Modelling the role of software in the propagation of failure across National Critical Infrastructures
Previous terrorist attacks, system failures and natural disasters have revealed the problems that many States face in preparing for national civil contingencies. The diversity of critical infrastructures and the interconnections between different systems makes it difficult for planners to ‘think of everything’. For example, the loss of power distribution networks can disrupt rail and road transportation systems. Knock-on effects can also be felt across telecommunications infrastructures as the uninterruptible power supplies (UPS’) that protect mobile phone base stations fail over time. Domestic water supplies are affected when pumping and treatment centres lose power. It is difficult to under-estimate the safety implications of these interdependencies. For example, Pironi, Spinucci and Paganelli describe how the Italian blackout of 2003 affected patients that relied on home parenteral nutrition systems [1]. These individuals used electronic pumps for the overnight infusion of nutritional solutions. The loss of power disrupted their treatment. Different devices responded in different ways as some began to generate alarms while others reverted to battery power. Patients responded in different ways as they became worried about whether or not their systems had sufficient power to complete their treatment for that night. The blackout lasted several days across many areas of Italy. This created further problems as stores of parenteral solution had to be stored in freezers. Other patients were placed at risk when the loss of power began to affect water treatment centres. It became difficult to guarantee that there was no microbiological or toxic contamination in the water supplies for dialysis patients.
Computational Support for Identifying Safety and Security Related Dependencies between National Critical Infrastructures
Previous terrorist attacks, system failures and natural disasters have revealed the problems that many States face in preparing for national civil contingencies. The diversity of critical infrastructures and the interconnections between different systems makes it difficult for planners to 'think of everything'. For example, the loss of power distribution networks can disrupt rail and road transportation systems. Knock-on effects can also be felt across telecommunications infrastructures as the uninterruptible power supplies (UPS') that protect Internet routers and mobile phone base stations fail over time. Domestic water supplies are affected when pumping and treatment centres lose power. These interconnections make it hard to anticipate the many different safety-related systems that might be affected by particular contingencies. This paper introduces a Geographic Information System that is intended to help government agencies plan for the knock-on effects that propagate between major infrastructures. The intention is to provide a flexible system, which can easily be configured and updated. This is important given that technical innovation and routine maintenance continually introduce changes across national infrastructures. (6 pages)
Public policy and the failure of national infrastructures
On the 14 August 2003, a complex combination of immediate events and longer term vulnerabilities led to a domino effect in which 50 million people had their power supplies interrupted. Consequent losses were between $5–$10 billion. It is, therefore, one of the most serious disruptions to a national power distribution network. The causes included technical issues to do with network capacity and the algorithms used to predict potential distribution problems. It also had managerial and human factors causes; these arguably included an over-reliance on automated monitoring systems. The infrastructure failure also stemmed from governmental and regulatory intervention in the operation of the energy markets. The following paper applies accident investigation techniques to represent and reason about the complex interactions between these causes. In particular, we use Violation and Vulnerability (V2) diagrams to map out arguments for and against market deregulation as a causal factor in engineering failures.