Tobias Kovats, Navaneeth Rameshan, Kumudu Geethan Karunaratne, Iason Giannopoulos, Abu Sebastian
{"title":"使用高级加密标准的内存加密。","authors":"Tobias Kovats, Navaneeth Rameshan, Kumudu Geethan Karunaratne, Iason Giannopoulos, Abu Sebastian","doi":"10.1098/rsta.2023.0396","DOIUrl":null,"url":null,"abstract":"<p><p>Encryption and decryption of data with very low latency and high energy efficiency is desirable in almost every application that deals with sensitive data. The advanced encryption standard (AES) is a widely adopted algorithm in symmetric key cryptography with numerous efficient implementations. Nonetheless, in scenarios involving extensive data processing, the primary limitations on performance and efficiency arise from data movement between memory and the processor, rather than data processing itself. In this article, we present a novel in-memory computing (IMC) approach for AES encryption and key-expansion, and experimentally validate it on an IMC prototype chip based on phase-change memory (PCM) technology. We leverage operators stored in PCM crossbar arrays to achieve the flexibility to tune performance at runtime based on the amount of free storage available in the memory system. In addition, we introduce a method for parallel in-memory polynomial modular multiplication and evaluate the potential of intrinsic stochastic properties of PCM devices for random key generation. We show how to further improve efficiency with minimal additional auxiliary circuitry. To evaluate the performance within a custom-built large-scale in-memory AES system, we design and implement a cycle-accurate simulator that integrates parameters from Spice simulations for detailed latency and energy consumption analysis of the AES algorithm. Our evaluations indicate that our IMC-based AES approach outperforms state-of-the-art methods, achieving speed factor improvements of up to 19.7 at equivalent energy efficiency.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.</p>","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2288","pages":"20230396"},"PeriodicalIF":4.3000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In-memory encryption using the advanced encryption standard.\",\"authors\":\"Tobias Kovats, Navaneeth Rameshan, Kumudu Geethan Karunaratne, Iason Giannopoulos, Abu Sebastian\",\"doi\":\"10.1098/rsta.2023.0396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Encryption and decryption of data with very low latency and high energy efficiency is desirable in almost every application that deals with sensitive data. The advanced encryption standard (AES) is a widely adopted algorithm in symmetric key cryptography with numerous efficient implementations. Nonetheless, in scenarios involving extensive data processing, the primary limitations on performance and efficiency arise from data movement between memory and the processor, rather than data processing itself. In this article, we present a novel in-memory computing (IMC) approach for AES encryption and key-expansion, and experimentally validate it on an IMC prototype chip based on phase-change memory (PCM) technology. We leverage operators stored in PCM crossbar arrays to achieve the flexibility to tune performance at runtime based on the amount of free storage available in the memory system. In addition, we introduce a method for parallel in-memory polynomial modular multiplication and evaluate the potential of intrinsic stochastic properties of PCM devices for random key generation. We show how to further improve efficiency with minimal additional auxiliary circuitry. To evaluate the performance within a custom-built large-scale in-memory AES system, we design and implement a cycle-accurate simulator that integrates parameters from Spice simulations for detailed latency and energy consumption analysis of the AES algorithm. Our evaluations indicate that our IMC-based AES approach outperforms state-of-the-art methods, achieving speed factor improvements of up to 19.7 at equivalent energy efficiency.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.</p>\",\"PeriodicalId\":19879,\"journal\":{\"name\":\"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences\",\"volume\":\"383 2288\",\"pages\":\"20230396\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1098/rsta.2023.0396\",\"RegionNum\":3,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1098/rsta.2023.0396","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
In-memory encryption using the advanced encryption standard.
Encryption and decryption of data with very low latency and high energy efficiency is desirable in almost every application that deals with sensitive data. The advanced encryption standard (AES) is a widely adopted algorithm in symmetric key cryptography with numerous efficient implementations. Nonetheless, in scenarios involving extensive data processing, the primary limitations on performance and efficiency arise from data movement between memory and the processor, rather than data processing itself. In this article, we present a novel in-memory computing (IMC) approach for AES encryption and key-expansion, and experimentally validate it on an IMC prototype chip based on phase-change memory (PCM) technology. We leverage operators stored in PCM crossbar arrays to achieve the flexibility to tune performance at runtime based on the amount of free storage available in the memory system. In addition, we introduce a method for parallel in-memory polynomial modular multiplication and evaluate the potential of intrinsic stochastic properties of PCM devices for random key generation. We show how to further improve efficiency with minimal additional auxiliary circuitry. To evaluate the performance within a custom-built large-scale in-memory AES system, we design and implement a cycle-accurate simulator that integrates parameters from Spice simulations for detailed latency and energy consumption analysis of the AES algorithm. Our evaluations indicate that our IMC-based AES approach outperforms state-of-the-art methods, achieving speed factor improvements of up to 19.7 at equivalent energy efficiency.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.
期刊介绍:
Continuing its long history of influential scientific publishing, Philosophical Transactions A publishes high-quality theme issues on topics of current importance and general interest within the physical, mathematical and engineering sciences, guest-edited by leading authorities and comprising new research, reviews and opinions from prominent researchers.