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

Reliable Delay Based Algorithm to Boost PUF Security Against Modeling Attacks

Silicon Physical Unclonable Functions (sPUFs) are one of the security primitives and state-of-the-art topics in hardware-oriented security and trust research. This paper presents an efficient and dynamic ring oscillator PUFs (d-ROPUFs) technique to improve sPUFs security against modeling attacks. In addition to enhancing the Entropy of weak ROPUF design, experimental results show that the proposed d-ROPUF technique allows the generation of larger and updated challenge-response pairs (CRP space) compared with simple ROPUF. Additionally, an innovative hardware-oriented security algorithm, namely, the Optimal Time Delay Algorithm (OTDA), is proposed. It is demonstrated that the OTDA algorithm significantly improves PUF reliability under varying operating conditions. Further, it is shown that the OTDA further efficiently enhances the d-ROPUF capability to generate a considerably large set of reliable secret keys to protect the PUF structure from new cyber-attacks, including machine learning and modeling attacks