On protection in federated social computing systems

Nowadays, a user may belong to multiple social computing systems (SCSs) in order to benefit from a variety of services that each SCS may provide. To facilitate the sharing of contents across the system boundary, some SCSs provide a mechanism by which a user may “connect ” his accounts on two SCSs. The effect is that contents from one SCS can now be shared to another SCS. Although such a connection feature delivers clear usability advantages for users, it also generates a host of privacy challenges. A notable challenge is that the access control policy of the SCS from which the content originates may not be honoured by the SCS to which the content migrates, because the latter fails to faithfully replicate the protection model of the former. In this paper we formulate a protection model for a fed-eration of SCSs that support content sharing via account connection. A core feature of the model is that sharable con-tents are protected by access control policies that transcend system boundary — they are enforced even after contents are migrated from one SCS to another. To ensure faith-ful interpretation of access control policies, their evaluation involves querying the protection states of various SCSs, us-ing Secure Multiparty Computation (SMC). An important contribution of this work is that we carefully formulate the conditions under which policy evaluation using SMC does not lead to the leakage of information about the protection states of the SCSs. We also study the computational prob-lem of statically checking if an access control policy can be evaluated without information leakage. Lastly, we identify useful policy idioms

A Constant-Time Algorithm for Vector Field SLAM using an Exactly Sparse Extended Information Filter

Abstract — Designing a localization system for a low-cost robotic consumer product poses a major challenge. In previous work, we introduced Vector Field SLAM [5], a system for simultaneously estimating robot pose and a vector field induced by stationary signal sources present in the environment. In this paper we show how this method can be realized on a low-cost embedded processing unit by applying the concepts of the Exactly Sparse Extended Information Filter [15]. By restricting the set of active features to the 4 nodes of the current cell, the size of the map becomes linear in the area explored by the robot while the time for updating the state can be held constant under certain approximations. We report results from running our method on an ARM 7 embedded board with 64 kByte RAM controlling a Roomba 510 vacuum cleaner in a standard test environment. NS spot1 X (sensor units) Spot1 X readings Node X1 estimate

Graphene-based Josephson junction single photon detector

We propose to use graphene-based Josephson junctions (gJjs) to detect single photons in a wide electromagnetic spectrum from visible to radio frequencies. Our approach takes advantage of the exceptionally low electronic heat capacity of monolayer graphene and its constricted thermal conductance to its phonon degrees of freedom. Such a system could provide high sensitivity photon detection required for research areas including quantum information processing and radio-astronomy. As an example, we present our device concepts for gJj single photon detectors in both the microwave and infrared regimes. The dark count rate and intrinsic quantum efficiency are computed based on parameters from a measured gJj, demonstrating feasibility within existing technologies.Comment: 11 pages, 6 figures, and 1 table in the main tex