Healthcare Data Protection Using Cellular Automata Encryption Techniques

A mechanism for synthesizing sequential logic, modeled as a finite state machine (FSM), is presented. This method uses cellular automata (CA) to find an underlying sequential machine which has behaviour resembling that of the FSM. Interrupt logic is added to this machine to match the behavior of the CA to that of the FSM. The authors also introduce a variant of this system based on programmable cellular automata (PCA) that has certain advantages over synthesis using fixed CA structures. Designs synthesized using CA and PCA are very regular and efficient, while having the advantages of testability and better manufacturability. Also, in contrast to most conventional techniques, these schemes stress the optimization of the total area of the design, including the interconnects, while synthesizing the sequential machine. >

Elementary cellular automata (ECA) rule 184 can be used as mathematical models of traffic flows. The slow-to-start model is obtained from the ECA rule 184 model by taking time lag for restart into consideration and is represented by 3-state 3-neighbor cellular automata (CA). In the present paper, we propose a traffic model where vehicles following the slow-to-start rule and those not following the slow-to-start rule are mixed. This model, called the mixed slow-to-start model, is represented by 4-state 3-neighbor CA. Further, we introduce the vector representation of CA with the slow-to-start rule and with the mixed slow-to-start rule, and then get their corresponding fuzzy CA. These fuzzy CA provide continuous-valued traffic models with the slow-to-start effect. Comparing the fundamental diagrams of the the slow-to-start model, the mixed slow-to-start model, and their fuzzy counterparts, we investigate the influence of the density and the mixing ratio of vehicles on traffic jams.

In this paper is developed a high-performance cryptosystem based on programmable cellular automata (PCA). The cellular automata (CA) are programmable according to the rules stored in the file memory. As the development of CA applications is generally an experimental effort, the research implies the exploration through simulation of the huge space of cellular automata local rules and global states. The encryption and decryption modules are identically and the cryptosystem is featured by its large key space and high speed due to cellular automata's parallel information processing. A cascadable structure of PCA is used in order to ensure the security of the algorithm. The proposed PCA block cipher is used, as a library (DLL Dynamic Link Library), in order to assure the data encryption of medical data sent over the internet.

Programmable Cellular Automata (PCA) employs some control signals on a Cellular Automata(CA) structure. Programmable Cellular Automata were successfully applied for simulation of biological systems, physical systems and recently to design parallel and distributed algorithms for solving task density and synchronization problems. In this paper PCA is applied to develop cryptography algorithms. This paper deals with the cryptography for a parallel AES encryption algorithm based on programmable cellular automata. This proposed algorithm based on symmetric key systems.KeywordsCAPCACryptographyAESSymmetric Key

In this chapter, bio-inspired techniques based on the cellular automata (CAs) and programmable cellular automata (PCAs) theory are used to develop information security systems. The proposed cryptosystem is composed from a combination of a CA as a pseudorandom number generator (PRNG) and a PCA that construct the ciphering functions of the designed enciphering scheme. It is presented how simple elements named „cells” interact between each other using certain rules and topologies to form a larger system that can be used to encrypt/decrypt data sent over network communication systems. The proposed security system was implemented in hardware in FPGA devices of type Spartan 3E – XC3S500E and was analyzed and verified, including NIST statistical tests, to assure that the system has good security and high speed. The experimental results proves that the cryptographic techniques based on bio-inspired algorithms provides an alternative to the conventional techniques (computational methods).

This work investigates elementary cellular automata comparing their dynamic evolution on two topologies: the usual regular lattice and a small-world network constructed as a directed graph. The number of iterations for any initial perturbation to propagate over all cells of the automaton corresponds to how quickly an initial configuration reaches a high entropy state, and the temporal rate of propagation of the perturbation can be evaluated from a chaotic set of elementary cellular automata rules using an entropy measure. Results indicate that the average entropy can be nearly tripled in the small-world network topology, suggesting much faster applications (e.g. in Cryptography) from alterations in the topological arrangement of usual cellular automata regular lattices.

Chaotic properties of elementary cellular automata with majority memory

The regular structure of 1-D and 2-D cellular automata as a Built-in Self-Test (BIST) structure have been proposed [Hort'89, Hort'90, Das'89, Das90b, DRC91b]. In the present paper, the performance of 2-D CA as a pseudo-randorn pattern generator has been evaluated. The potential increase in the local neigh bourhood structure for 2-D CA has led to better randomness of the generated patterns as compared to LFSR and 1-D CA. The quality of the random patterns generated with 2-D CA based BIST structure has been evaluated by comparing the fault cover age on several benchmark circuits. The design of a Programmable Cellular Automata chip has been proposed as a versatile BIST structure.

Evolution-in-Materio (EIM) is a method of using artificial evolution to exploit physical properties of materials for computation. It has previously been successfully used to evolve a multitude of different computational devices implemented in physical materials. One of the main problems has been the stability of solutions due to physical changes in the substrate materials, e.g. topological or electrical, leading to devices sensitive to the evolutionary history, i.e. instability. This paper presents stable linearly and non-linearly separable logic gates, and elementary cellular automata (CA) transition functions, successfully evolved in single-walled carbon nanotube (SWCNT) and polymer composite materials. The results herein show the feasibility of building stand-alone in-materio devices and outline a novel computational abstraction for EIM based on CA. This work is done within the European Project NASCENCE.

In this paper, we presented a low-power, less area architecture of S-Box used in advanced encryption standard (AES) using programmable cellular automata (PCA). The proposed architecture performance in terms of security is evaluated using cryptographic properties such as nonlinearity, input/output entropy, correlation immunity bias, balancedness property, strict avalanche criterion, and it is found that the proposed method is secure enough for cryptography applications. The proposed architecture of AES with PCA-based S-Box is implemented on ASIC using TSMC 0.18-\({\upmu }\)m and UMC 0.13-\({\upmu }\)m CMOS technology libraries. Simulation studies show that the proposed architecture has average energy consumption of 58.702 nJ, power dissipation of 3.259 mW, area of 0.184 mm\(^2\), for TSMC 0.18-\({\upmu }\)m at 13.69 MHz and energy consumption of 18.275 nJ, power dissipation of 1.026 mW, area of 0.069 \({\upmu m}^{2}\) for UMC 0.13-\({\upmu }\)m at 13.69 MHz. The proposed architecture shows reduction in power dissipation by 83% and in energy consumption by 10% compared to the best classical S-Box and composite field arithmetic-based S-Box for AES algorithm. The S-Box using PCA is more flexible and dynamic in nature with low power, lesser energy consumption area and hence suitable for wireless body area network applications.

Programmable cellular automata based Montgomery hardware architecture

This article presents an encryption system based on the PCA (Programmable Cellular Automata) theory and the implementation in reconfigurable hardware in order to achieve high speed communication for real time applications. The proposed encryption algorithm belongs to the class of symmetric key and the entire model was implemented on a reconfigurable hardware in FPGA (Field-Programmable Gate Arrays) device of type Spartan 3E XC3S500E in order to take the full advantage of the inherent parallelism of the PCA. Based on PCA state transitions certain fundamental transformations are defined which represents block ciphering functions of the proposed enciphering scheme. The experimental results prove that the proposed enciphering scheme provides high speed, good security and it is ideally for hardware implementation in FPGA devices.

In this paper, programmable cellular automata (PCAs) are used to design a symmetric key cryptosystem. Based on PCAs state transitions certain fundamental transformations are defined which represents block ciphering functions of the proposed enciphering scheme. In order to verify the proposed encryption algorithm, an experimental hardware platform based on a reconfigurable FPGA of type Spartan 3E XC3S500E was used. The enciphering scheme provides high speed, good security and it is ideally suit for hardware implementation in FPGA devices.

This paper explores the concept of isomorphism in cellular automata (CAs), focusing on identifying and understanding isomorphic relationships between distinct CAs. A cellular automaton (CA) is said to be isomorphic to another CA if the configuration transition diagrams of the two CAs are identical. To illustrate how isomorphism entails the preservation of structural properties while allowing for variations in state representations, we exhaustively explore the isomorphic reversible rules in the first degree CAs (FDCAs), that is, the simple three-neighborhood CAs represented by eight parameters. The experimental study includes reversible FDCAs for states two to 10 with cell lengths of four to seven under the null boundary condition and states two to seven with cell lengths of four to seven under the periodic boundary condition. Given a CA, we also provide two synthesis methods for identifying the set of CAs that are isomorphic to it. The first method operates by permuting the states of a group of CA cell locations, whereas the second method involves exchanging cells at various points. We demonstrate that, depending on the range of exchanged cell positions, the isomorphic CAs produced in this way may have a bigger neighborhood than the input CA. Finally, we provide an exhaustive classification of the elementary CAs (ECAs) using the first synthesis method and compare it with existing results.

In this paper, we propose a new method to obtain the transition rules of two-dimensional cellular automata (CA) that performs grayscale image processing. CA has the advantages of producing complex systems from the local interaction of simple elements, and has attracted increased research interest. The difficulty of designing CA's transition rules to perform a particular task has severely limited their applications. So, the evolutionary design of CA rules has been studied. In this method, an evolutionary algorithm was used to evolve CA. In recent years, this method has been applied to image processing. Rosin has studied the evolutionary design of two-dimensional CA to perform noise reduction, thinning and convex hulls. Batouche et al. and Slatnia et al. employed genetic algorithm to investigate the possibility of CA to perform edge detection. In the previous methods, 2-state CA was used for binary image processing. Unlike the previous methods, the present method uses 256-state CA rules to perform grayscale image processing. Gene Expression Programming (GEP) proposed by Ferreira is employed as a learning algorithm in which the chromosomes encode the transition rules as expression trees. Experimental results for the reduction of impulse noise, salt-and-pepper noise and gaussian noise show that the proposed method is equivalent to previous methods in performance and more than 100 times faster than the method proposed by Rosin. We show that the rule obtained by the proposed method employs symmetry-based strategy in the noise reduction process and this property can reduce complexity of CA.