Community Seismic Network

The article describes the design of the Community Seismic Network, which is a dense open seismic network based on low cost sensors. The inputs are from sensors hosted by volunteers from the community by direct connection to their personal computers, or through sensors built into mobile devices. The server is cloud-based for robustness and to dynamically handle the load of impulsive earthquake events. The main product of the network is a map of peak acceleration, delivered within seconds of the ground shaking. The lateral variations in the level of shaking will be valuable to first responders, and the waveform information from a dense network will allow detailed mapping of the rupture process. Sensors in buildings may be useful for monitoring the state-of-health of the structure after major shaking

The PHENIX Experiment at RHIC

The physics emphases of the PHENIX collaboration and the design and current status of the PHENIX detector are discussed. The plan of the collaboration for making the most effective use of the available luminosity in the first years of RHIC operation is also presented.Comment: 5 pages, 1 figure. Further details of the PHENIX physics program available at http://www.rhic.bnl.gov/phenix

Toward a practical survivable intrusion tolerant replication system,”

Abstract-The increasing number of cyber attacks against critical infrastructures, which typically require large state and long system lifetimes, necessitates the design of systems that are able to work correctly even if part of them is compromised. We present the first practical survivable intrusion tolerant replication system, which defends across space and time using compiler-based diversity and proactive recovery, respectively. Our system supports large-state applications, and utilizes the Prime BFT protocol (providing performance guarantees under attack) with a compiler-based diversification engine. We devise a novel theoretical model that computes how resilient the system is over its lifetime based on the rejuvenation rate and the number of replicas. This model shows that we can achieve a confidence in the system of 95% over 30 years even when we transfer a state of 1 terabyte after each rejuvenation

DELF: Safeguarding deletion correctness in Online Social Networks

Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably occur. While developers are effective at identifying high-level deletion requirements in products (e.g., users should be able to delete posted photos), they are less effective at mapping high-level requirements into concrete operations (e.g., deleting all relevant items in data stores). Without framework support, developer mistakes lead to violations of users' privacy, such as retaining data that should be deleted, deleting the wrong data, and exploitable vulnerabilities.We propose DELF, a deletion framework for modem OSNs. In DELF, developers specify deletion annotations on data type definitions, which the framework maps into asynchronous, reliable and temporarily reversible operations on backing data stores. DELF validates annotations both statically and dynamically, proactively flagging errors and suggesting fixes.We deployed DELF in three distinct OSNs, showing the feasibility of our approach. DELF detected, surfaced, and helped developers correct thousands of omissions and dozens of mistakes, while also enabling timely recovery in tens of incidents where user data was inadvertently deleted