Sharif Digital Repository

With the growing deployment of host and network intrusion detection systems, analyzing generated alerts from these systems becomes critically important and challenging due to its complexity and high amount of data. Alert Correlation systems are a possible solution for deep analysis of incoming alerts in response to potential attacks against enterprise networks. Although several known alert correlation systems have been proposed for this purpose so far, most of them do not support high amount of input due to their centralized architecture. In this thesis, we propose a system architecture and approach for alert correlation to be extensible, flexible, and modular. The architecture encompasses... 

Today’s biggest IoT companies are built on the extraction of insight from data of sensors, and data processing has become crucial in IoT businesses. Nevertheless, the size of data which should be processed is growing significantly fast. The pace of the data growing has changed the nature of data processing in IoT. Today, IoT industries demand highly scalable and fault tolerant data processing architectures which can handle the massive amount of data. In this research, we presented a distributed architecture for scalable and resilient data processing based on the Liquid which is a nearline and offline big data architecture. We used the Reactive Manifesto to design the architecture highly...