大数据安全可视化

Waqar Ahmed, Uzair Hashmi
{"title":"大数据安全可视化","authors":"Waqar Ahmed, Uzair Hashmi","doi":"10.31645/2013.11.2.6","DOIUrl":null,"url":null,"abstract":"IN 2012 2.5 QB OF DATA (18 ZEROS AFTER 1) WAS GENERATED WORLDWIDE KNOW SO FAR. EVERY DAY DATA CREATION SIZE IS BECOMING BIG-TO-BIGGER THAN WAS SEEN BY EVERYONE SINCE THE BEGINNING OF HUMANKIND. BRIEF DATA GENERATION HISTORY IN CATEGORICAL FASHION IS AS FOLLOWS: 5 Petabytes: Data flowing through Walmart’s transactional databases. Consumers spend $272,000 on Web shopping /day. Apple receives around 47,000 app downloads /minute. On Facebook, Brands receive more than 34,000 “likes” /minute. 8 billion Email messages per day On Twitter 340 million tweets per day On Facebook 684,000 bits of content per day 3,125 new photos uploaded on Flicker per minute. As data size increased so are security threats, which comprise unauthorized modification/ alteration of big data. Conducting security visualization manually on such a large-scale data is beyond compression. Therefore, we need some automated easy to use, time saving technique that can give comprehensive results, which can help to track the integrity of big data.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Security Visualization on Big Data\",\"authors\":\"Waqar Ahmed, Uzair Hashmi\",\"doi\":\"10.31645/2013.11.2.6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"IN 2012 2.5 QB OF DATA (18 ZEROS AFTER 1) WAS GENERATED WORLDWIDE KNOW SO FAR. EVERY DAY DATA CREATION SIZE IS BECOMING BIG-TO-BIGGER THAN WAS SEEN BY EVERYONE SINCE THE BEGINNING OF HUMANKIND. BRIEF DATA GENERATION HISTORY IN CATEGORICAL FASHION IS AS FOLLOWS: 5 Petabytes: Data flowing through Walmart’s transactional databases. Consumers spend $272,000 on Web shopping /day. Apple receives around 47,000 app downloads /minute. On Facebook, Brands receive more than 34,000 “likes” /minute. 8 billion Email messages per day On Twitter 340 million tweets per day On Facebook 684,000 bits of content per day 3,125 new photos uploaded on Flicker per minute. As data size increased so are security threats, which comprise unauthorized modification/ alteration of big data. Conducting security visualization manually on such a large-scale data is beyond compression. Therefore, we need some automated easy to use, time saving technique that can give comprehensive results, which can help to track the integrity of big data.\",\"PeriodicalId\":412730,\"journal\":{\"name\":\"Journal of Independent Studies and Research Computing\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Independent Studies and Research Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31645/2013.11.2.6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Independent Studies and Research Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31645/2013.11.2.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

到目前为止,2012年全球产生了2.5 qb的数据(1后18个0)。每天的数据创建规模都在变得越来越大,比人类诞生以来的任何时候都要大。简要的数据生成历史分类如下:5pb:流经沃尔玛事务数据库的数据。消费者每天在网上购物上花费27.2万美元。苹果每分钟的应用下载量约为4.7万次。在Facebook上,品牌每分钟会收到超过34000个“赞”。每天有80亿条电子邮件在Twitter上每天有3.4亿条推文在Facebook上每天有68.4万个内容每分钟在Flicker上上传3125张新照片。随着数据规模的增加,安全威胁也在增加,其中包括未经授权的大数据修改/更改。在如此大规模的数据上手动执行安全可视化是无法压缩的。因此,我们需要一些自动化的、易于使用的、节省时间的技术,可以给出全面的结果,这有助于跟踪大数据的完整性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Security Visualization on Big Data
IN 2012 2.5 QB OF DATA (18 ZEROS AFTER 1) WAS GENERATED WORLDWIDE KNOW SO FAR. EVERY DAY DATA CREATION SIZE IS BECOMING BIG-TO-BIGGER THAN WAS SEEN BY EVERYONE SINCE THE BEGINNING OF HUMANKIND. BRIEF DATA GENERATION HISTORY IN CATEGORICAL FASHION IS AS FOLLOWS: 5 Petabytes: Data flowing through Walmart’s transactional databases. Consumers spend $272,000 on Web shopping /day. Apple receives around 47,000 app downloads /minute. On Facebook, Brands receive more than 34,000 “likes” /minute. 8 billion Email messages per day On Twitter 340 million tweets per day On Facebook 684,000 bits of content per day 3,125 new photos uploaded on Flicker per minute. As data size increased so are security threats, which comprise unauthorized modification/ alteration of big data. Conducting security visualization manually on such a large-scale data is beyond compression. Therefore, we need some automated easy to use, time saving technique that can give comprehensive results, which can help to track the integrity of big data.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Alzheimer’s Disease Detection: A Deep Learning-Based Approach Performance Comparison Of Three Antennas With Passive Reflecting Walls For Wireless Power Transmission End-Users' Perception Of Cybercrimes Towards E-Banking Adoption And Retention A Review Of Blockchain Technology In Big Data Paradigm Comparative Study Of Software Automation Tools: Selenium And Quick Test Professional
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1