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This article introduces a novel, low-cost technique for hiding data in commercially available resistive-RAM (ReRAM) chips. The data is kept hidden in ReRAM cells by manipulating its analog physical properties through switching (set/reset) operations. This hidden data, later, is retrieved by sensing the changes in cells' physical properties (i.e., set/reset time of the memory cells). The proposed system-level hiding technique does not affect the normal memory operations and does not require any hardware modifications. Furthermore, the proposed hiding approach is robust against temperature variations and the aging of the devices through normal read/write operation. The silicon results show that our proposed data hiding technique is acceptably fast with ∼0.4bit/min of encoding and ∼15.625bits/s of retrieval rates, and the hidden message is unrecoverable without the knowledge of the secret key, which is used to enhance the security of hidden information.

Many commercially available memory chips are fabricated worldwide in untrusted facilities. Therefore, a counterfeit memory chip can easily enter into the supply chain in different formats. Deploying these counterfeit memory chips into an electronic system can severely affect security and reliability domains because of their sub-standard quality, poor performance, and shorter lifespan. Therefore, a proper solution is required to identify counterfeit memory chips before deploying them in mission-, safety-, and security-critical systems. However, a single solution to prevent counterfeiting is challenging due to the diversity of counterfeit types, sources, and refinement techniques. Besides, the chips can pass initial testing and still fail while being used in the system. Furthermore, existing solutions focus on detecting a single counterfeit type (e.g., detecting recycled memory chips). This work proposes a framework that detects major counterfeit static random-access memory (SRAM) types by attesting/identifying the origin of the manufacturer. The proposed technique generates a single signature for a manufacturer and does not require any exhaustive registration/authentication process. We validate our proposed technique using 345 SRAM chips produced by major manufacturers. The silicon results show that the test scores ( F 1 score) of our proposed technique of identifying memory manufacturer and part-number are 93% and 71%, respectively.