Relational Data Leakage Detection using Fake Object and Allocation Strategies
Relational Data Leakage Detection using Fake Object and Allocation Strategies
复制标题
使用虚假对象和分配策略的关系数据泄漏检测
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
P. Desai
中科院分区：
文献类型：
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作者：
J. Chavan;P. Desai
在当今世界，有许多公司需要外包他们的业务流程（如市场营销，人力资源）和相关活动的第三方，如他们的服务供应商。在许多情况下，服务供应商希望访问公司的机密信息，如客户数据、银行详细信息，以提供他们的服务。对于大多数公司来说，外包供应商使用的敏感数据量在不断增加。因此，在当今的情况下，数据泄漏是一种全球范围内常见的风险和错误，防止数据泄漏是一项广泛的业务挑战。因此，我们需要强大的技术来检测这种不诚实。传统上，泄漏检测是通过水印来处理的，水印在某些情况下是非常有用的，但同样需要对原始数据进行一些修改。因此，本文研究了一种用于检测一组对象或记录的泄漏的不显眼技术。该模型是为评估代理人的“罪恶感”而开发的。该算法用于将对象分配给代理，以提高我们识别泄密者的机会。最后，考虑向分布式集中添加“假”对象的选项。该系统的主要贡献是利用假消除概念建立了罪恶感模型
In today’s world, there is need of many companies to outsource their sure business processes (e.g. marketing ,human resources) and related activities to a third party like their service suppliers. In many cases the service supplier desires access to the company’s confidential information like customer data, bank details to hold out their services. And for most corporations the amount of sensitive data used by outsourcing providers continues to increase. So in today’s condition data Leakage is a Worldwide Common Risks and Mistakes and preventing data leakage is a business-wide challenge. Thus we necessitate powerful technique that can detect such a dishonest. Traditionally, leakage detection is handled by watermarking, Watermarks can be very useful in some cases, but again, involve some modification of the original data. So in this paper, unobtrusive techniques are studied for detecting leakage of a set of objects or records. The model is developed for assessing the “guilt” of agents. The algorithms are present for distributing objects to agents, in a way that improves our chances of identifying a leaker. Finally, consider the option of adding “fake” objects to the distributed set. The major contribution in this system is to develop a guilt model using fake elimination concept