ISSN 2394-5125
 

Research Article 


Approaches for Detecting Anomaly in Real Time Network

Arun Prakash Agrawal, Amrita.

Abstract
The omnipresence of the Internet and coming of connected devices has cleared a path to attack networks for intruders which prompt financial loss, cyber-attack, information loss in cyber war and healthcare. Consequently, network security investigation has become a significant field of concern and it has achieved serious consideration between researchers, off late, particularly in anomaly detection field in the network that is viewed as critical for network security. In any case, primer researches have uncovered that existing approaches in-network for detecting anomalies are not effectual sufficient, especially in real time to detect them. The ineffectiveness of current methods is due to the accumulation by devices connected of enormous volumes of knowledge. In this context, it is important to suggest a sort of framework that adequately manages the real-time broad data processing and the identification of service anomalies. This paper attempts to tackle the issue of deviations in real time. The fact. This article has also examined state of the art BID analysis techniques in real time in relation to the identification of anomalies and the important features of the associated machine learning. Begin with the description of relevant taxonomy and meanings of live time data analytics, spatial relationship and computational mathematics algorithms, and follow up with the overview of the biodata technology.

Key words: Anomaly Detection, Big Data Processing, Machine Learning, Real Time Network and Security Analytics.


 
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Pubmed Style

Arun Prakash Agrawal, Amrita. Approaches for Detecting Anomaly in Real Time Network. JCR. 2020; 7(10): 765-769. doi:10.31838/jcr.07.10.152


Web Style

Arun Prakash Agrawal, Amrita. Approaches for Detecting Anomaly in Real Time Network. http://www.jcreview.com/?mno=114681 [Access: August 17, 2021]. doi:10.31838/jcr.07.10.152


AMA (American Medical Association) Style

Arun Prakash Agrawal, Amrita. Approaches for Detecting Anomaly in Real Time Network. JCR. 2020; 7(10): 765-769. doi:10.31838/jcr.07.10.152



Vancouver/ICMJE Style

Arun Prakash Agrawal, Amrita. Approaches for Detecting Anomaly in Real Time Network. JCR. (2020), [cited August 17, 2021]; 7(10): 765-769. doi:10.31838/jcr.07.10.152



Harvard Style

Arun Prakash Agrawal, Amrita (2020) Approaches for Detecting Anomaly in Real Time Network. JCR, 7 (10), 765-769. doi:10.31838/jcr.07.10.152



Turabian Style

Arun Prakash Agrawal, Amrita. 2020. Approaches for Detecting Anomaly in Real Time Network. Journal of Critical Reviews, 7 (10), 765-769. doi:10.31838/jcr.07.10.152



Chicago Style

Arun Prakash Agrawal, Amrita. "Approaches for Detecting Anomaly in Real Time Network." Journal of Critical Reviews 7 (2020), 765-769. doi:10.31838/jcr.07.10.152



MLA (The Modern Language Association) Style

Arun Prakash Agrawal, Amrita. "Approaches for Detecting Anomaly in Real Time Network." Journal of Critical Reviews 7.10 (2020), 765-769. Print. doi:10.31838/jcr.07.10.152



APA (American Psychological Association) Style

Arun Prakash Agrawal, Amrita (2020) Approaches for Detecting Anomaly in Real Time Network. Journal of Critical Reviews, 7 (10), 765-769. doi:10.31838/jcr.07.10.152