Demo Data from SIGIR 2026 / reviewers in the wild / expert
Mazhar Naqvi
dblp:201/4800
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 77% Cloud and datacenter computing · 23% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › storage performance
low-latency storage |
0.3 | 1 | 2018 | Splinter: Bare-Metal Extensions for Multi-Tenant Low-Latency Storage · OSDI 2018 |
Cloud and datacenter computing › multi-tenancy
multi-tenant storage |
0.1 | 1 | 2018 | Splinter: Bare-Metal Extensions for Multi-Tenant Low-Latency Storage · OSDI 2018 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Splinter: Bare-Metal Extensions for Multi-Tenant Low-Latency Storage
Chinmay Kulkarni 0002, Sara Moore, Mazhar Naqvi, Tian Zhang 0005, Robert Ricci, Ryan Stutsman |
OSDI | 3 |
| 2017 | An Anomaly Detection Fabric for Clouds Based on Collaborative VM CommunitiesabstractThe vast attack surface of clouds presents a challenge in deploying scalable and effective defenses. Traditional security mechanisms, which work from inside the VM fail to provide strong protection as attackers can bypass them easily. The only available option is to provide security from the layer below the VM i.e., the hypervisor. Previous works that attempt to secure VMs from "outside" either incur substantial space or compute overheads making them slow and impractical or require modifications to the OS or the application codebase. To address these issues, we propose an anomaly detection fabric for clouds based on system call monitoring, which compresses the stream of system calls at their source making the system scalable and near real-time. Our system requires no modifications to the guest OS or the application making it ideal for the data center setting. Additionally, for robust and early detection of threats, we leverage the notion of VM/container communities that share information about attacks in their early stages to provide immunity to the entire deployment. We make certain aspects of the system flexible so that vendors can tune metrics to offer customized protection to clients based on their workload types. Detailed evaluation on a prototype implementation on KVM substantiates our claims. Rashid Tahir, Matthew Caesar 0001, Ali Raza 0003, Mazhar Naqvi, Fareed Zaffar |
CCGrid | 4 |