We propose SigFree, an online signature-free out-of-the-box application-layer method for blocking code-injection buffer overflow attack messages targeting at various Internet services such as Web service. Motivated by the observation that buffer overflow attacks typically contain executables whereas legitimate client requests never contain executables in most Internet services, SigFree blocks attacks by detecting the presence of code. Unlike the previous code detection algorithms, SigFree uses a new data-flow analysis technique called code abstraction that is generic, fast, and hard for exploit code to evade. SigFree is signature free, thus it can block new and unknown buffer overflow attacks; SigFree is also immunized from most attack-side code obfuscation methods. Since SigFree is a transparent deployment to the servers being protected, it is good for economical Internet-wide deployment with very low deployment and maintenance cost. We implemented and tested SigFree; our experimental study shows that the dependency-degree-based SigFree could block all types of code-injection attack packets (above 750) tested in our experiments with very few false positives. Moreover, SigFree causes very small extra latency to normal client requests when some requests contain exploit code.

Today, many applications require users from one organization to access data belonging to organizations. While traditional solutions offered for the federated and mediated databases facilitate this by sharing metadata, this may not be acceptable for certain organizations due to privacy concerns. In this paper, we propose a novel solution -- Privacy-preserving Access Control Toolkit (PACT) -- that enables privacy-preserving secure semantic access control and allows sharing of data among heterogeneous databases without having to share metadata. PACT uses encrypted ontologies, encrypted ontology-mapping tables and conversion functions, encrypted role hierarchies and encrypted queries. The encrypted results of queries are sent directly from the responding system to the requesting system, bypassing the mediator to further improve the security of the system. PACT provides semantic access control using ontologies and semantically expanded authorization tables at the mediator. One of the distinguishing features of the PACT is that it requires very little changes to underlying databases. Despite using encrypted queries and encrypted mediation, we demonstrate that PACT provides acceptable performance.

Sharing information across different organizations is a critical problem. Using security enforcement mechanisms, accessing databases is limited to authorized users only. However, if databases and access control policies are syntactically and schematically heterogeneous, information interoperation becomes a crucial challenge. In order to allow users from multiple organizations to access databases, a better access control model is desired. In this paper, we propose Semantic Access Control based on popular Role-Base Access Control. Semantic Access Control provides secure access control to databases while resolving the heterogeneity among the databases. We present Semantic Access Control Enabler (SACE), a novel middleware-based system that has been designed and implemented to enable Semantic Access Control on the Web. SACE is a middleware system that requires only a few changes to be done on the legacy systems of any organizations involved. Unlike traditional mediator technologies, we integrate heterogeneity resolution and access control into one process. We show that despite performing ontology mappings and query and data translations our toolkit still provides acceptable performance.

This paper proposes a novel path planning algorithm of 3-D articulated robots with moving bases based on a generalized potential field model. The approach computes, similar to that done in electrostatics, repulsive force and torque between charged objects. A collision-free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these force and torque. The proposed approach is efficient since these potential gradients are analytically tractable. In order to speedup the computation, a sequential planning strategy is adopted. Simulation results show that the proposed algorithm works well, in terms of collision avoidance and computation efficiency.