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Journal of Advanced Research in Applied Sciences and Engineering Technology, Dec 20, 2023
Today's device authentications in IoT devices use public and private key cryptography. Neverthele... more Today's device authentications in IoT devices use public and private key cryptography. Nevertheless, they are still vulnerable to threats because keys or device IDs digitally stored in IoT devices can be stolen or cloned. In contrast, SRAM PUFs utilize physical variations in memory cells of embedded SRAM in microcontrollers or standalone SRAM chips. These inherent physical characteristics are unpredictable and practically impossible to duplicate. They are negligible to affect regular SRAM operation but large enough to be used for authentication purposes in SRAM PUFs operation. However, SRAM PUFs have poor stability and a relatively high bit error rate (BER). Temporal Majority Voting (TMV) and other error correction codes (ECCs) have improved SRAM PUFs performance, but they require a lot of processing time and hardware resources. The data remanence nature of SRAM cells can be utilized to select SRAM PUFs bits with much lower BER and more stable bits, but a suitable algorithm is required to find the best possible power-off time for each type of chip. This paper proposes using the data remanence method and binary search algorithm to obtain the strong SRAM PUFs characteristics of the selected SRAMs at the optimal power-off time. These SRAMs include embedded SRAMs of AtMega328P, STM32F108C, ESP8266 microcontrollers, and an off-the-shelf SRAM chip 23LC1024-I/P, which are being used in various IoT applications. The strong SRAM PUF has more stable characteristics that reduce BER to 0% and increase stability to 99.999%. This proposed method can be utilized on any IoT platform which deals with essential data and requires less resource-hungry security and authentication protocols.
Journal of Advanced Research in Applied Sciences and Engineering Technology, 2024
Today's device authentications in IoT devices use public and private key cryptography. Neverthele... more Today's device authentications in IoT devices use public and private key cryptography. Nevertheless, they are still vulnerable to threats because keys or device IDs digitally stored in IoT devices can be stolen or cloned. In contrast, SRAM PUFs utilize physical variations in memory cells of embedded SRAM in microcontrollers or standalone SRAM chips. These inherent physical characteristics are unpredictable and practically impossible to duplicate. They are negligible to affect regular SRAM operation but large enough to be used for authentication purposes in SRAM PUFs operation. However, SRAM PUFs have poor stability and a relatively high bit error rate (BER). Temporal Majority Voting (TMV) and other error correction codes (ECCs) have improved SRAM PUFs performance, but they require a lot of processing time and hardware resources. The data remanence nature of SRAM cells can be utilized to select SRAM PUFs bits with much lower BER and more stable bits, but a suitable algorithm is required to find the best possible power-off time for each type of chip. This paper proposes using the data remanence method and binary search algorithm to obtain the strong SRAM PUFs characteristics of the selected SRAMs at the optimal power-off time. These SRAMs include embedded SRAMs of AtMega328P, STM32F108C, ESP8266 microcontrollers, and an off-the-shelf SRAM chip 23LC1024-I/P, which are being used in various IoT applications. The strong SRAM PUF has more stable characteristics that reduce BER to 0% and increase stability to 99.999%. This proposed method can be utilized on any IoT platform which deals with essential data and requires less resource-hungry security and authentication protocols.
Better security is essential for IoT devices these days. Device authentication of IoT devices can... more Better security is essential for IoT devices these days. Device authentication of IoT devices can be done by using Static Random-Access Memory Physical Unclonable Functions (SRAM PUF). However, SRAM PUF has poor stability and relatively high error rate. Temporal Majority Voting (TMV) and other Error Correction Codes (ECCs) has been used to improve SRAM PUF performance. But they require a lot of processing time and hardware resources. Most of the microcontrollers used in IoT devices do not have that. Still, those methods cannot produce sufficiently stable bits of SRAM PUF. The data remanence nature of SRAM cells can be utilized to generate much more stable SRAM PUF with low error rates. In this paper, we made use of both TMV and data remanence to obtain SRAM PUF characteristics of microcontrollers used in IoT devices. The characteristics of SRAM PUF such as biasness, uniqueness and stability have been analyzed and investigated for better understanding of SRAM PUF on different chips. ...
Journal of Advanced Research in Applied Sciences and Engineering Technology, Dec 20, 2023
Today's device authentications in IoT devices use public and private key cryptography. Neverthele... more Today's device authentications in IoT devices use public and private key cryptography. Nevertheless, they are still vulnerable to threats because keys or device IDs digitally stored in IoT devices can be stolen or cloned. In contrast, SRAM PUFs utilize physical variations in memory cells of embedded SRAM in microcontrollers or standalone SRAM chips. These inherent physical characteristics are unpredictable and practically impossible to duplicate. They are negligible to affect regular SRAM operation but large enough to be used for authentication purposes in SRAM PUFs operation. However, SRAM PUFs have poor stability and a relatively high bit error rate (BER). Temporal Majority Voting (TMV) and other error correction codes (ECCs) have improved SRAM PUFs performance, but they require a lot of processing time and hardware resources. The data remanence nature of SRAM cells can be utilized to select SRAM PUFs bits with much lower BER and more stable bits, but a suitable algorithm is required to find the best possible power-off time for each type of chip. This paper proposes using the data remanence method and binary search algorithm to obtain the strong SRAM PUFs characteristics of the selected SRAMs at the optimal power-off time. These SRAMs include embedded SRAMs of AtMega328P, STM32F108C, ESP8266 microcontrollers, and an off-the-shelf SRAM chip 23LC1024-I/P, which are being used in various IoT applications. The strong SRAM PUF has more stable characteristics that reduce BER to 0% and increase stability to 99.999%. This proposed method can be utilized on any IoT platform which deals with essential data and requires less resource-hungry security and authentication protocols.
Journal of Advanced Research in Applied Sciences and Engineering Technology, 2024
Today's device authentications in IoT devices use public and private key cryptography. Neverthele... more Today's device authentications in IoT devices use public and private key cryptography. Nevertheless, they are still vulnerable to threats because keys or device IDs digitally stored in IoT devices can be stolen or cloned. In contrast, SRAM PUFs utilize physical variations in memory cells of embedded SRAM in microcontrollers or standalone SRAM chips. These inherent physical characteristics are unpredictable and practically impossible to duplicate. They are negligible to affect regular SRAM operation but large enough to be used for authentication purposes in SRAM PUFs operation. However, SRAM PUFs have poor stability and a relatively high bit error rate (BER). Temporal Majority Voting (TMV) and other error correction codes (ECCs) have improved SRAM PUFs performance, but they require a lot of processing time and hardware resources. The data remanence nature of SRAM cells can be utilized to select SRAM PUFs bits with much lower BER and more stable bits, but a suitable algorithm is required to find the best possible power-off time for each type of chip. This paper proposes using the data remanence method and binary search algorithm to obtain the strong SRAM PUFs characteristics of the selected SRAMs at the optimal power-off time. These SRAMs include embedded SRAMs of AtMega328P, STM32F108C, ESP8266 microcontrollers, and an off-the-shelf SRAM chip 23LC1024-I/P, which are being used in various IoT applications. The strong SRAM PUF has more stable characteristics that reduce BER to 0% and increase stability to 99.999%. This proposed method can be utilized on any IoT platform which deals with essential data and requires less resource-hungry security and authentication protocols.
Better security is essential for IoT devices these days. Device authentication of IoT devices can... more Better security is essential for IoT devices these days. Device authentication of IoT devices can be done by using Static Random-Access Memory Physical Unclonable Functions (SRAM PUF). However, SRAM PUF has poor stability and relatively high error rate. Temporal Majority Voting (TMV) and other Error Correction Codes (ECCs) has been used to improve SRAM PUF performance. But they require a lot of processing time and hardware resources. Most of the microcontrollers used in IoT devices do not have that. Still, those methods cannot produce sufficiently stable bits of SRAM PUF. The data remanence nature of SRAM cells can be utilized to generate much more stable SRAM PUF with low error rates. In this paper, we made use of both TMV and data remanence to obtain SRAM PUF characteristics of microcontrollers used in IoT devices. The characteristics of SRAM PUF such as biasness, uniqueness and stability have been analyzed and investigated for better understanding of SRAM PUF on different chips. ...