Yuhang Lin

College of Engineering

Works (9)

Updated: April 20th, 2024 05:02

2023 journal article

Control Design of a Continuous Model and Its Application in Highway Traffic Flow

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 70(7), 2575–2579.

By: X. Cai *, Y. Lin n, L. Liu * & C. Lin *

author keywords: Continuous model; control design; traffic flow control; partial differential equation
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Source: Web Of Science
Added: August 21, 2023

2023 article

Inverse Optimal Control of Korteweg-de Vries-Burgers Equation

IFAC PAPERSONLINE, Vol. 56, pp. 1351–1356.

By: X. Cai *, Y. Lin n, X. Zhan *, L. Wan*, L. Liu * & C. Lin *

author keywords: Korteweg-de Vries-Burgers equation; inverse optimality; boundary control; stabilization.
Source: Web Of Science
Added: April 15, 2024

2023 article

Inverse optimality of adaptive control for Korteweg-de Vries-Burgers equation

Cai, X., Lin, Y., Lin, C., & Liu, L. (2023, May 15). INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL.

By: X. Cai *, Y. Lin n, C. Lin * & L. Liu *

author keywords: Korteweg-de Vries-Burgers; Adaptive control; Stabilization; Inverse optimality
Source: Web Of Science
Added: October 16, 2023

2022 journal article

PREDICTOR CONTROL FOR WAVE PDE / NONLINEAR ODE CASCADED SYSTEM WITH BOUNDARY VALUE- DEPENDENT PROPAGATION SPEED

KYBERNETIKA, 58(3), 400–425.

By: X. Cai, Y. Lin*, J. Zhang & C. Lin

author keywords: cascaded system; wave dynamics; boundary value-dependent; predictor con-trol; backstepping transformation
Source: Web Of Science
Added: November 7, 2022

2022 article

PerfSig: Extracting Performance Bug Signatures via Multi-modality Causal Analysis

2022 ACM/IEEE 44TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2022), pp. 1669–1680.

By: J. He *, Y. Lin n, X. Gu n, C. Yeh * & Z. Zhuang *

author keywords: Debugging; Bug signatures; Software reliability; Performance
TL;DR: The experimental results show that PerfSig captures various kinds of fine-grained anomaly patterns from different machine data and successfully identifies the root cause functions through multi-modality causal analysis for 19 out of 20 tested performance bugs. (via Semantic Scholar)
Source: Web Of Science
Added: August 29, 2022

2022 article

SHIL: Self-Supervised Hybrid Learning for Security Attack Detection in Containerized Applications

2022 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING AND SELF-ORGANIZING SYSTEMS (ACSOS 2022), pp. 41–50.

By: Y. Lin n, O. Tunde-Onadele  n, X. Gu n, J. He * & H. Latapie

author keywords: Container Security; Security Attack Detection; Hybrid Machine Learning
TL;DR: SHIL is presented, a self-supervised hybrid learning solution, which combines unsupervised and supervised learning methods to achieve high accuracy without requiring any manual data labelling and can reduce false alarms by 39-91%. (via Semantic Scholar)
Source: Web Of Science
Added: December 19, 2022

2022 article

Understanding Software Security Vulnerabilities in Cloud Server Systems

2022 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING (IC2E 2022), pp. 245–252.

By: O. Tunde-Onadele  n, Y. Lin n, X. Gu n & J. He *

author keywords: Cloud Security; Vulnerability Detection; Bug Study
TL;DR: This paper conducts a systematic study over 110 software security vulnera-bilities in 13 popular cloud server systems and extracts principal vulnerable code patterns from those common vulnerability categories. (via Semantic Scholar)
Source: Web Of Science
Added: December 19, 2022

2020 article

CDL: Classified Distributed Learning for Detecting Security Attacks in Containerized Applications

36TH ANNUAL COMPUTER SECURITY APPLICATIONS CONFERENCE (ACSAC 2020), pp. 179–188.

By: Y. Lin n, O. Tunde-Onadele  n & X. Gu n

author keywords: Container Security; Anomaly Detection; Machine Learning
TL;DR: By introducing application classification into container behavior learning, CDL can improve the detection rate from catching 20 attacks to 31 attacks before those attacks succeed and reduce the false positive rate from over 12% to 0.24% compared to traditional anomaly detection schemes. (via Semantic Scholar)
Source: Web Of Science
Added: September 13, 2021

2020 article

Self-Patch: Beyond Patch Tuesday for Containerized Applications

2020 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING AND SELF-ORGANIZING SYSTEMS (ACSOS 2020), pp. 21–27.

By: O. Tunde-Onadele  n, Y. Lin n, J. He n & X. Gu n

author keywords: Container Security; Anomaly Detection; Security Patching
TL;DR: Self-Patch is presented, a new self-triggering patching framework for applications running inside containers that combines light-weight runtime attack detection and dynamic targeted patching to achieve more efficient and effective security protection for containerized applications. (via Semantic Scholar)
Source: Web Of Science
Added: November 29, 2021

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