Zobrazeno 1 - 10
of 1 028
pro vyhledávání: '"Kim, TaeSoo"'
Autor:
Liu, Mingyi, Huh, Jun Ho, Han, HyungSeok, Lee, Jaehyuk, Ahn, Jihae, Li, Frank, Kim, Hyoungshick, Kim, Taesoo
Decentralized Finance (DeFi) offers a whole new investment experience and has quickly emerged as an enticing alternative to Centralized Finance (CeFi). Rapidly growing market size and active users, however, have also made DeFi a lucrative target for
Externí odkaz:
http://arxiv.org/abs/2406.15709
Autor:
Kim, Juhee, Park, Jinbum, Roh, Sihyeon, Chung, Jaeyoung, Lee, Youngjoo, Kim, Taesoo, Lee, Byoungyoung
ARM Memory Tagging Extension (MTE) is a new hardware feature introduced in ARMv8.5-A architecture, aiming to detect memory corruption vulnerabilities. The low overhead of MTE makes it an attractive solution to mitigate memory corruption attacks in mo
Externí odkaz:
http://arxiv.org/abs/2406.08719
Caches on the modern commodity CPUs have become one of the major sources of side-channel leakages and been abused as a new attack vector. To thwart the cache-based side-channel attacks, two types of countermeasures have been proposed: detection-based
Externí odkaz:
http://arxiv.org/abs/2402.15425
Autor:
Guan, Mingyu, Stokes, Jack W., Luo, Qinlong, Liu, Fuchen, Mehta, Purvanshi, Nouri, Elnaz, Kim, Taesoo
The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs) since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, existing methods ignore a tree hierarchy among met
Externí odkaz:
http://arxiv.org/abs/2402.13496
Autor:
Jeon, Hyeonjae, Seo, Junghyun, Kim, Taesoo, Son, Sungho, Lee, Jungki, Choi, Gyeungho, Lim, Yongseob
Autonomous driving technology nowadays targets to level 4 or beyond, but the researchers are faced with some limitations for developing reliable driving algorithms in diverse challenges. To promote the autonomous vehicles to spread widely, it is impo
Externí odkaz:
http://arxiv.org/abs/2401.00460
Trustworthiness of generative language models (GLMs) is crucial in their deployment to critical decision making systems. Hence, certified risk control methods such as selective prediction and conformal prediction have been applied to mitigating the h
Externí odkaz:
http://arxiv.org/abs/2307.09254
Contrastive learning, along with its variations, has been a highly effective self-supervised learning method across diverse domains. Contrastive learning measures the distance between representations using cosine similarity and uses cross-entropy for
Externí odkaz:
http://arxiv.org/abs/2306.11526
Recently, deep learning models have shown the potential to predict breast cancer risk and enable targeted screening strategies, but current models do not consider the change in the breast over time. In this paper, we present a new method, PRIME+, for
Externí odkaz:
http://arxiv.org/abs/2303.15699
Fuzzing has gained in popularity for software vulnerability detection by virtue of the tremendous effort to develop a diverse set of fuzzers. Thanks to various fuzzing techniques, most of the fuzzers have been able to demonstrate great performance on
Externí odkaz:
http://arxiv.org/abs/2302.12879
Blockchains with smart contracts are distributed ledger systems that achieve block-state consistency among distributed nodes by only allowing deterministic operations of smart contracts. However, the power of smart contracts is enabled by interacting
Externí odkaz:
http://arxiv.org/abs/2211.09330