No abstract

An incessant rhythm of data breaches, data leaks, and privacy exposure highlights the need to improve control over potentially sensitive data. History has shown that neither public nor private sector organizations are immune. Lax data handling, incidental leakage, and adversarial breaches are all contributing factors. Prudent organizations should consider the sensitive nature of network security data. Logged events often contain data elements that are directly correlated with sensitive information about people and their activities-often at the same level of detail as sensor data. Our intent is to produce a database which holds network security data representative of people's interaction with the network mid-points and end-points without the problems of identifiability. In this paper we discuss architectures and propose a system design that supports a risk based approach to privacy preserving data publication of network security data that enables network security data analytics research.

In this paper we document our approach to overcoming service discovery and con guration of Apache Hadoop and Spark frameworks with dynamic resource allocations in a batch oriented Advanced Research Computing (ARC) High Performance Computing (HPC) environment. ARC e orts have produced a wide variety of HPC architectures. A common HPC architectural pa ern is multi-node compute clusters with low-latency, high-performance interconnect fabrics and shared central storage. is pa ern enables processing of workloads with high data co-dependency, frequently solved with message passing interface (MPI) programming models, and then executed as batch jobs. Unfortunately, many HPC programming paradigms are not well suited to big data workloads which are o en easily separable. Our approach lowers barriers of entry to HPC environments by enabling end users to utilize Apache Hadoop and Spark frameworks that support big data oriented programming paradigms appropriate for separable workloads in batch oriented HPC environments. CCS CONCEPTS •Information systems → Computing platforms; Nearest-neighbor search; •So ware and its engineering → So ware as a service orchestration system;