Complexity-theoretic modeling of biological cyanide poisoning as security Attack in Self-Organizing Networks

被引:0
|
作者
Kong, Jiejun [1 ]
Hong, Xiaoyan [2 ]
Wu, Dapeng [1 ]
Gerla, Mario [3 ]
机构
[1] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
[2] Univ Alabama, Dept Comp Sci, Tuscaloosa, AL 35487 USA
[3] Univ California, Dept Comp Sci, Los Angeles, CA 90095 USA
关键词
algorithms; modeling and simulation of bio-sets; complexity theory; self-organization;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
We draw an analogy of biological cyanide poisoning to security attacks in self-organizing mobile ad hoc networks. When a circulatory system is treated as an enclosed network space, a hemoglobin is treated as a mobile node, and a hemoglobin binding with cyanide ion is treated as a compromised node (which cannot bind with oxygen to furnish its oxygen-transport function), we show how cyanide poisoning can reduce the probability of oxygen/message delivery to a "negligible" quantity. Like modern cryptography, security problem in our network-centric model is defined on the complexity-theoretic concept of "negligible", which is asymptotically sub-polynomial with respect to a pre-defined system parameter x. Intuitively, the parameter x is the key length n in modern cryptography, but is changed to the network scale, or the number of network nodes N, in our model. Based on this new analytic model, we show that RP (n-runs) complexity class with a virtual oracle can formally model the cyanide poisoning phenomenon and similar network threats. This new analytic approach leads to a new view of biological threats from the perspective of network security and complexity theoretic study.
引用
收藏
页码:914 / +
页数:2
相关论文
共 47 条
  • [21] Wireless integrated network sensors: Towards low cost and robust self-organizing security networks
    Pottie, GJ
    Clare, LP
    SENSORS, C31, INFORMATION, AND TRAINING TECHNOLOGIES FOR LAW ENFORCEMENT, 1999, 3577 : 86 - 95
  • [22] Nonlinear system modeling using self-organizing fuzzy neural networks for industrial applications
    Zhou, Hongbiao
    Zhao, Huanyu
    Zhang, Yu
    APPLIED INTELLIGENCE, 2020, 50 (05) : 1657 - 1672
  • [23] Nonlinear system modeling using self-organizing fuzzy neural networks for industrial applications
    Hongbiao Zhou
    Huanyu Zhao
    Yu Zhang
    Applied Intelligence, 2020, 50 : 1657 - 1672
  • [24] Combining Self-Organizing and Graph Neural Networks for Modeling Deformable Objects in Robotic Manipulation
    Valencia, Angel J.
    Payeur, Pierre
    FRONTIERS IN ROBOTICS AND AI, 2020, 7
  • [25] Self-Organizing Map-Based Scheme Against Probabilistic SSDF Attack in Cognitive Radio Networks
    Cheng, Zhixu
    Song, Tiecheng
    Zhang, Jing
    Hu, Jing
    Hu, Yazhou
    Shen, Lianfeng
    Li, Xi
    Wu, Jun
    2017 9TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2017,
  • [26] Improving attack detection in self-organizing networks: A trust-based approach toward alert satisfaction
    Gil Perez, Manuel
    Gomez Marmol, Felix
    Martinez Perez, Gregorio
    2015 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2015, : 1945 - 1951
  • [27] COMPLEXITY AND SPATIAL DYNAMICS MODELING - FROM CATASTROPHE-THEORY TO SELF-ORGANIZING PROCESS - A REVIEW OF THE LITERATURE
    LUNG, Y
    ANNALS OF REGIONAL SCIENCE, 1988, 22 (02): : 81 - 111
  • [28] Applying emergent self-organizing behavior for the coordination of 4G networks using complexity metrics
    Ho, LTW
    Samuel, LG
    Pitts, JM
    BELL LABS TECHNICAL JOURNAL, 2003, 8 (01) : 5 - 25
  • [29] Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps
    Bankovic, Zorana
    Fraga, David
    Moya, Jose M.
    Carlos Vallejo, Juan
    Araujo, Alvaro
    Malagon, Pedro
    de Goyeneche, Juan-Mariano
    Villanueva, Daniel
    Romero, Elena
    Blesa, Javier
    ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, 2010, 339 : 311 - 318
  • [30] Probabilistic morphological modeling of hydrographic networks from satellite imagery using Self-Organizing Maps
    Zaremba, MB
    Palenichka, RM
    CONTROL AND CYBERNETICS, 2002, 31 (02): : 343 - 369