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12 March 2019

·        A. Abhishta

Title: Measuring the Economic Impact of DDoS Attacks 

Abstract: Today every firm relies on the Internet for carrying out its day to day functions. Availability of the Internet and the services based on it are of great importance to the organizations. This provides attackers with an economic incentive to target firms with cyber attacks that can cause IT unavailability.  One such attack that can significantly reduce the reliability of network services and leave them inaccessible for the intended users is Distributed Denial of Service (DDoS) attacks. Firms can potentially experience heavy losses due to unavailability of IT systems. But resilience (partial) of organisations against unavailability makes it tricky to estimate the economic loses. In this presentation, I discuss strategies to measure the economic impact of DDoS attacks on public and private firms. 



·       Martijn Koot

Title: Real-time ICT for Resilient Logistics Planning 

Abstract: Supply chain decision making heavily relies on the application of well-analyzed data, especially in the field of logistics planning and control. Over the years, techniques from Operations Research and Computer Science enabled managers to make better-informed logistics decisions. However, it remains difficult to construct efficient and resilient plans for dynamic and uncertain environments. Current decision-support tools are data intensive and irregularly applied, while detection of disruptions should constantly rely on data obtained from actual business executions. The planning complexity aggravates even further because collaboration between logistics service providers is required more often in a highly fragmented market characterized by single-enterprise IT infrastructures supporting decision-making. Therefore, the question arises how the detection of daily disruptions can be included within the decision support tools to improve both resilience and efficiency of real-time logistic planning and control. The increasing number of tracking and monitoring devices provide the opportunity to monitor business performances constantly. Therefore, this research aims at advancing the extant logistics knowledge with novel Internet of Things (IoT) and Big Data solutions. The real-time analysis of large data sets and real-time sensor information will be used to improve the logistics planning, monitoring, and quality control. The main vision is to develop autonomous software agents empowered by Artificial Logistical Intelligence (ALI) to support human planners during both operational and tactical decision-making.