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1. Implementation of Chaotic Encryption Architecture on FPGA for On-Chip Secure Communication

   https://doi.org/10.1109/IGESSC55810.2022.9955334  

   Monani, Ravi; Rogers, Brian; Rezaei, Amin; Hedayatipour, Ava (July 2022, IEEE Green Energy and Systems Conference IGESC)

   Chaos is an interesting phenomenon for nonlinear systems that emerges due to its complex and unpredictable behavior. With the escalated use of low-powered edge-compute devices, data security at the edge develops the need for security in communication. The characteristic that Chaos synchronizes over time for two different chaotic systems with their own unique initial conditions, is the base for chaos implementation in communication. This paper proposes an encryption architecture suitable for communication of on-chip sensors to provide a POC (proof of concept) with security encrypted on the same chip using different chaotic equations. In communication, encryption is achieved with the help of microcontrollers or software implementations that use more power and have complex hardware implementation. The small IoT devices are expected to be operated on low power and constrained with size. At the same time, these devices are highly vulnerable to security threats, which elevates the need to have low power/size hardware-based security. Since the discovery of chaotic equations, they have been used in various encryption applications. The goal of this research is to take the chaotic implementation to the CMOS level with the sensors on the same chip. The hardware co-simulation is demonstrated on an FPGA board for Chua encryption/decryption architecture. The hardware utilization for Lorenz, SprottD, and Chua on FPGA is achieved with Xilinx System Generation (XSG) toolbox which reveals that Lorenz’s utilization is ~9% lesser than Chua’s. 

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2. Attacks on Continuous Chaos Communication and Remedies for Resource Limited Devices

   https://doi.org/10.1109/isqed57927.2023.10129355  

   Vishwakarma, Rahul; Monani, Ravi; Rezaei, Amin; Sayadi, Hossein; Aliasgari, Mehrdad; Hedayatipour, Ava (April 2023, 2023 24th International Symposium on Quality Electronic Design (ISQED))

   The Global Wearable market is anticipated to rise at a considerable rate in the next coming years and communication is a fundamental block in any wearable device. In communication, encryption methods are being used with the aid of microcontrollers or software implementations, which are power-consuming and incorporate complex hardware implementation. Internet of Things (IoT) devices are considered as resource-constrained devices that are expected to operate with low computational power and resource utilization criteria. At the same time, recent research has shown that IoT devices are highly vulnerable to emerging security threats, which elevates the need for low-power and small-size hardware-based security countermeasures. Chaotic encryption is a method of data encryption that utilizes chaotic systems and non-linear dynamics to generate secure encryption keys. It aims to provide high-level security by creating encryption keys that are sensitive to initial conditions and difficult to predict, making it challenging for unauthorized parties to intercept and decode encrypted data. Since the discovery of chaotic equations, there have been various encryption applications associated with them. In this paper, we comprehensively analyze the physical and encryption attacks on continuous chaotic systems in resource-constrained devices and their potential remedies. To this aim, we introduce different categories of attacks of chaotic encryption. Our experiments focus on chaotic equations implemented using Chua’s equation and leverages circuit architectures and provide simulations proof of remedies for different attacks. These remedies are provided to block the attackers from stealing users’ information (e.g., a pulse message) with negligible cost to the power and area of the design. 

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3. Reliable and secure memristor-based chaotic communication against eavesdroppers and untrusted foundries

   https://doi.org/10.1007/s43926-023-00029-2  

   Vishwakarma, Rahul; Monani, Ravi; Hedayatipour, Ava; Rezaei, Amin (December 2023, Discover Internet of Things)

   Abstract Chaos is a deterministic phenomenon that occurs in a non-linear dynamic system under specific condition when the trajectories of the state vector become periodic and extremely sensitive to the initial conditions. While traditional resistor-based chaotic communications are primarily concerned with the safe transfer of information across networks, the transceivers themselves can be compromised due to outsource manufacturing. With the growth of wireless sensors in resource-constrained implantable and wearable devices, chaotic communication may be a good fit if the information transmitted is reliable and the transmitter devices are secure. We believe that memristor, as the fourth fundamental two-terminal circuit element, can close the gap between reliable communication and secure manufacturing since its resistance can be programmed and saved by the designer and not the foundry. Thus, in this paper, we propose a memristor-based Chua’s chaotic transceiver that is both reliable in the presence of eavesdroppers and secure against untrusted foundries. Specifically, we consider the pair of transmitter and receiver under the same memristor value to show the possibility of uninterrupted communication as well as cases where different values of memristors are used to find out the possible range in which the message can still be meaningfully decoded. Experimental results confirm that both reliable communication and secure design can be achieved via our proposed memristor-based chaos transceivers. 

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4. Enhancing Continuous Chaos Communication Using Machine Learning in Resource-Limited Devices

   https://doi.org/10.1109/dcas57389.2023.10130267  

   Hwang, Jinha; Hosseinzadeh, Nima; Hedayatipour, Ava (April 2023, 2023 IEEE 16th Dallas Circuits and Systems Conference (DCAS))

   Machine learning is rapidly finding its way into the solving of everyday complex problems. One such application is in the area of chaotic encryption, where machine learning techniques can be used to improve the security and synchronization of encryption algorithms. Chaotic encryption is a technique that uses chaos theory to encrypt messages communicated between a transmitter and a receiver, making them extremely difficult to decipher without the correct decryption key. Here, we first discuss error correction for chaotic synchronization using conventional methods with an accuracy of 86%. We then use machine learning algorithms to reduce the error of the decrypted message extracted by learning patterns in the encrypted message and adjusting the encryption parameters accordingly. Using linear regression, k-mean, and DB-Scan, We present an increase in the original accuracy achieved by the decrypted message. Additionally, we use machine learning algorithms to detect anomalies in encrypted messages. The use of machine learning in chaotic encryption has the potential to greatly improve the security of encryption algorithms. 

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5. Si0.97Ge0.03 microelectronic thermoelectric generators with high power and voltage densities

   https://doi.org/10.1038/s41467-020-18122-3  

   Dhawan, Ruchika; Madusanka, Prabuddha; Hu, Gangyi; Debord, Jeff; Tran, Toan; Maggio, Kenneth; Edwards, Hal; Lee, Mark (August 2020, Nature Communications)

   Abstract Microelectronic thermoelectric generators are one potential solution to energizing energy autonomous electronics, such as internet-of-things sensors, that must carry their own power source. However, thermoelectric generators with the mm²footprint area necessary for on-chip integration made from high thermoelectric figure-of-merit materials have been unable to produce the voltage and power levels required to run Si electronics using common temperature differences. We present microelectronic thermoelectric generators using Si_0.97Ge_0.03, made by standard Si processing, with high voltage and power generation densities that are comparable to or better than generators using high figure-of-merit materials. These Si-based thermoelectric generators have <1 mm²areas and can energize off-the-shelf sensor integrated circuits using temperature differences ≤25 K near room temperature. These generators can be directly integrated with Si circuits and scaled up in area to generate voltages and powers competitive with existing thermoelectric technologies, but in what should be a far more cost-effective manner. 

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