441 research outputs found
Homomorphic Data Isolation for Hardware Trojan Protection
The interest in homomorphic encryption/decryption is increasing due to its
excellent security properties and operating facilities. It allows operating on
data without revealing its content. In this work, we suggest using homomorphism
for Hardware Trojan protection. We implement two partial homomorphic designs
based on ElGamal encryption/decryption scheme. The first design is a
multiplicative homomorphic, whereas the second one is an additive homomorphic.
We implement the proposed designs on a low-cost Xilinx Spartan-6 FPGA. Area
utilization, delay, and power consumption are reported for both designs.
Furthermore, we introduce a dual-circuit design that combines the two earlier
designs using resource sharing in order to have minimum area cost. Experimental
results show that our dual-circuit design saves 35% of the logic resources
compared to a regular design without resource sharing. The saving in power
consumption is 20%, whereas the number of cycles needed remains almost the sam
Experimental Simulation for Load Reduction Techniques on Underground Utilities using Geofoam
This paper investigates an experimental study on reducing stress acting on buried flexible pipes by using expanded polystyrene (EPS) geofoam techniques. An experimental model was carried out with dimensions depending on pipe diameter (D) and location, the used fill cover material was from sand and EPS blocks either embankment form, or within sand backfill as embedded layer. The pipe flexible is un-plasticized polyvinyl chloride (UPVC). A series of experiments have been carried out by using static surface loading on rectangular steel plate,where the load is distributed over the backfill. The behavior of sand backfill around the pipe was observed, and the displacement and strains of the pipe were measured. The experimental results showed that the embedded layer of EPS geofoam block embedded in sand for different techniques reduced the deformation of flexible buried pipe, with high efficiency and low coast compared with EPS geofoam only. The results reveal that, the most effective methods thatcanreduce the stress on buried flexible pipe with low cost were EPS encasement block with head void method, and EPS block embraces the upper part of pipe method
The concept of direct adaptive control for improving voltage and frequency regulation loops in several power system applications
Authenticated public key elliptic curve based on deep convolutional neural network for cybersecurity image encryption application
The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE algorithm. Moreover, the 3D Quantum Chaotic Logistic Map (3D QCLM) has an extremely chaotic behavior of the bifurcation diagram and high Lyapunov exponent, which can be used in high-level security. In addition, in order to achieve the authentication property, the secure hash function uses the output sequence of the DCNN and the output sequence of the 3D QCLM in the proposed authenticated expansion diffusion matrix (AEDM). Finally, partial frequency domain encryption (PFDE) technique is achieved by using the discrete wavelet transform in order to satisfy the robustness and fast encryption process. Simulation results and security analysis demonstrate that the proposed encryption algorithm achieved the performance of the state-of-the-art techniques in terms of quality, security, and robustness against noise- and signal-processing attacks
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