scholarly journals FINDING ATTRACTORS IN ASYNCHRONOUS BOOLEAN DYNAMICS

2011 ◽  
Vol 14 (03) ◽  
pp. 439-449 ◽  
Author(s):  
THOMAS SKODAWESSELY ◽  
KONSTANTIN KLEMM
Keyword(s):  
Fixed Points ◽  
State Transition ◽  
Boolean Networks ◽  
Computational Method ◽  
State Transitions ◽  
Transition Graph ◽  
Numerical Tests ◽  
State Transition Graph ◽  
Boolean Dynamics ◽  
Reduced State

We present a computational method for finding attractors (ergodic sets of states) of Boolean networks under asynchronous update. The approach is based on a systematic removal of state transitions to render the state transition graph acyclic. In this reduced state transition graph, all attractors are fixed points that can be enumerated with little effort in most instances. This attractor set is then extended to the attractor set of the original dynamics. Our numerical tests on standard Kauffman networks indicate that the method is efficient in the sense that the total number of state vectors visited grows moderately with the number of states contained in attractors.

scholarly journals Network Threat Identification and Analysis Based on a State Transition Graph

2013 ◽  
Vol 13 (Special-Issue) ◽  
pp. 51-61
Author(s):  
Huiying Lv ◽  
Yuan Zhang ◽  
Jie Wang
Keyword(s):  
Network Security ◽  
Real Time ◽  
State Transition ◽  
Local Area Network ◽  
State Transitions ◽  
State Graph ◽  
Area Network ◽  
Identification Algorithm ◽  
Transition Graph ◽  
State Transition Graph

Abstract With the rapid popularity of Internet and information technology, local area network is becoming insecure. Along with the improving advantages, security threats are emerging continually and bringing great pressure and challenges. An identification and analysis method for network real-time threats is proposed to accurately assess and master the current network security situation, and thereby preferably guide a dynamic defense. This method recognizes the current threats and predicts the subsequent threats by modeling attack scenarios and simulating attack state transferring. The threat identification model is called Attack State Transition Graph and Real-Time Attack State Graph, which is constructed by an Expanded Finite-State Automata. Based on the former possible threat paths, the state transitions can be illustrated and based on the latter, actually successful threats and threat paths are described. Then a threat identification algorithm is presented based on the above model. With this algorithm, various invalid threats are filtered; current valid threats are obtained by correlating the dynamic alarms with a static attack scenario. Further on, combining the Attack State Transition Graph with a Real-Time Attack State Graph, a possible next threat and a threat path can be identified and an attack target can also be predicted. Finally, the simulated results in an experimental network verify the feasibility and validity of the model and algorithm. This method provides a novel solution to evaluate and analyze the network security situation.

1A1-L10 Contact-State Transition Graph for Complex Shaped Objects(New Control Theory and Motion Control)

2011 ◽  
Vol 2011 (0) ◽  
pp. _1A1-L10_1-_1A1-L10_3
Author(s):  
Kensuke HARADA ◽  
Hiromu ONDA ◽  
Natsuki YAMANOBE ◽  
Eiichi YOSHIDA ◽  
Tokuo TSUJI ◽  
...  
Keyword(s):  
Control Theory ◽  
Motion Control ◽  
State Transition ◽  
Transition Graph ◽  
Contact State ◽  
State Transition Graph
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