{"title":"4. Use of big data in hacking and social engineering","authors":"Shibakali Gupta, A. Mukherjee","doi":"10.1515/9783110606058-004","DOIUrl":null,"url":null,"abstract":": Nowadays, in the fast-paced world of Google and Facebook, every detail of human being could be considered as a set of data or array of data that can be stored, verified, and processed in several ways for the benefits of users. Big data would be perfectly described with humongous large and complex data entities, where classic approach application software is incompetent for them. Big data epitomizes the evidence chattels classified by a high volume, velocity, and variability to require precise technology and analytical approaches for its transformation into value. Big data include netting data, search, data stowing, transmission, updating, data scrutiny, visualization, sharing, querying, data source, and information confidentiality. Big data can castoff in innumerable sectors like defense, health care, and Internet of things. The most famous example probably being Palantir, which was primarily sponsored by the Intelligence Its primary was to deliver analytics sway in the war against terrorism of any kind but with accumulative dependency on big data, the menace of exploitation of this data also arises. The prominence of big data does not gyrate around data magnitude or dimensions rather it revolves around how you process it. You can consider stats from whichever cradle and analyze it to discover answers that facilitate cost diminutions, interval time declines, fresh product development and elevated offerings, and smart management. When you conglomer-ate big data with efficient and dynamic analytics, you can achieve business-corre-lated tasks such as detecting fraudulent behavior, recalculating entire risk portfolios in shorter span of time, determining root causes of failures, disputes, and blemishes in near real time. Few instances such as Cambridge Analytica lighten the insight of the exploitation of the big data. There are several instances where large amount of data has been stolen like in 2014, Yahoo Inc., where 3 billion accounts were effec-tively according to official sources in 2016, Adult Friend Finder where 412.2 million accounts were effected with credit card details of an event that is not a requisite illegal, but sketchy to say the least. The statistic that several sets of international figures were acknowledged in this bulk data set is what marks the news. With the evolution of big data, it makes treasured visions for hackers invariably tempting, but it also provides a big structure of data that con-verts it to payload utmost necessary to protect. In such a scenario, the security of big data is very important. This chapter shares sheer insight of how big data can be used in hacking and social engineering. This chapter will try to list down the ways big data is mined from various sources such as Google Services of Android and Facebook. It will list the various ways the big data is used in day-to-day life by the given companies and other advertising companies. This chapter will try to enlist all the major ill ways this data can be used against us and the ways the important and private data can be protected from the data-collecting companies.","PeriodicalId":93151,"journal":{"name":"The Third IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2017 : The Third IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2017 ; the Second IEEE International Conferenc...","volume":"63 5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Third IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2017 : The Third IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2017 ; the Second IEEE International Conferenc...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/9783110606058-004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: Nowadays, in the fast-paced world of Google and Facebook, every detail of human being could be considered as a set of data or array of data that can be stored, verified, and processed in several ways for the benefits of users. Big data would be perfectly described with humongous large and complex data entities, where classic approach application software is incompetent for them. Big data epitomizes the evidence chattels classified by a high volume, velocity, and variability to require precise technology and analytical approaches for its transformation into value. Big data include netting data, search, data stowing, transmission, updating, data scrutiny, visualization, sharing, querying, data source, and information confidentiality. Big data can castoff in innumerable sectors like defense, health care, and Internet of things. The most famous example probably being Palantir, which was primarily sponsored by the Intelligence Its primary was to deliver analytics sway in the war against terrorism of any kind but with accumulative dependency on big data, the menace of exploitation of this data also arises. The prominence of big data does not gyrate around data magnitude or dimensions rather it revolves around how you process it. You can consider stats from whichever cradle and analyze it to discover answers that facilitate cost diminutions, interval time declines, fresh product development and elevated offerings, and smart management. When you conglomer-ate big data with efficient and dynamic analytics, you can achieve business-corre-lated tasks such as detecting fraudulent behavior, recalculating entire risk portfolios in shorter span of time, determining root causes of failures, disputes, and blemishes in near real time. Few instances such as Cambridge Analytica lighten the insight of the exploitation of the big data. There are several instances where large amount of data has been stolen like in 2014, Yahoo Inc., where 3 billion accounts were effec-tively according to official sources in 2016, Adult Friend Finder where 412.2 million accounts were effected with credit card details of an event that is not a requisite illegal, but sketchy to say the least. The statistic that several sets of international figures were acknowledged in this bulk data set is what marks the news. With the evolution of big data, it makes treasured visions for hackers invariably tempting, but it also provides a big structure of data that con-verts it to payload utmost necessary to protect. In such a scenario, the security of big data is very important. This chapter shares sheer insight of how big data can be used in hacking and social engineering. This chapter will try to list down the ways big data is mined from various sources such as Google Services of Android and Facebook. It will list the various ways the big data is used in day-to-day life by the given companies and other advertising companies. This chapter will try to enlist all the major ill ways this data can be used against us and the ways the important and private data can be protected from the data-collecting companies.