Physical Unclonable Functions Based On Boolean Networks

Information security is related to many aspects of national security,economic development,personal privacy and social life.Physically unclonable function(PUF)is a hardware-based information security technology that is widely used in fields such as identification,key generation,device authentication and random number generation.PUF can dynamically generate random,unique and unpredictable "digital fingerprints" by extracting differences in the physical characteristics of the hardware systems(including differences in manufacturing processes and preparation materials,etc.).The security of PUF lies in the inherent complexity and non-reproducibility of the physical system.Due to the uncontrollable manufacturing process and the differences in preparation materials,even the same manufacturer cannot generate a completed identical PUF.Once the concept of PUF was proposed,it was soon widely studied in areas such as cryptography and information security.At present,a variety of PUF implementation schemes have been proposed,such as optical-PUF,magnetic-PUF,memory-PUF,arbiter-PUF,ring oscillator-PUF and so on.However,for most PUF schemes,their similar excitations tend to produce similar responses,making these schemes vulnerable to modeling attacks or even cracking,resulting in PUFs losing their proper security.The chaotic dynamics are highly sensitive to initial conditions and details of their underlying physical circuitry.Therefore,even chaotic systems with similar parameters can have exponential differences,so the exponentially growing response space can be obtained,thus improving the security of PUF.In this thesis,we propose a physical unclonable function based on Boolean networks(BNPUF),with the initial state of the nodes in the Boolean network as the input(challenge)and the chaotic transients of the Boolean network as the output(response).By constructing PUFs based on chaotic systems,BN-PUF can generate different responses by amplifying the small differences that exist in the manufacturing process of Boolean network circuits through chaotic mechanisms,which is important for increasing the security of PUF.This thesis focuses on BN-PUF,mainly carried out the following research:1.A Boolean network based on two-input logic gates is proposed to construct a physical unclonable function,and its physical realization is completed through a field programmable gate array(FPGA).By studying the output characteristics of BN-PUF at different numbers of nodes and initial states of nodes,it is found that BN-PUF has an exponentially growing excitation-response space when the number of nodes is greater than 6.2.The response collection method of BN-PUF is studied.The study found that there is a time window after BN-PUF leaves the initial state.High performance PUF can be achieved by sampling the chaotic signal generated by BN-PUF within the time window.The relationship between the number of BN-PUF nodes and the length of time window was also analyzed,and it was found that this time window gradually became shorter as the number of nodes increased.Finally,the correct acquisition of the response was achieved by studying the relationship between the effective measurement time and the time window of the BN-PUF response.3.The reliability,uniqueness and randomness of BN-PUF were evaluated,and the reliability of BN-PUF for different number of nodes was <0.1,uniqueness was >0.47 and randomness was 49.53%.The reliability of BN-PUF was also analyzed under different environments(temperature and voltage).Finally,the BN-PUF-based random number generator was implemented and the performance of the generated random numbers was evaluated by the NIST SP 800-22 test standard.