Kinds Of Digital Systems Research Articles

Design of Logically Obfuscated Memory and Arithmetic Logic Unit for Improved Hardware Security

In any kind of digital system, the processor and memories are used to play a vital role in today’s trend. The processors and memories are done many critical tasks in the system. Whereas the processor used to do several functions and memories used to store and retrieve the data. But these processors and memories are more vulnerable to various hardware attacks. By using several new devices may lead to many security issues which the attackers can leverage to introduce a new hardware attack. Various hardware security (HS) studies have been presented to prevent hardware from a security issue. Some of the security issues that are occurred in hardware are overbuilding, piracy and reverse engineering (RE) and so on. In many works of literature, obfuscating and camouflaging are done in the netlist of hardware devices. Even though, these methods are highly overheads, and also not secured up to the level of expectation. Therefore, the main motive of Hardware security is to secure an Arithmetic Logic Unit (ALU) processor and memory unit from the various threats. In this work, a Configurable GDI based Locking cell (GLC) is proposed which is added as redundant to the original netlist of ALU and memory units for its hardware protection. The basic concept of configurable GLC is to perform a wire or inverter by using keys to obfuscate an attacker. This GLC logic can overcome the drawback of existing methods based on obfuscation and cryptographic techniques. The results show that proposed GLC is possible in any kind of memory system, all with low area and delay penalty.

A Modified PSO Algorithm for IIR Digital Filter Modeling

Modeling for an unknown plant is a very important and primary task in the control system engineering. By using this established model, an adequate controller can be further designed to meet certain control specifications. This paper will propose a new modeling method which is based on the infinite impulse response (IIR) digital filter structure. A modified particle swarm optimization (PSO) with multiple subpopulations is utilized to solve for the IIR filter coefficients to model an unknown digital system. The developed PSO algorithm is able to overcome the multimodal error surface problem that often occurs in the system modeling of IIR digital filter. Finally, three different kinds of digital systems are examined to demonstrate the feasibility of the proposed method, including the same system order and reduced order structures. It is concluded from several simulation results that the proposed method has an excellent performance on solving the IIR digital modeling problem.

Differential evolution-based nonlinear system modeling using a bilinear series model

This paper presents a new modeling method for nonlinear dynamic systems based on using bilinear series model. Basically, bilinear model is an extension of infinite impulse response (IIR) filter and belongs to the recursive nonlinear system model, i.e., its past output signals will heavily affect the present output. This kind of model can efficiently approximate a large class of nonlinear systems with fewer parameters than other non-recursive models. To adjust the model kernels, we here adopt an evolutionary computation called the differential evolution (DE) algorithm. This algorithm is based on real-valued manipulations and has a good convergence property for finding the global solution or the near global solution of optimized problem. Design steps of DE-based nonlinear system modeling are clearly given in this study. Finally, two kinds of digital systems are illustrated to demonstrate the efficiency of the proposed method.