Big Data Process-Based Security and Privacy Issues and Measures

Autor:	Kesava Pillai Rajadorai, Selvakumar Samuel, Vazeerudeen Abdul Hameed
Rok vydání:	2021
Předmět:	Test data generation Process (engineering) Computer science business.industry Feature extraction Big data Volume (computing) Computer security computer.software_genre Resource (project management) Big data architecture business computer Vulnerability (computing)
Zdroj:	Services and Business Process Reengineering ISBN: 9789811610066
DOI:	10.1007/978-981-16-1007-3_3
Popis:	Big data is a valuable resource that when correctly tapped can produce a large number of vital statistics to solve numerous problems. However, such large volume of data could be contaminated due to security breaches and hence disrupt the benefits from big data. This chapter presents an insight into the various points of vulnerability of big data architecture and the research towards alleviating security breach in big data paradigm. This chapter aims at alleviating fake data generation which is one of the major threats to big data. Feature extraction using Cartesian moment functions has been suggested as a potential tool to handle fake data generation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e79b0d6dd33b912afe7b18e27a63b7b9 https://doi.org/10.1007/978-981-16-1007-3_3 Zobrazit plný text záznamu