DATA PROVENANCE: A DATA LEAKAGE DETECTION MODEL
Neha Belekar · International journal of advance research and innovative ideas in education · 2017
In today’s era, information leakage is one of the most serious threats to companies. A data owner sends secret or confidential information to a group of trusted data consumers. Some of the information is lost and found in an inappropriate place. Thus data has been leaked. Data leakage means data distributed by the data owner is leaked by one or more agents. This causes a huge harm to the business. The distributor must assess whether data is leaked from one or more agents. To enhance the probability of detecting data loss, data allocation strategies (across the agents) are used. A data lineage framework is used for identifying a guilty entity. The digital watermarking is a technique in which vital information is kept hidden in the original data for protecting unauthorised copying and circulation of data. An accountable data transfer protocol can be built using transfer method, watermarking, and signature primitives. In some occasions fake data records can be injected in order to improve detecting data loss and identifying the guilty entity. The data sent by the data owner must be protected, secret and it must not be regenerated. The framework of data lineage is considered for transmission of data and is a key step towards achieving accountability.