[hpc-announce] CFP for S-HPC 2022:: The First Annual Workshop on Cyber Security in High Performance @ SC22
Joseph B Manzano
josbry27 at gmail.com
Wed Jun 15 16:47:50 CDT 2022
First Annual Workshop on Cyber Security in High Performance
November 18, 2022
Dallas, Texas, USA.
Held in conjunction with the International Conference for High Performance
Computing, Networking, Storage and Analysis (SC22), Nov 13-18, 2022,
Dallas, Texas, USA.
Paper Submission: August 5th 2022
Security in High-Performance Computing (HPC) has traditionally been an
"operational" challenge (i.e., restrict access and usage to certified users).
However, as HPC gradually permeates more areas of public interest, the
traditional focus of HPC only on performance might expose attack surfaces to
an ever growing body of users. Paired with HPC?s traditional role of early
technology adoption, a new set of early target-worthwhile vulnerabilities are
emerging that are not necessarily found in other computing scenarios that
operate with more established technologies.
In addition to early adoption vulnerabilities, potential vulnerabilities
specific to the HPC community arise from acute hardware heterogeneity, novel
networks technologies/topologies, massive resource management orchestration --
including power consumption, heavy reliance on open software, brittle
experimental software not hardened by numerous deployments and dusty deck
software with a lack of maintenance. In combination with the commercial,
single-node exploits, these vulnerabilities open fertile new attack surfaces.
This workshop focuses on threats and solutions across the HPC hardware/software
stack. These threats include weaknesses in current and future architectural
designs, escalation of privileges through data extraction or computation
manipulation and intentional misuse of resources across scientific instruments
feeding HPC machines.
This workshop will focus on the topics listed below. However, this list is due
to grow thanks to the interactions and discoveries presented in the workshop.
* Trade-offs between system functionality (i.e., performance, energy, etc.),
cybersecurity and confidentiality.
* Privacy/ confidentiality preserving workflows and their implication on
High Performance Computing.
* Approaches to evaluate data and system trustworthiness for HPC workflows.
* Approaches to embedding security features across the computing sensor
platforms, network elements, and other components part of the HPC
* Techniques to find Attack Surfaces in HPC systems, data feeding instruments,
and scientific sensors.
* Artificial Intelligence in cybersecurity and privacy: methodologies to
evaluate the impact of AI and identifying potential risks.
* Machine Learning techniques applied to cybersecurity and privacy in terms of
HPC workloads and HPC co-design.
* Security Enhanced prescriptive programming of HPC system.
* New attacks targeting HPC systems or components.
Full submission will be 8 pages long using the same format as the SC22
conference (i.e., using the IEEE conference template). All submitted papers
will undergo a rigorous review process and each will have at least three
reviews by members of the program committee. Papers will be accepted based on
their technical contributions. Submission will be made through SC submission
site through Linking (https://submissions.supercomputing.org/. )
Accepted papers will be published with the IEEE Computer Society in the IEEE
Xplore Digital Library. At least one author of an accepted paper must
register for and present the paper at the workshop (in-person live, remote
live or pre-recorded video):
* Paper Submission: August 5th, 2022
* Paper Notification: September 7th, 2022
* Final Paper Due: October 10th, 2022
* Andres Marquez, Pacific Northwest National Laboratory
* Haipeng Cai, Washington State University
* Jim Basney, University of Illinois
* Kevin J. Baker, Pacific Northwest National Laboratory
* Sean Peisert, Lawrence Berkeley National Laboratory
* Nael B Abhu-Ghazaleh, University of California Riverside
* Cimone Wright-Hamor, Pacific Northwest National Laboratory
* Alexa Leal, University of Texas at Arlington
* Joseph Manzano, Pacific Northwest National Laboratory
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