arXiv subjects

Howon Kim

Publications and source records attributed to Howon Kim.

At least 19 recordsLinked to original sources

arXiv2025

MECHA: Multithreaded and Efficient Cryptographic Hardware Access

This paper presents a multithread and efficient cryptographic hardware access (MECHA) for efficient and fast cryptographic operations that eliminates the need for context switching. Utilizing a UNIX domain socket, MECHA manages multiple requests from multiple applications simultaneously, resulting in faster processing and improved efficiency. We comprise several key components, including the Server thread, Client thread, Transceiver thread, and a pair of Sender and Receiver queues. MECHA design is portable and can be used with any communication protocol, with experimental results demonstrating a 83% increase in the speed of concurrent cryptographic requests compared to conventional interface design. MECHA architecture has significant potential in the field of secure communication applications ranging from cloud computing to the IoT, offering a faster and more efficient solution for managing multiple cryptographic operation requests concurrently.

cs.CR↗

arXiv2024

Cityscape-Adverse: Benchmarking Robustness of Semantic Segmentation with Realistic Scene Modifications via Diffusion-Based Image Editing

Recent advancements in generative AI, particularly diffusion-based image editing, have enabled the transformation of images into highly realistic scenes using only text instructions. This technology offers significant potential for generating diverse synthetic datasets to evaluate model robustness. In this paper, we introduce Cityscape-Adverse, a benchmark that employs diffusion-based image editing to simulate eight adverse conditions, including variations in weather, lighting, and seasons, while preserving the original semantic labels. We evaluate the reliability of diffusion-based models in generating realistic scene modifications and assess the performance of state-of-the-art CNN and Transformer-based semantic segmentation models under these challenging conditions. Additionally, we analyze which modifications have the greatest impact on model performance and explore how training on synthetic datasets can improve robustness in real-world adverse scenarios. Our results demonstrate that all tested models, particularly CNN-based architectures, experienced significant performance degradation under extreme conditions, while Transformer-based models exhibited greater resilience. We verify that models trained on Cityscape-Adverse show significantly enhanced resilience when applied to unseen domains. Code and datasets will be released at https://github.com/naufalso/cityscape-adverse.

cs.CV↗

arXiv2024

Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch Attack

Monocular depth estimation (MDE) and semantic segmentation (SS) are crucial for the navigation and environmental interpretation of many autonomous driving systems. However, their vulnerability to practical adversarial attacks is a significant concern. This paper presents a novel adversarial attack using practical patches that mimic manhole covers to deceive MDE and SS models. The goal is to cause these systems to misinterpret scenes, leading to false detections of near obstacles or non-passable objects. We use Depth Planar Mapping to precisely position these patches on road surfaces, enhancing the attack's effectiveness. Our experiments show that these adversarial patches cause a 43% relative error in MDE and achieve a 96% attack success rate in SS. These patches create affected error regions over twice their size in MDE and approximately equal to their size in SS. Our studies also confirm the patch's effectiveness in physical simulations, the adaptability of the patches across different target models, and the effectiveness of our proposed modules, highlighting their practical implications.

cs.CV↗

arXiv2024

CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher

Penetration testing, a critical component of cybersecurity, typically requires extensive time and effort to find vulnerabilities. Beginners in this field often benefit from collaborative approaches with the community or experts. To address this, we develop CIPHER (Cybersecurity Intelligent Penetration-testing Helper for Ethical Researchers), a large language model specifically trained to assist in penetration testing tasks. We trained CIPHER using over 300 high-quality write-ups of vulnerable machines, hacking techniques, and documentation of open-source penetration testing tools. Additionally, we introduced the Findings, Action, Reasoning, and Results (FARR) Flow augmentation, a novel method to augment penetration testing write-ups to establish a fully automated pentesting simulation benchmark tailored for large language models. This approach fills a significant gap in traditional cybersecurity Q\&A benchmarks and provides a realistic and rigorous standard for evaluating AI's technical knowledge, reasoning capabilities, and practical utility in dynamic penetration testing scenarios. In our assessments, CIPHER achieved the best overall performance in providing accurate suggestion responses compared to other open-source penetration testing models of similar size and even larger state-of-the-art models like Llama 3 70B and Qwen1.5 72B Chat, particularly on insane difficulty machine setups. This demonstrates that the current capabilities of general LLMs are insufficient for effectively guiding users through the penetration testing process. We also discuss the potential for improvement through scaling and the development of better benchmarks using FARR Flow augmentation results. Our benchmark will be released publicly at https://github.com/ibndias/CIPHER.

cs.CR↗

arXiv2024

High-resolution spectroscopy of proximity superconductivity in finite-size quantized surface states

Adding superconducting (SC) electron pairing via the proximity effect to pristinely non-superconducting materials can lead to a variety of interesting physical phenomena. Particular interest has recently focused on inducing SC into two-dimensional surface states (SSs), potentially also combined with non-trivial topology. We study the mechanism of proximity-induced SC into the Shockley-type SSs of the noble metals Ag(111) and Cu(111) grown on the elemental SC Nb(110) using scanning tunneling spectroscopy. The tunneling spectra exhibit an intriguing multitude of sharp states at low energies. Their appearance can be explained by Andreev bound states (ABS) formed by the weakly proximitized SSs subject to lateral finite-size confinement. We study systematically how the proximity gap in the bulk states of both Ag(111) and Cu(111) persists up to island thicknesses of several times the bulk coherence length of Nb. We find that even for thick islands, the SSs acquire a gap, with the gap size for Cu being consistently larger than for Ag. Based on this, we argue that the SC in the SS is not provided through direct overlap of the SS wavefunction with the SC host but can be understood to be mediated by step edges inducing electronic coupling to the bulk. Our work provides important input for the microscopic understanding of induced superconductivity in heterostructures and its spectral manifestation. Moreover, it lays the foundation for more complex SC heterostructures based on noble metals.

cond-mat.supr-con↗

arXiv2023

Behind The Wings: The Case of Reverse Engineering and Drone Hijacking in DJI Enhanced Wi-Fi Protocol

This research paper entails an examination of the Enhanced Wi-Fi protocol, focusing on its control command reverse-engineering analysis and subsequent demonstration of a hijacking attack. Our investigation discovered vulnerabilities in the Enhanced Wi-Fi control commands, rendering them susceptible to hijacking attacks. Notably, the study established that even readily available and cost-effective commercial off-the-shelf Wi-Fi routers could be leveraged as effective tools for executing such attacks. To illustrate this vulnerability, a proof-of-concept remote hijacking attack was carried out on a DJI Mini SE drone, whereby we intercepted the control commands to manipulate the drone's flight trajectory. The findings of this research emphasize the critical necessity of implementing robust security measures to safeguard unmanned aerial vehicles against potential hijacking threats. Considering that civilian drones are now used as war weapons, the study underscores the urgent need for further exploration and advancement in the domain of civilian drone security.

cs.CR↗

arXiv2023

ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion

Adversarial camouflage has garnered attention for its ability to attack object detectors from any viewpoint by covering the entire object's surface. However, universality and robustness in existing methods often fall short as the transferability aspect is often overlooked, thus restricting their application only to a specific target with limited performance. To address these challenges, we present Adversarial Camouflage for Transferable and Intensive Vehicle Evasion (ACTIVE), a state-of-the-art physical camouflage attack framework designed to generate universal and robust adversarial camouflage capable of concealing any 3D vehicle from detectors. Our framework incorporates innovative techniques to enhance universality and robustness, including a refined texture rendering that enables common texture application to different vehicles without being constrained to a specific texture map, a novel stealth loss that renders the vehicle undetectable, and a smooth and camouflage loss to enhance the naturalness of the adversarial camouflage. Our extensive experiments on 15 different models show that ACTIVE consistently outperforms existing works on various public detectors, including the latest YOLOv7. Notably, our universality evaluations reveal promising transferability to other vehicle classes, tasks (segmentation models), and the real world, not just other vehicles.

cs.CV↗

arXiv2023

Quantum Circuit Designs of Point Doubling for Binary Elliptic Curves

In the past years, research on Shor's algorithm for solving elliptic curves for discrete logarithm problems (Shor's ECDLP), the basis for cracking elliptic curve-based cryptosystems (ECC), has started to garner more significant interest. To achieve this, most works focus on quantum point addition subroutines to realize the double scalar multiplication circuit, an essential part of Shor's ECDLP, whereas the point doubling subroutines are often overlooked. In this paper, we investigate the quantum point doubling circuit for the stricter assumption of Shor's algorithm when doubling a point should also be taken into consideration. In particular, we analyze the challenges on implementing the circuit and provide the solution. Subsequently, we design and optimize the corresponding quantum circuit, and analyze the high-level quantum resource cost of the circuit. Additionally, we discuss the implications of our findings, including the concerns for its integration with point addition for a complete double scalar multiplication circuit and the potential opportunities resulting from its implementation. Our work lays the foundation for further evaluation of Shor's ECDLP.

quant-ph↗

arXiv2023

Proximity-induced superconductivity in a 2D Kondo lattice of an f-electron-based surface alloy

Realizing hybrids of low-dimensional Kondo lattices and superconducting substrates leads to fascinating platforms for studying the exciting physics of strongly correlated electron systems with induced superconducting pairing. Here, we report a scanning tunneling microscopy and spectroscopy study of a new type of two-dimensional (2D) La-Ce alloy grown epitaxially on a superconducting Re(0001) substrate. We observe the characteristic spectroscopic signature of a hybridization gap evidencing the coherent spin screening in the 2D Kondo lattice realized by the ultrathin La-Ce alloy film on normal conducting Re(0001). Upon lowering the temperature below the critical temperature of rhenium, a superconducting gap is induced with an in-gap Shiba band arising from the interaction of residual unscreened magnetic moments with the superconducting substrate. A positive correlation between the Kondo hybridization gap and the binding energy of the subgap Shiba band maximum is found. Our results open up a promising route toward the design of artificial superconducting Kondo and heavy fermion systems.

cond-mat.str-el↗

arXiv2022

Reducing the Depth of Quantum FLT-Based Inversion Circuit

Works on quantum computing and cryptanalysis has increased significantly in the past few years. Various constructions of quantum arithmetic circuits, as one of the essential components in the field, has also been proposed. However, there has only been a few studies on finite field inversion despite its essential use in realizing quantum algorithms, such as in Shor's algorithm for Elliptic Curve Discrete Logarith Problem (ECDLP). In this study, we propose to reduce the depth of the existing quantum Fermat's Little Theorem (FLT)-based inversion circuit for binary finite field. In particular, we propose follow a complete waterfall approach to translate the Itoh-Tsujii's variant of FLT to the corresponding quantum circuit and remove the inverse squaring operations employed in the previous work by Banegas et al., lowering the number of CNOT gates (CNOT count), which contributes to reduced overall depth and gate count. Furthermore, compare the cost by firstly constructing our method and previous work's in Qiskit quantum computer simulator and perform the resource analysis. Our approach can serve as an alternative for a time-efficient implementation.

quant-ph↗

arXiv2022

DTA: Physical Camouflage Attacks using Differentiable Transformation Network

To perform adversarial attacks in the physical world, many studies have proposed adversarial camouflage, a method to hide a target object by applying camouflage patterns on 3D object surfaces. For obtaining optimal physical adversarial camouflage, previous studies have utilized the so-called neural renderer, as it supports differentiability. However, existing neural renderers cannot fully represent various real-world transformations due to a lack of control of scene parameters compared to the legacy photo-realistic renderers. In this paper, we propose the Differentiable Transformation Attack (DTA), a framework for generating a robust physical adversarial pattern on a target object to camouflage it against object detection models with a wide range of transformations. It utilizes our novel Differentiable Transformation Network (DTN), which learns the expected transformation of a rendered object when the texture is changed while preserving the original properties of the target object. Using our attack framework, an adversary can gain both the advantages of the legacy photo-realistic renderers including various physical-world transformations and the benefit of white-box access by offering differentiability. Our experiments show that our camouflaged 3D vehicles can successfully evade state-of-the-art object detection models in the photo-realistic environment (i.e., CARLA on Unreal Engine). Furthermore, our demonstration on a scaled Tesla Model 3 proves the applicability and transferability of our method to the real world.

cs.CV↗

arXiv2021

Anisotropic non-split zero-energy vortex bound states in a conventional superconductor

Vortices in topological superconductors are predicted to host Majorana bound states (MBSs) as exotic quasiparticles. In recent experiments, the spatially non-split zero-energy vortex bound state in topological superconductors has been regarded as an essential spectroscopic signature for the observation of MBSs. Here, we report the observation of anisotropic non-split zero-energy vortex bound states in a conventional elemental superconductor with a topologically trivial band structure using scanning tunneling microscopy and spectroscopy. The experimental results, corroborated by quasi-classical theoretical calculations, indicate that the non-split states directly reflect the quasiparticle trajectories governed by the surface electronic structure. Our study implies that non-split zero-energy states are not a conclusive signature of MBSs in vortex cores, stimulating a revision of the current understanding of such states.

cond-mat.supr-con↗

arXiv2020

Spectroscopic signature of the Stark-shifted Tamm-type surface state of La(0001)

We have studied the Tamm-type surface state of La(0001) by tunneling spectroscopy within a wide range of tunneling currents from 0.1 nA to 8000 nA, thereby tuning the electric-field strength in a tip-vacuum-sample tunnel junction. We observe a significant shift of the unoccupied Tamm-type surface state toward the Fermi energy with increasing electric-field strength, accompanied by a broadening of the width of the resonance peak indicating a decrease of the surface-state lifetime. Our experimental results are contrary to previous reports for Stark-shifted Shockley-type surface states of noble metal (111) surfaces.

cond-mat.mes-hall↗

arXiv2020

Long-range focusing of magnetic bound states in superconducting lanthanum

Quantum mechanical systems with long-range interactions between quasiparticles provide a promising platform for coherent quantum information technology. Superconductors are a natural choice for solid-state based quantum devices, while magnetic impurities inside superconductors give rise to quasiparticle excitations of broken Cooper pairs that provide characteristic information about the host superconductor. Here, we reveal that magnetic impurities embedded below a superconducting La(0001) surface interact via quasiparticles extending to very large distances, up to several tens of nanometers. Using low-temperature scanning probe techniques, we observe the corresponding anisotropic and giant oscillations in the local density of states. Theoretical calculations indicate that the quasi-two-dimensional surface states with their strongly anisotropic Fermi surface play a crucial role for the focusing and long-range extension of the magnetic bound states. The quasiparticle focusing mechanism should facilitate the design of versatile magnetic structures with tunable and directed magnetic interactions over large distances, thereby paving the way toward the design of low-dimensional magnet-superconductor hybrid systems exhibiting topologically non-trivial quantum states as possible elements of quantum computation schemes based on Majorana quasiparticles.

cond-mat.supr-con↗

arXiv2018

Atomic-Scale Interface Engineering of Majorana Edge Modes in a 2D Magnet-Superconductor Hybrid System

Topological superconductors are predicted to harbor exotic boundary states - Majorana zero-energy modes - whose non-Abelian braiding statistics present a new paradigm for the realization of topological quantum computing. Using low-temperature scanning tunneling spectroscopy (STS), we here report on the direct real-space visualization of chiral Majorana edge states in a monolayer topological superconductor, a prototypical magnet-superconductor hybrid system comprised of nano-scale Fe islands of monoatomic height on a Re(0001)-O(2$\times$1) surface. In particular, we demonstrate that interface engineering by an atomically thin oxide layer is crucial for driving the hybrid system into a topologically non-trivial state as confirmed by theoretical calculations of the topological invariant, the Chern number.

cond-mat.supr-con↗

arXiv2017

Atomic-scale visualization of surface-assisted orbital order

Orbital-related physics attracts growing interest in condensed matter research, but direct real-space access of the orbital degree of freedom is challenging. Here we report a first, real-space, imaging of a surface- assisted orbital ordered structure on a cobalt-terminated surface of the well-studied heavy fermion compound CeCoIn5. Within small tip-sample distances, the cobalt atoms on a cleaved (001) surface take on dumbbell shapes alternatingly aligned in the [100] and [010] directions in scanning tunneling microscopy topographies. First- principles calculations reveal that this structure is a consequence of the staggered dxz-dyz orbital order triggered by enhanced on-site Coulomb interaction at the surface. This so-far-overlooked surface-assisted orbital ordering may prevail in transition metal oxides, heavy fermion superconductors and other materials.

cond-mat.str-el↗

arXiv2017

Dirac fermions in borophene

Honeycomb structures of group IV elements can host massless Dirac fermions with non-trivial Berry phases. Their potential for electronic applications has attracted great interest and spurred a broad search for new Dirac materials especially in monolayer structures. We present a detailed investigation of the \beta 12 boron sheet, which is a borophene structure that can form spontaneously on a Ag(111) surface. Our tight-binding analysis revealed that the lattice of the \beta 12-sheet could be decomposed into two triangular sublattices in a way similar to that for a honeycomb lattice, thereby hosting Dirac cones. Furthermore, each Dirac cone could be split by introducing periodic perturbations representing overlayer-substrate interactions. These unusual electronic structures were confirmed by angle-resolved photoemission spectroscopy and validated by first-principles calculations. Our results suggest monolayer boron as a new platform for realizing novel high-speed low-dissipation devices.

cond-mat.mtrl-sci↗

arXiv2015

Site-dependent conduction channel transmission in atomic-scale superconducting junctions

Using scanning tunneling microscopy, we reproducibly obtained electrical conductance spectra of superconductor- superconductor atomic point contacts formed on various atomic sites of the substrate. From the analysis of the subharmonic features due to the multiple Andreev reflection, spatial distributions of the number of the conduction channels and their transmission probabilities were obtained. It is found that the number of channels and the transmission probabilities strongly depend on an atomic site where the contact is formed. We also revealed how the conduction channels and their transmission probability evolve from the tunneling to contact regimes. The Josephson current also exhibits the atomic site dependence, which is explained by the site-dependent transmission probabilities. Our results demonstrate a crucial role of the atomic geometry in the conduction channels of the ultimately confined conductor for the first time experimentally.

cond-mat.mes-hall↗