Titlebook: Data and Applications Security and Privacy XXXI; 31st Annual IFIP WG Giovanni Livraga,Sencun Zhu Conference proceedings 2017 IFIP Internat

費(fèi)解

Competitor Information: Know Your Opponenttes of Online Social Networks users that utilizes such reported community-aware trending topics. Additionally, we provide an algorithmic methodology that alters an existing community-aware trending topic algorithm so that it can preserve the privacy of the involved users while still reporting topics with a satisfactory level of utility.

發(fā)炎

Communal

Cholagogue

Preventing Unauthorized Data Flowss to address this problem employ analysis techniques that keep track of all subject accesses to objects, and hence can be expensive. In this paper we show that for an unauthorized flow to exist in an access control matrix, a flow of length one must exist. Thus, to eliminate unauthorized flows, it is

transdermal

Object-Tagged RBAC Model for the Hadoop Ecosystemer and Apache Sentry are two predominant frameworks used to provide authorization capabilities in Hadoop ecosystem. In this paper we present a formal multi-layer access control model (called .) for Hadoop ecosystem, as an academic-style abstraction of Ranger, Sentry and native Apache Hadoop access-c

使痛苦

Identification of Access Control Policy Sentences from Natural Language Policy Documentsdels in the information security realm. However, attribute-based access control (ABAC) has been proposed as a general model that could overcome the limitations of the dominant access control models (i.e., role-based access control) while unifying their advantages. One issue with migrating to an ABAC

decode

Fast Distributed Evaluation of Stateful Attribute-Based Access Control Policies systems. This approach is popular in attribute-based access control (ABAC) systems and is embodied in the XACML standard. For this approach to be practical in an enterprise system, the access control decision engine must be scalable, able to quickly respond to access control requests from many conc

Mercurial

Gaussian Mixture Models for Classification and Hypothesis Tests Under Differential Privacy. When a data set contains sensitive information and cannot be directly released to users, such models can be easily constructed based on noise added query responses. The models nonetheless provide preliminary results to users. Although the queried basic statistics meet the differential privacy guar

Paleontology

Differentially Private K-Skyband Query Answering Through Adaptive Spatial Decompositionmportant type of multi-criteria analysis with diverse applications in practice. In this paper, we investigate techniques to answer .-skyband queries with differential privacy. We first propose a general technique ., which accepts any differentially private spatial decomposition tree as input and lev

多節(jié)

Mutually Private Location Proximity Detection with Access Controlels of service based on consumer classifications, sometimes without disclosing areas of interest (AOI) locations to all users. Both actors want to leverage location-based services utility without sacrificing privacy. We propose a protocol that supports queries from different classifications of users