Random sequences and maps are essential for the applications in cryptography and many other fields in Information Technologies. To achieve true randomness, one still needs to refer to natural phenomena, be it physical, chemical or biological. Here we analyse the possibility to apply stochastic physico–chemical dynamics to generate truly random sequences and bitmaps. To this purpose, we utilize simulations of adsorption–desorption (AD) based intrinsic noise in realistic microsystems and nanosystems. We focus on affinity-based chemical or biological sensors, for instance those based on micro or nanocantilevers, as well as those utilizing plasmonic and generally metamaterial phenomena (refractometric nanosensors.) Random numbers in sequences or maps in both types of structures are generated by simulations of intrinsic fluctuations of AD processes. We present three novel AD-simulation based algorithms, two of them for bitstreams and one for dynamic bitmaps. We use the stochastic simulation algorithm developed for modelling of chemical kinetics. We tested the obtained pseudo random numbers by visual analysis and using our custom designed test suite. We have proven the applicability of the proposed method for generation of random sequences and maps. Our results could be used in digital data encryption and communication. They also point out to a possibility to a hardware implementation of a full random number generator that would incorporate the mentioned micro and nanosystems.

随机序列和图谱对于密码学和信息技术中许多其他领域的应用至关重要。为了获得真正的随机性，人们仍然需要提及自然现象，无论是物理的，化学的还是生物的。在这里，我们分析了应用随机物理化学动力学来生成真正随机序列和位图的可能性。为此，我们在现实的微系统和纳米系统中利用了基于吸附-解吸（AD）的固有噪声的模拟。我们专注于基于亲和力的化学或生物传感器，例如基于微悬臂或纳米悬臂的传感器，以及利用等离子体和一般超材料现象的传感器（折光纳米传感器）。通过模拟生成两种结构中序列或图的随机数AD过程的内在波动。我们提出了三种基于AD仿真的新颖算法，其中两种用于位流，一种用于动态位图。我们使用为化学动力学建模开发的随机模拟算法。我们通过视觉分析和使用定制设计的测试套件对获得的伪随机数进行了测试。我们已经证明了所提出的方法可用于生成随机序列和图谱。我们的结果可用于数字数据加密和通信。他们还指出完全随机数生成器的硬件实现可能会包含上述微系统和纳米系统。我们通过视觉分析和使用定制设计的测试套件对获得的伪随机数进行了测试。我们已经证明了所提出的方法可用于生成随机序列和图谱。我们的结果可用于数字数据加密和通信。他们还指出完全随机数生成器的硬件实现可能会包含上述微系统和纳米系统。我们通过视觉分析和使用我们定制设计的测试套件来测试获得的伪随机数。我们已经证明了所提出的方法可用于生成随机序列和图谱。我们的结果可用于数字数据加密和通信。他们还指出完全随机数生成器的硬件实现可能会包含上述微系统和纳米系统。