Jinshu Su

Jinshu Su


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 June 2010 in IEEE Transactions on Vehicular Technology
Verified
Journal Article
Closed access
YSYipin Sun
Yipin Sun
RLRongxing Lu
Rongxing Lu
XLXiaodong Lin
Xiaodong Lin
XSXuemin (Sherman) Shen
Xuemin (Sherman) Shen
JSJinshu Su
Jinshu Su
In this paper, we propose an efficient pseudonymous authentication scheme with strong privacy preservation (PASS), for vehicular communications. Unlike traditional pseudonymous authentication schemes, the size of the certificate revocation list (CRL) in PASS is linear with the number of revoked vehicles and unrelated to how many pseudonymous certificates are held by the revoked vehicles. PASS supports the roadside unit (RSU)-aided distributed certificate service that allows the vehicles to update certificates on road, but the service overhead is almost unrelated to the number of updated certificates. Furthermore, PASS provides strong privacy preservation to the vehicles so that the adversaries cannot trace any vehicle, even though all RSUs have been compromised. Extensive simulations demonstrate that PASS outperforms previously reported schemes in terms of the revocation cost and the certificate updating overhead.

11 May 2016 in IEEE Communications Surveys & Tutorials
Verified
Journal Article
Closed access
CXChengcheng Xu
Chengcheng Xu
SCShuhui Chen
Shuhui Chen
JSJinshu Su
Jinshu Su
SYS. M. Yiu
S. M. Yiu
LHLucas C. K. Hui
Lucas C. K. Hui
Deep packet inspection (DPI) is widely used in content-aware network applications such as network intrusion detection systems, traffic billing, load balancing, and government surveillance. Pattern matching is a core and critical step in DPI, which checks the payload of each packet for known signatures (patterns) in order to identify packets with certain characteristics (e.g., malicious packets that carry viruses or worms). Regular expression is the major tool for signature description due to its powerful and flexible expressive ability. However, this flexibility also brings great challenges for efficient implementation in practice. Despite of hundreds to thousands of empirical proposals, wire-speed matching for large scale regular expressions still remains a big challenge. The gap between the matching throughput and the link speed is widening with the ever-increasing network link speed and pattern scale. This survey begins with a full-scale application background of DPI and technical background of regular expression matching in order to provide a global view and essential knowledge for readers. We then analyze the challenges in regular expression matching originated from the state explosion of finite state automaton used for regular expression matching. The nature of state explosion is analyzed in details, and the state-of-the-art solutions are grouped into categories of methods to relieve state expansion and methods to avoid state explosion, suggestions are also provided for building compact and efficient automata in different scenarios. Furthermore, proposals employing parallel platforms, including field-programmable gate array, GPU, general multi-processors, and ternary content addressable memory, to accelerate the matching process are introduced and thoroughly discussed. We also provide guidelines for efficient deployment for each of these platforms.

12 May 2011 in Journal of Computer Science and Technology
Verified
Journal Article
Closed access
PDF file
XYXue-Jun Yang
Xue-Jun Yang
XLXiang-Ke Liao
Xiang-Ke Liao
KLKai Lu
Kai Lu
QHQing-Feng Hu
Qing-Feng Hu
JSJun-Qiang Song
Jun-Qiang Song
JSJinshu Su
Jinshu Su

21 November 2018 in IEEE Internet of Things Journal
Verified
Journal Article
Closed access
ZWZiling Wei
Ziling Wei
BZBaokang Zhao
Baokang Zhao
JSJinshu Su
Jinshu Su
XLXicheng Lu
Xicheng Lu

23 November 2020 in IEEE Transactions on Network Science and Engineering
Verified
Journal Article
Closed access
JLJiahao Liu
Jiahao Liu
BZBaokang Zhao
Baokang Zhao
QXQin Xin
Qin Xin
JSJinshu Su
Jinshu Su
WOWei Ou
Wei Ou
Major space companies are developing satellite mega-constellations to provide global Internet coverage and services. Limited battery capacity is one of the biggest obstacles on mega-constellations due to the restricted weight and volume of satellites. Massive Internet packet routing tasks pose a big challenge to the energy system in such mega constellations. Incorrect use of satellite batteries during routing phases may significantly increase the energy consumption and cause node failure quickly.Existing state-of-the-art works on energy-saving routing for satellite networks paid much attention on traffic distribution and end-to-end delay issues.However, these methodologies were using many real-time network information for optimization which is not practical in mega-constellations.Note also that these works did not consider energy efficiency and guaranteed end-to-end delay simultaneously. In this paper, we propose a novel deep reinforcement learning based energy-efficient routing protocol called DRL-ER, which avoids the battery energy imbalance of constellations and can also guarantee a required bounded end-to-end delay. In DRL-ER, satellites can learn a routing policy that will balance energy usage among satellites.Extensive simulation results show that our proposed DRL-ER protocol reduces the energy consumption of satellites in average by more than 55% compared to the current state-of-the-art work, and prolongs the lifetime of constellations significantly.

1 October 2011 in Future Generation Computer Systems
Verified
Journal Article
Closed access
XWXiaofeng Wang
Xiaofeng Wang
CYChee Shin Yeo
Chee Shin Yeo
RBRajkumar Buyya
Rajkumar Buyya
JSJinshu Su
Jinshu Su