21 citations · 103 across the 21 of their papers we have counts for
22 papers
HE-Guardrail: A Homomorphic Guardrail Against Jailbreak Attacks for Encrypted Large Language Model Inference
Byeongseo Min, Yongwoo Lee, Young-Sik Kim +1
Homomorphic encryption (HE) has emerged as a promising approach to privacy-preserving machine learning (PPML), enabling computation directly over encrypted data. In HE-based PPML,…
CGF-Softmax: A Cumulant-Based Softmax Reformulation for Efficient Inference under Homomorphic Encryption
Hanjun Park, Byeongseo Min, Jiheon Woo +5
Homomorphic encryption (HE) is a prominent framework for privacy-preserving machine learning, enabling inference directly on encrypted data. However, evaluating softmax, a core com…
Mutual Information Minimization for Side-Channel Attack Resistance via Optimal Noise Injection
Jiheon Woo, Donggyun Ryu, Daewon Seo +4
Side-channel attacks (SCAs) pose a serious threat to system security by extracting secret keys through physical leakages such as power consumption, timing variations, and electroma…
A Context-Aware CEO Problem
Daewon Seo, Sung Hoon Lim, Yongjune Kim
In many sensor network applications, a fusion center often has additional valuable information, such as context data, which cannot be obtained directly from the sensors. Motivated…
How to Mask in Error Correction Code Transformer: Systematic and Double Masking
Seong-Joon Park, Hee-Youl Kwak, Sang-Hyo Kim +3
In communication and storage systems, error correction codes (ECCs) are pivotal in ensuring data reliability. As deep learning's applicability has broadened across diverse domains,…
Information and Energy Transmission with Wavelet-Reconstructed Harvesting Functions
Daewon Seo, Yongjune Kim
In practical simultaneous information and energy transmission (SIET), the exact energy harvesting function is usually unavailable because an energy harvesting circuit is nonlinear…
Communication-Efficient and Drift-Robust Federated Learning via Elastic Net
Seonhyeong Kim, Jiheon Woo, Daewon Seo +1
Federated learning (FL) is a distributed method to train a global model over a set of local clients while keeping data localized. It reduces the risks of privacy and security but f…
Generalized LRS Estimator for Min-entropy Estimation
Jiheon Woo, Chanhee Yoo, Young-Sik Kim +2
The min-entropy is a widely used metric to quantify the randomness of generated random numbers, which measures the difficulty of guessing the most likely output. It is difficult to…
On the Efficient Estimation of Min-Entropy
Yongjune Kim, Cyril Guyot, Young-Sik Kim
The min-entropy is a widely used metric to quantify the randomness of generated random numbers in cryptographic applications; it measures the difficulty of guessing the most likely…
Optimizing the Write Fidelity of MRAMs
Yongjune Kim, Yoocharn Jeon, Cyril Guyot +1
Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs si…
Boosting Classifiers with Noisy Inference
Yongjune Kim, Yuval Cassuto, Lav R. Varshney
We present a principled framework to address resource allocation for realizing boosting algorithms on substrates with communication or computation noise. Boosting classifiers (e.g.…
On the Optimal Refresh Power Allocation for Energy-Efficient Memories
Yongjune Kim, Won Ho Choi, Cyril Guyot +1
Refresh is an important operation to prevent loss of data in dynamic random-access memory (DRAM). However, frequent refresh operations incur considerable power consumption and degr…
Redundancy allocation in finite-length nested codes for nonvolatile memories
Yongjune Kim, B. V. K. Vijaya Kumar
In this paper, we investigate the optimum way to allocate redundancy of finite-length nested codes for modern nonvolatile memories suffering from both permanent defects and transie…
Generalized Water-filling for Source-aware Energy-efficient SRAMs
Yongjune Kim, Mingu Kang, Lav R. Varshney +1
Conventional low-power static random access memories (SRAMs) reduce read energy by decreasing the bit-line voltage swings uniformly across the bit-line columns. This is because the…
Duality between erasures and defects
Yongjune Kim, B. V. K. Vijaya Kumar
We investigate the duality of the binary erasure channel (BEC) and the binary defect channel (BDC). This duality holds for channel capacities, capacity achieving schemes, minimum d…
Locally rewritable codes for resistive memories
Yongjune Kim, Abhishek A. Sharma, Robert Mateescu +4
We propose locally rewritable codes (LWC) for resistive memories inspired by locally repairable codes (LRC) for distributed storage systems. Small values of repair locality of LRC…
Writing on dirty flash memory
Yongjune Kim, B. V. K. Vijaya Kumar
The most important challenge in the scaling down of flash memory is its increased inter-cell interference (ICI). If side information about ICI is known to the encoder, the flash me…
Coding scheme for 3D vertical flash memory
Yongjune Kim, Robert Mateescu, Seung-Hwan Song +2
Recently introduced 3D vertical flash memory is expected to be a disruptive technology since it overcomes scaling challenges of conventional 2D planar flash memory by stacking up c…
On the Duality of Erasures and Defects
Yongjune Kim, B V K Vijaya Kumar
In this paper, the duality of erasures and defects will be investigated by comparing the binary erasure channel (BEC) and the binary defect channel (BDC). The duality holds for cha…
Redundancy Allocation of Partitioned Linear Block Codes
Yongjune Kim, B. V. K. Vijaya Kumar
Most memories suffer from both permanent defects and intermittent random errors. The partitioned linear block codes (PLBC) were proposed by Heegard to efficiently mask stuck-at def…
Coding for Memory with Stuck-at Defects
Yongjune Kim, B. V. K. Vijaya Kumar
In this paper, we propose an encoding scheme for partitioned linear block codes (PLBC) which mask the stuck-at defects in memories. In addition, we derive an upper bound and the es…
Modulation Coding for Flash Memories
Yongjune Kim, Kyoung Lae Cho, Hongrak Son +4
The aggressive scaling down of flash memories has threatened data reliability since the scaling down of cell sizes gives rise to more serious degradation mechanisms such as cell-to…