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An important security challenge is to protect the execution of security-sensitive code on legacy systems from malware that may infect the OS, applications, or system devices. Prior work experienced a tradeoff between the level of security achieved and efficiency. In this work, we leverage the features of modern processors from AMD and Intel to overcome the tradeoff to simultaneously achieve a high level of security and high performance.We present TrustVisor, a special-purpose hypervisor that provides code integrity as well as data integrity and secrecy for selected portions of an application. TrustVisor achieves a high level of security, first because it can protect sensitive code at a very fine granularity, and second because it has a very small code base (only around 6K lines of code) that makes verification feasible. TrustVisor can also attest the existence of isolated execution to an external entity. We have implemented TrustVisor to protect security-sensitive code blocks while imposing less than 7% overhead on the legacy OS and its applications in the common case.

Abstract-We argue that the traditional notion of trust as a relation among entities, while useful, becomes insufficient for emerging data-centric mobile ad hoc networks. In these systems, setting the data trust level equal to the trust level of the dataproviding entity would ignore system salient features, rendering applications ineffective and systems inflexible. This would be even more so if their operation is ephemeral, i.e., characterized by short-lived associations in volatile environments. In this paper, we address this challenge by extending the traditional notion of trust to data-centric trust: trustworthiness attributed to nodereported data per se. We propose a framework for data-centric trust establishment: First, trust in each individual piece of data is computed; then multiple, related but possibly contradictory, data are combined; finally, their validity is inferred by a decision component based on one of several evidence evaluation techniques. We consider and evaluate an instantiation of our framework in vehicular networks as a case study. Our simulation results show that our scheme is highly resilient to attackers and converges stably to the correct decision.

We study the diffusion of influence in random multiplex networks where links can be of r different types, and, for a given content (e.g., rumor, product, or political view), each link type is associated with a content-dependent parameter ci in [0,∞] that measures the relative bias type i links have in spreading this content. In this setting, we propose a linear threshold model of contagion where nodes switch state if their "perceived" proportion of active neighbors exceeds a threshold τ. Namely a node connected to mi active neighbors and ki-mi inactive neighbors via type i links will turn active if ∑cimi/∑ciki exceeds its threshold τ. Under this model, we obtain the condition, probability and expected size of global spreading events. Our results extend the existing work on complex contagions in several directions by (i) providing solutions for coupled random networks whose vertices are neither identical nor disjoint, (ii) highlighting the effect of content on the dynamics of complex contagions, and (iii) showing that content-dependent propagation over a multiplex network leads to a subtle relation between the giant vulnerable component of the graph and the global cascade condition that is not seen in the existing models in the literature.