the similar class.

Veneer

NUL

Tony Thomas,Athira P. Vijayaraghavan,Sabu EmmanuelIncludes applications of the latest machine learning algorithms in cyber security.Discusses how applications in cyber security analytics complement machine learning research.Provides the latest resear

吞噬

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