Spiking Neural P systems are a class of membrane computing models inspired directly by biological neurons. Besides the theoretical progress made in this new computational model, there are also numerous applications of P systems in fields like formal verification, artificial intelligence, or cryptography. Motivated by all the use cases of SN P systems, in this paper, we present a new privacy-preserving protocol that enables a client to compute a linear function using an SN P system hosted on a remote server. Our protocol allows the client to use the server to evaluate functions of the form t_1k + t_2 without revealing t_1, t_2 or k and without the server knowing the result. We also present an SN P system to implement any linear function over natural numbers and some security considerations of our protocol in the honest-but-curious security model.

翻译：脉冲神经P系统是一类直接受生物神经元启发的膜计算模型。除了这一新型计算模型在理论上取得的进展外，P系统在形式化验证、人工智能或密码学等领域也有众多应用。受SN P系统所有应用场景的启发，本文提出了一种新的隐私保护协议，使客户端能够利用远程服务器上部署的SN P系统计算线性函数。该协议允许客户端使用服务器评估形如t₁k + t₂的函数，同时不泄露t₁、t₂或k的值，并且服务器无法获知计算结果。本文还给出了一个可在自然数上实现任意线性函数的SN P系统，并讨论了该协议在诚实但好奇安全模型下的部分安全特性。