VLDB 2026 Research / reviewers in the wild / expert
Junseung You
dblp:282/1124
· DBLP profile ↗
5ranked-venue papers
2as first author
5since 2021 · last 2026
0000-0003-1539-229XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 4 · 1 first-author · 4 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | SECV: Securing Connected Vehicles with Hardware Trust Anchors
Martin Kayondo, Junseung You, Eunmin Kim, Yunheung Paek |
NDSS | 2 |
| 2025 | BASTAG: Byte-level Access Control on Shared Memory using ARM Memory Tagging ExtensionabstractAs software grows in size and complexity, modular designs are increasingly adopted, leading to frequent interactions via shared memory between components. This design however increases the risk of vulnerabilities from uncontrolled memory access to shared memory. Enforcing byte-level access control can mitigate these risks by enabling byte-level permissions on complex shared objects and their sub-elements. However, existing approaches face performance limitations as they increase the granularity of control to byte level. In this paper, we present BASTAG, a novel system that leverages ARM's Memory Tagging Extension (MTE) to tack this challenge. Although MTE enforces tag-matching between pointers and memory, its hardware-defined granularity is too coarse to support byte-level control on its own. To address the inherent limitations of applying MTE for nuanced access control, BASTAG incorporates a technique known as shadow memory tagging that places separate, but associated MTE tags for the actual memory targets, allowing for more flexible and finer access control with efficiency. We implemented a BASTAG prototype on AArch64 hardware with MTE support and evaluated it on three real-world use cases. Our results demonstrate that BASTAG significantly outperforms existing byte-level access control mechanisms. Junseung You, Kyeongryong Lee, Yeongpil Cho, Yunheung Paek |
CCS | 1 |
| 2023 | Sfitag: Efficient Software Fault Isolation with Memory Tagging for ARM Kernel ExtensionsabstractAs ARM is becoming more popular in today’s processor market, the OS kernel on ARM is gradually bloated to meet the market demand for more sophisticated services by absorbing diverse kernel extensions. Since this kernel bloating inevitably increases the attack surface, there has been a continuous effort to decrease the surface by dissociating or isolating untrusted extensions from the kernel. One approach in this effort is using software fault isolation (SFI) that instruments memory and control-transfer instructions to prevent isolated extensions from having unauthorized accesses to memory regions of the core kernel. Being implementable in pure software has been considered the greatest strength of SFI and thus popularly adopted by engineers to isolate kernel extensions, but software versions of SFI mostly suffer from high performance overhead, which can be a critical drawback for performance-sensitive mobile devices that overwhelmingly use ARM CPUs. The purpose of our work, named as Sfitag, is to make SFI for ARM kernel extensions more efficient by leveraging the hardware support from the latest ARM AArch64 architecture, called the ARM8.5-A memory tagging extension (MTE). For efficiency, Sfitag relies on MTE support when it allocates a tag value different from the core kernel for untrusted extensions and enforces extensions to use that value as a tag for pointers and memory objects. Consequently, in Sfitag, accessing the core kernel memory is legitimate only when the tag of a pointer matches the value of the kernel tag, which by means of MTE in effect enables us to safely confine unexpected and buggy behaviors of extensions within the space isolated from the kernel. Through our evaluation, we prove the effectiveness of Sfitag by showing that our MTE-supported SFI efficiently enforces isolation for extensions just with 1% slowdown on the throughput of a network driver and 5.7% on a block device driver. Junseung You, Yungi Cho, Yeongpil Cho, Donghyun Kwon, Yunheung Paek |
AsiaCCS | 2 |
| 2023 | KVSEV: A Secure In-Memory Key-Value Store with Secure Encrypted VirtualizationabstractAMD's Secure Encrypted Virtualization (SEV) is a hardware-based Trusted Execution Environment (TEE) designed to secure tenants' data on the cloud, even against insider threats. The latest version of SEV, SEV-Secure Nested Paging (SEV-SNP), offers protection against most well-known attacks such as cold boot and hypervisor-based attacks. However, it remains susceptible to a specific type of attack known as Active DRAM Corruption (ADC), where attackers manipulate memory content using specially crafted memory devices. The in-memory key-value store (KVS) on SEV is a prime target for ADC attacks due to its critical role in cloud infrastructure and the predictability of its data structures. To counter this threat, we propose KVSEV, an in-memory KVS resilient to ADC attacks. KVSEV leverages SNP's Virtual Machine Management (VMM) and attestation mechanism to protect the integrity of key-value pairs, thereby securing the KVS from ADC attacks. Our evaluation shows that KVSEV secures in-memory KVSs on SEV with a performance overhead comparable to other secure in-memory KVS solutions. Junseung You, Kyeongryong Lee, Hyungon Moon, Yeongpil Cho, Yunheung Paek |
SoCC | 1 |
| 2023 | ZOMETAG: Zone-Based Memory Tagging for Fast, Deterministic Detection of Spatial Memory Violations on ARMabstractAgainst spatial memory violations threatening a vast amount of legacy software, various safety solutions have been suggested for decades. However, their practical uses have been impeded by diverse reasons, such as significant overheads and mandatory modifications of existing architectures. Accordingly, there has been a clear need for a practical safety solution that is fast enough and yet runs on commodity systems for its wide applicability in the field. As an effort to meet this need, a major processor vendor, ARM, recently announced a hardware extension, called Memory Tagging Extension (MTE), that helps engineers to implement efficient safety solutions. However, due to lack of hardware tags to isolate all data objects, MTE either resorts to a probabilistic memory safety guarantee, which is susceptible to a security loophole, or suffers from severe performance degradation to guarantee deterministic security. The aim of our work is to develop a MTE-based deterministic spatial safety solution, called ZOMETAG, with high efficiency by capitalizing on salient architectural features. Our key idea for fast, deterministic safety is to somehow assign permanently all objects unique tags throughout program execution. For this, ZOMETAG first divides the data memory into a number of small regions, called zones, and distributes data objects over the zones subject to certain constraints (to be discussed later). Then, we extend the notion of a tag in a way that each object stored with MTE tag$t$in zone$z$is uniquely assigned the zone-tag pair$z$,$t$> as a new tag. To work with this new tag assignment, we devise a novel mechanism, called two-layer isolation, that is basically a combination of MTE-based tagging (for one-layer of isolation) with zone-based tagging (for the other) both of which collaborate together to ensure spatial safety for all objects by preventing a pointer currently assigned one zone-tag pair from erroneously referring to objects assigned different pairs. Our experimental results are quite encouraging. ZOMETAG enforces deterministic spatial safety with overheads of 35% in SPEC CPU2006 and merely of 6% in real world applications like nginx. Junseung You, Donghyun Kwon, Yeongpil Cho, Yunheung Paek |
IEEE Trans. Inf. Forensics Secur. | 2 |