A Tutorial and Review of Automobile Direct ToF LiDAR SoCs: Evolution of Next-Generation LiDARs

Yoshioka, Kentaro

doi:10.1587/transele.2021cti0002

Cited by 7 publications

(9 citation statements)

References 40 publications

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“…1), and is typically processed by a DNN for accurate object detection. Among dToF LiDARs, early Velodyne LiDARs such as VLP-16 [16] and VLP-32c [24] are commonly known as the first-generation (first-gen) LiDARs [18], which naively integrate the classic point-wise laser ranging systems. To achieve 360 • measurements, they mechanically rotate to scan each azimuth with a small step such as 0.1 • .…”

Section: Basics Of Lidar Sensingmentioning

confidence: 99%

“…The advent of first-gen LiDAR has greatly improved AD perception, but its complex mechanical design increases costs and limits scalability. To overcome the limitations, the next-generation (next-gen) LiDARs [18] mount all components, such as the photodetector and the readout circuitry, on a single chip known as a system-on-chip (SoC) approach. This approach not only reduces the cost and improves the scalability of the system, but also allows new designs of laser firing and receiving.…”

Section: Technology Trends In Recent Lidarsmentioning

confidence: 99%

“…The following works thus all evaluate their attacks only on VLP-16 [10,11,13,14] or use the attack capability on VLP-16 to justify the validity of their threat model [15,17]. Although these results are valid on VLP-16, there is no guarantee that these results are still valid in more recent LiDARs, known as next-generation (or next-gen) LiDARs [18], as opposed to the first-generation (or firstgen) ones such as VLP-16. The next-gen LiDARs have more advanced security-related features, such as laser timing randomization and pulse fingerprinting.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack

Sato¹,

Hayakawa²,

Suzuki³

et al. 2023

Preprint

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LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long-and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD). Meanwhile, such a safety-critical application strongly motivates its security research. A recent line of research demonstrates that one can manipulate the LiDAR point cloud and fool object detection by firing malicious lasers against LiDAR. However, these efforts face 3 critical research gaps: (1) evaluating only on a specific LiDAR (VLP-16); (2) assuming unvalidated attack capabilities; and (3) evaluating with models trained on limited datasets.To fill these critical research gaps, we conduct the first large-scale measurement study on LiDAR spoofing attack capabilities on object detectors with 9 popular LiDARs in total and 3 major types of object detectors. To perform this measurement, we significantly improved the LiDAR spoofing capability with more careful optics and functional electronics, which allows us to be the first to clearly demonstrate and quantify key attack capabilities assumed in prior works. However, we further find that such key assumptions actually can no longer hold for all the other (8 out of 9) LiDARs that are more recent than VLP-16 due to various recent LiDAR features. To this end, we further identify a new type of LiDAR spoofing attack that can improve on this and be applicable to a much more general and recent set of LiDARs. We find that its attack capability is enough to (1) cause end-to-end safety hazards in simulated AD scenarios, and (2) remove real vehicles in the physical world. We also discuss the defense side.

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Section: Basics Of Lidar Sensingmentioning

confidence: 99%

Section: Technology Trends In Recent Lidarsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack

Sato¹,

Hayakawa²,

Suzuki³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The following works thus all evaluate their attacks only on VLP-16 [9,10,12,13] or use the attack capability on VLP-16 to justify the validity of their threat model [14,16]. Although these results are valid on VLP-16, there is no guarantee that these results are still valid in more recent LiDARs, known as next-generation or new-generation (or new-gen) LiDARs [17], as opposed to the first-generation (or first-gen) ones such as VLP-16. The new-gen LiDARs have more advanced securityrelated features, such as laser timing randomization and pulse fingerprinting.…”

Section: Introduction Lidar (Light Detection and Rangingmentioning

confidence: 99%

LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies

Sato,

Hayakawa,

Suzuki

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

View full text Add to dashboard Cite

LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long-and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD). Meanwhile, such a safety-critical application strongly motivates its security research. A recent line of research finds that one can manipulate the LiDAR point cloud and fool object detectors by firing malicious lasers against LiDAR. However, these efforts face 3 critical research gaps: (1) considering only one specific LiDAR (VLP-16); (2) assuming unvalidated attack capabilities; and (3) evaluating object detectors with limited spoofing capability modeling and setup diversity.To fill these critical research gaps, we conduct the first large-scale measurement study on LiDAR spoofing attack capabilities on object detectors with 9 popular LiDARs, covering both first-and new-generation LiDARs, and 3 major types of object detectors trained on 5 different datasets. To facilitate the measurements, we (1) identify spoofer improvements that significantly improve the latest spoofing capability, (2) identify a new object removal attack that overcomes the applicability limitation of the latest method to new-generation LiDARs, and (3) perform novel mathematical modeling for both object injection and removal attacks based on our measurement results. Through this study, we are able to uncover a total of 15 novel findings, including not only completely new ones due to the measurement angle novelty, but also many that can directly challenge the latest understandings in this problem space. We also discuss defenses.

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“…Vertical III–V compound semiconductor nanowires (NWs) on Si have attracted attention as building blocks for nanoscale light sources in such light‐emitting diodes (LEDs) and laser diodes (LDs) in Si nanophotonics, [ 1 ] imaging technologies, [ 2 ] on‐chip spectroscopy [ 3 ] and LiDAR systems. [ 4 ] This is because the NW structure geometrically shrinks the occupied area by one several thousand as compared to those of planar light sources like the smallest vertical surface‐emitting laser (VCSEL). Core–multishell (CMS) structures are able to mount radial double heterostructures (DH) with quantum well (QW) and p–n junctions on the NW sidewalls and enlarge surface‐to‐volume ratio.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Light Extraction of Nano‐Light‐Emitting Diodes with Metal‐Clad Structure Using Vertical GaAs/GaAsP Core–Multishell Nanowires on Si Platform

Tomioka

Sugita

Motohisa

2023

Advanced Photonics Research

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Nanometer‐scaled light sources using III–V compound semiconductor nanowires (NWs) on Si are expected as building blocks for next‐generation Si photonics, bioimaging, on‐chip microscopy, and light detection and ranging (LiDAR) techniques. This is, however, limited in a few materials systems due to complexity in integration of the vertical III–V NWs on Si and device process flow. Suppressing optical loss in the NW materials beyond the optical diffraction remains difficult in enhancing light extraction. Herein, the effect of the vertical metal‐clad architectures for the vertical nano‐light‐emitting diodes (LEDs) using GaAs/GaAsP‐related core–multishell NWs heterogeneously integrated on Si is investigated. The grown core–multishell NW is composed of a radial n‐GaAs/n‐GaAsP/p‐GaAs/p‐GaAsP double heterostructure. The vertical metal‐clad NW‐LEDs show suppression of carrier overflow effect and rapid enhancement of electrical luminescence.

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A Tutorial and Review of Automobile Direct ToF LiDAR SoCs: Evolution of Next-Generation LiDARs

Cited by 7 publications

References 40 publications

Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack

Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack

LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies

Enhanced Light Extraction of Nano‐Light‐Emitting Diodes with Metal‐Clad Structure Using Vertical GaAs/GaAsP Core–Multishell Nanowires on Si Platform

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