Secure and efficient application monitoring and replication

Memory corruption vulnerabilities remain a grave threat to systems software written in C/C++. Current best practices dictate compiling programs with exploit mitigations such as stack canaries, address space layout randomization, and control-flow integrity. However, adversaries quickly find ways to circumvent such mitigations, sometimes even before these mitigations are widely deployed. In this paper, we focus on an "orthogonal" defense that amplifies the effectiveness of traditional exploit mitigations. The key idea is to create multiple diversified replicas of a vulnerable program and then execute these replicas in lockstep on identical inputs while simultaneously monitoring their behavior. A malicious input that causes the diversified replicas to diverge in their behavior will be detected by the monitor; this allows discovery of previously unknown attacks such as zero-day exploits. So far, such multi-variant execution environments (MVEEs) have been held back by substantial runtime overheads. This paper presents a new design, ReMon, that is non-intrusive, secure, and highly efficient. Whereas previous schemes either monitor every system call or none at all, our system enforces cross-checking only for security critical system calls while supporting more relaxed monitoring policies for system calls that are not security critical. We achieve this by splitting the monitoring and replication logic into an in-process component and a cross-process component. Our evaluation shows that ReMon offers same level of security as conservative MVEEs and run realistic server benchmarks at near-native speeds

Parallel netCDF: A Scientific High-Performance I/O Interface

Dataset storage, exchange, and access play a critical role in scientific applications. For such purposes netCDF serves as a portable and efficient file format and programming interface, which is popular in numerous scientific application domains. However, the original interface does not provide an efficient mechanism for parallel data storage and access. In this work, we present a new parallel interface for writing and reading netCDF datasets. This interface is derived with minimum changes from the serial netCDF interface but defines semantics for parallel access and is tailored for high performance. The underlying parallel I/O is achieved through MPI-IO, allowing for dramatic performance gains through the use of collective I/O optimizations. We compare the implementation strategies with HDF5 and analyze both. Our tests indicate programming convenience and significant I/O performance improvement with this parallel netCDF interface.Comment: 10 pages,7 figure