Embedded TaintTracker: Lightweight Tracking of Taint Data against Buffer Overflow Attacks

被引:0
|
作者
Lin, Ying-Dar [1 ]
Wu, Fan-Cheng [1 ]
Huang, Tze-Yau [1 ]
Lai, Yuan-Cheng [2 ]
Lin, Frank C. [3 ]
机构
[1] Natl Chiao Tung Univ, Dept Comp Sci & Informat Engn, Hsinchu 30050, Taiwan
[2] Natl Taiwan Univ Sci & Technol, Dept Informat Management, Taipei, Taiwan
[3] San Jose State Univ, Dept Comp Engn, San Jose, CA USA
关键词
Software security; buffer overflow; taint tracking;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Taint tracking is a novel technique to prevent buffer overflow. Previous studies on taint tracking ran a victim's program on an emulator to dynamically instrument the code for tracking the propagation of taint data in memory and checking whether malicious code is executed. However, the critical problem of this approach is its heavy performance overhead. This paper proposes a new taint-style system called Embedded TaintTracker to eliminate the overhead in the emulator and dynamic instrumentation by compressing a checking mechanism into the operating system (OS) kernel and moving the instrumentation from runtime to compilation time. Results show that the proposed system outperforms the previous work, TaintCheck, by at least 8 times on throughput degradation, and is about 17.5 times faster than TaintCheck when browsing 1KB web pages.
引用
收藏
页数:5
相关论文
共 41 条
  • [31] Lightweight privacy-preserving data aggregation protocol against internal attacks in smart grid
    Wang, Xiao-Di
    Meng, Wei-Zhi
    Liu, Yi-Ning
    JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2020, 55
  • [32] Design and Detection of False Data Injection Attacks Against Output Tracking Control Systems
    Pang, Zhonghua
    Yang, Ruhang
    Liu, Guoping
    Zhang, Ji
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 7996 - 8001
  • [33] Multisensor-multitarget tracking based on belief propagation against false data injection attacks and denial of service attacks
    Yu, Yihua
    Liang, Yuan
    DIGITAL SIGNAL PROCESSING, 2022, 126
  • [34] SLP: A Secure and Lightweight Scheme Against Content Poisoning Attacks in Named Data Networking Based on Probing
    Ding, Kunpeng
    Yang, Jiayu
    Xue, Kaiping
    Han, Jiangping
    Li, Jian
    Sun, Qibin
    Lu, Jun
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2024, 32 (06) : 5128 - 5143
  • [35] K-Implicit Tracking Data Publishing Scheme Against Geo-Matching Attacks
    Niu, Kun
    Peng, Changgen
    Tian, Youliang
    Tan, Weijie
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2022, 38 (01) : 1 - 16
  • [36] Distributed Tracking Control of Nonlinear Multi-agent Systems Against False Data Injection Attacks
    Zhang, Yanhui
    Sun, Jian
    Wang, Gang
    Xu, Yong
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 4837 - 4842
  • [37] Two-Channel False Data Injection Attacks Against Output Tracking Control of Networked Systems
    Pang, Zhong-Hua
    Liu, Guo-Ping
    Zhou, Donghua
    Hou, Fangyuan
    Sun, Dehui
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2016, 63 (05) : 3242 - 3251
  • [38] A novel approach for securing data against adversary attacks in UAV embedded HetNet using identity based authentication scheme
    Wani, Aabid Rashid
    Gupta, Sachin Kumar
    Khanam, Zeba
    Rashid, Mamoon
    Alshamrani, Sultan S.
    Baz, Mohammed
    IET INTELLIGENT TRANSPORT SYSTEMS, 2023, 17 (11) : 2171 - 2189
  • [39] Fuzzy adaptive secure tracking control against unknown false data injection attacks for uncertain nonlinear systems with input quantization
    Zhao, Jipeng
    Yang, Guang-Hong
    APPLIED MATHEMATICS AND COMPUTATION, 2023, 437
  • [40] Adaptive predefined-time secure consensus tracking control for nonlinear multiagent systems against unknown false data injection attacks
    Wen, Luyao
    Niu, Ben
    Ji, Yulong
    Zhang, Baoyi
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2024, 361 (18):