| Title | Toward Resilient Stream Processing on Clouds Using Moving Target Defense |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Chaturvedi, Shilpa, Simmhan, Yogesh |
| Conference Name | 2019 IEEE 22nd International Symposium on Real-Time Distributed Computing (ISORC) |
| Date Published | may |
| Keywords | Apache Storm, Big Data, Big Data platforms, canonical distributed stream processing platform, cloud computing, clouds, distributed clusters, Distributed databases, Fast Data platforms, Metrics, moving target defense, MTD, operating system, Payloads, pubcrawl, real-time stream processing, Real-time Systems, resilience, Resiliency, resilient stream processing, Runtime, Scalability, security of data, sensitive streaming applications, shared computing resources, Storms, Task Analysis, virtual machine, virtual machines |
| Abstract | Big data platforms have grown popular for real-time stream processing on distributed clusters and clouds. However, execution of sensitive streaming applications on shared computing resources increases their vulnerabilities, and may lead to data leaks and injection of spurious logic that can compromise these applications. Here, we adopt Moving Target Defense (MTD) techniques into Fast Data platforms, and propose MTD strategies by which we can mitigate these attacks. Our strategies target the platform, application and data layers, which make these reusable, rather than the OS, virtual machine, or hardware layers, which are environment specific. We use Apache Storm as the canonical distributed stream processing platform for designing our MTD strategies, and offer a preliminary evaluation that indicates the feasibility and evaluates the performance overheads. |
| DOI | 10.1109/ISORC.2019.00035 |
| Citation Key | chaturvedi_toward_2019 |
Toward Resilient Stream Processing on Clouds Using Moving Target Defense