Information reconciliation through agent controlled graph model. (c2018)

Abstract

With the advancement of Internet technology and the rise of big data, securing information from malicious attacks has become more important; yet, more challenging. Even though prevention techniques exist, they’re not enough to fully secure the data from malicious activities. Thus, the need for a detection and recovery algorithm to assess the damage and bring the database back to its consistent state in case of an attack. Multiple models have been proposed and different techniques and data structures were used. Our approach provides a damage assessment and recovery algorithm that is based on agents and graphs.