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Journal articles on the topic 'Trusted Execution Environments (TEEs)'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Abhilash, Kayyidavazhiyil, and Kaipacheri Sheena. "Trusted Execution Environments for Internet of Things Devices." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 11, no. 6 (2022): 45–48. https://doi.org/10.35940/ijitee.F9885.0511622.

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<strong>Abstract: </strong>A trusted execution Environment (TEE) could be a comfy place of a computer’s essential processor that's designed to shield the most touchy information and operations. TEEs are utilized in an expansion of applications, which incorporates cell gadgets, price processing, and statistics safety. The usage of TEEs is becoming increasingly crucial because the amount of touchy records that are processed and stored electronically continues to develop. TEEs can help guard statistics from being accessed or changed with the resource of unauthorised customers, and can a

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Subramanyan, Bala. "Object Capability Model for Tee: A Cheri Based Compartmentalization Approach." International Journal of Security, Privacy and Trust Management 12, no. 3/4 (2023): 23–30. http://dx.doi.org/10.5121/ijsptm.2023.12402.

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In this paper, we introduce a capability-driven approach to bolster security and granularity within Trusted Execution Environments (TEEs) [1]. By delivering precise privilege control and fine-grained compartmentalization, we aim to improve TEE security standards. To address vulnerabilities within Trusted Execution Environments (TEEs) and enable selective privilege management and secure object sharing between secure and normal worlds, we introduce a TEE compartmentalization framework based on the CHERI object-capability model. Leveraging DSbD technologies, our framework provides an efficient pr

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Wen, Sheng, Liam Xu, Liwei Tian, Suping Liu, and Yong Ding. "TeeDFuzzer: Fuzzing Trusted Execution Environment." Electronics 14, no. 8 (2025): 1674. https://doi.org/10.3390/electronics14081674.

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The Trusted Execution Environment (TEE) is crucial for safeguarding the ecosystem of embedded systems. It uses isolation to minimize the TCB (Trusted Computing Base) and protect sensitive software. It is vital because devices handle vast, potentially sensitive data. Leveraging ARM TrustZone, widely used in mobile and IoT for TEEs, it ensures hardware protection via security extensions, though needing firmware and software stack support. Despite the reputation of TEEs for high security, TrustZone-aided ones have vulnerabilities. Fuzzing, as a practical bug-finding technique, has seen limited re

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Musale, Pratik, and Adam Lee. "Trust TEE?: Exploring the Impact of Trusted Execution Environments on Smart Home Privacy Norms." Proceedings on Privacy Enhancing Technologies 2023, no. 3 (2023): 5–23. http://dx.doi.org/10.56553/popets-2023-0067.

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IoT devices like smart cameras and speakers provide convenience but can collect sensitive information within private spaces. While research has investigated user perception of comfort with information flows originating from these types of devices, little focus has been given to the role of the sensing hardware in influencing these sentiments. Given the proliferation of trusted execution environments (TEEs) across commodity- and server-class devices, we surveyed 1049 American adults using the Contextual Integrity framework to understand how the inclusion of cloud-based TEEs in IoT ecosystems ma

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Meftah, Souhail, Shuhao Zhang, Bharadwaj Veeravalli, and Khin Mi Mi Aung. "Revisiting the Design of Parallel Stream Joins on Trusted Execution Environments." Algorithms 15, no. 6 (2022): 183. http://dx.doi.org/10.3390/a15060183.

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The appealing properties of secure hardware solutions such as trusted execution environment (TEE) including low computational overhead, confidentiality guarantee, and reduced attack surface have prompted considerable interest in adopting them for secure stream processing applications. In this paper, we revisit the design of parallel stream join algorithms on multicore processors with TEEs. In particular, we conduct a series of profiling experiments to investigate the impact of alternative design choices to parallelize stream joins on TEE including: (1) execution approaches, (2) partitioning sc

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Han, Shumin, Kuixing Shen, Derong Shen, and Chuang Wang. "Enhanced Multi-Party Privacy-Preserving Record Linkage Using Trusted Execution Environments." Mathematics 12, no. 15 (2024): 2337. http://dx.doi.org/10.3390/math12152337.

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With the world’s data volume growing exponentially, it becomes critical to link it and make decisions. Privacy-preserving record linkage (PPRL) aims to identify all the record information corresponding to the same entity from multiple data sources, without disclosing sensitive information. Previous works on multi-party PPRL methods typically adopt homomorphic encryption technology due to its ability to perform computations on encrypted data without needing to decrypt it first, thus maintaining data confidentiality. However, these methods have notable shortcomings, such as the risk of collusion

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Singh, Jatinder, Jennifer Cobbe, Do Le Quoc, and Zahra Tarkhani. "Enclaves in the Clouds." Queue 18, no. 6 (2020): 78–114. http://dx.doi.org/10.1145/3442632.3448126.

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With organizational data practices coming under increasing scrutiny, demand is growing for mechanisms that can assist organizations in meeting their data-management obligations. TEEs (trusted execution environments) provide hardware-based mechanisms with various security properties for assisting computation and data management. TEEs are concerned with the confidentiality and integrity of data, code, and the corresponding computation. Because the main security properties come from hardware, certain protections and guarantees can be offered even if the host privileged software stack is vulnerabl

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Sasy, Sajin, Aaron Johnson, and Ian Goldberg. "TEEMS: A Trusted Execution Environment based Metadata-protected Messaging System." Proceedings on Privacy Enhancing Technologies 2025, no. 4 (2025): 56–75. https://doi.org/10.56553/popets-2025-0119.

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Ensuring privacy of online messaging remains a challenge. While the contents or data of online communications are often protected by end-to-end encryption, the metadata of communications are not. Metadata such as who is communicating with whom, how much, and how often, are leaked by popular messaging systems today. In the last four decades we have witnessed a rich literature of designs towards metadata-protecting communications systems (MPCS). While recent MPCS works often target metadata-protected messaging systems, no existing construction simultaneously attains four desirable properties for

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Maliszewski, Kajetan, Jorge-Arnulfo Quiané-Ruiz, Jonas Traub, and Volker Markl. "What is the price for joining securely?" Proceedings of the VLDB Endowment 15, no. 3 (2021): 659–72. http://dx.doi.org/10.14778/3494124.3494146.

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Protection of personal data has been raised to be among the top requirements of modern systems. At the same time, it is now frequent that the owner of the data and the owner of the computing infrastructure are two entities with limited trust between them (e. g., volunteer computing or the hybrid-cloud). Recently, trusted execution environments (TEEs) became a viable solution to ensure the security of systems in such environments. However, the performance of relational operators in TEEs remains an open problem. We conduct a comprehensive experimental study to identify the main bottlenecks and c

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Crocetti, Luca, Pietro Nannipieri, Stefano Di Matteo, and Sergio Saponara. "Design Methodology and Metrics for Robust and Highly Qualified Security Modules in Trusted Environments." Electronics 12, no. 23 (2023): 4843. http://dx.doi.org/10.3390/electronics12234843.

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Cyberattacks and cybercriminal activities constitute one of the biggest threats in the modern digital era, and the frequency, efficiency, and severity of attacks have grown over the years. Designers and producers of digital systems try to counteract such issues by exploiting increasingly robust and advanced security mechanisms to provide secure execution environments aimed at preventing cyberattacks or, in the worst case, at containing intrusions by isolation. One of the most significative examples comes from General Purpose Processor (GPP) manufacturers such as Intel, AMD, and ARM, which in t

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Khurshid, Anum, Sileshi Demesie Yalew, Mudassar Aslam, and Shahid Raza. "TEE-Watchdog: Mitigating Unauthorized Activities within Trusted Execution Environments in ARM-Based Low-Power IoT Devices." Security and Communication Networks 2022 (May 25, 2022): 1–21. http://dx.doi.org/10.1155/2022/8033799.

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Trusted execution environments (TEEs) are on the rise in devices all around us ranging from large-scale cloud-based solutions to resource-constrained embedded devices. With the introduction of ARM TrustZone-M, hardware-assisted trusted execution is now supported in IoT nodes. TrustZone-M provides isolated execution of security-critical operations and sensitive data-generating peripherals. However, TrustZone-M, like all other TEEs, does not provide a mechanism to monitor operations in the trusted areas of the device and software in the secure areas of an IoT device has access to the entire secu

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Niu, Yue, Ramy E. Ali, and Salman Avestimehr. "3LegRace: Privacy-Preserving DNN Training over TEEs and GPUs." Proceedings on Privacy Enhancing Technologies 2022, no. 4 (2022): 183–203. http://dx.doi.org/10.56553/popets-2022-0105.

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Leveraging parallel hardware (e.g. GPUs) for deep neural network (DNN) training brings high computing performance. However, it raises data privacy concerns as GPUs lack a trusted environment to protect the data. Trusted execution environments (TEEs) have emerged as a promising solution to achieve privacypreserving learning. Unfortunately, TEEs’ limited computing power renders them not comparable to GPUs in performance. To improve the trade-off among privacy, computing performance, and model accuracy, we propose an asymmetric model decomposition framework, AsymML, to (1) accelerate training usi

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Bocci, Alessandro, Stefano Forti, Roberto Guanciale, Gian-Luigi Ferrari, and Antonio Brogi. "Secure Partitioning of Cloud Applications, with Cost Look-Ahead." Future Internet 15, no. 7 (2023): 224. http://dx.doi.org/10.3390/fi15070224.

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The security of Cloud applications is a major concern for application developers and operators. Protecting users’ data confidentiality requires methods to avoid leakage from vulnerable software and unreliable Cloud providers. Recently, trusted execution environments (TEEs) emerged in Cloud settings to isolate applications from the privileged access of Cloud providers. Such hardware-based technologies exploit separation kernels, which aim at safely isolating the software components of applications. In this article, we propose a methodology to determine safe partitionings of Cloud applications t

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Liu, Songran, Nan Guan, Zhishan Guo, and Wang Yi. "MiniTEE—A Lightweight TrustZone-Assisted TEE for Real-Time Systems." Electronics 9, no. 7 (2020): 1130. http://dx.doi.org/10.3390/electronics9071130.

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While trusted execution environments (TEEs) provide industry standard security and isolation, TEE requests through secure monitor calls (SMCs) attribute to large time overhead and weakened temporal predictability. Moreover, as current available TEE solutions are designed for Linux and/or Android initially, it will encounter many constraints (e.g., driver libraries incompatible, large memory footprint, etc.) when integrating with low-end Real-Time Operating Systems, RTOSs. In this paper, we present MiniTEE to understand, evaluate and discuss the benefits and limitations when integrating TrustZo

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Dr., Harish Joshi, Ashok Bawge Prof., Uzma Kausar Prof., et al. "SARA: Safe Remote Authorization for Android." Research and Applications: Emerging Technologies 7, no. 2 (2025): 28–38. https://doi.org/10.5281/zenodo.15590555.

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<em>Modern smartphones now come equipped with Trusted Execution Environments (TEEs), which provide robust security even against attackers with full control over the standard operating system, such as Linux on Android. While both researchers and manufacturers have proposed using TEEs to enhance authorization security, these approaches often fall short due to practical limitations and incomplete security guarantees. To overcome these challenges, this paper introduces SARA (Secure Android Remote Authorization), an Android library that leverages existing TEE-supported Android APIs to provide secur

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Pereira, Sérgio, Tiago Gomes, Jorge Cabral, and Sandro Pinto. "TREE: Bridging the gap between reconfigurable computing and secure execution." IACR Transactions on Cryptographic Hardware and Embedded Systems 2025, no. 3 (2025): 115–38. https://doi.org/10.46586/tches.v2025.i3.115-138.

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Trusted Execution Environments (TEEs) have become a pivotal technology for securing a wide spectrum of security-sensitive applications. With modern computing systems shifting to heterogeneous architectures, integrating TEE support into these systems is paramount. One promising line of research has proposed leveraging FPGA technology to provide promising TEE solutions. Despite their potential, current implementations of FPGA-based TEEs have a set of drawbacks. Some solutions (i.e., MeetGo and ShEF) prioritize the secure loading of reconfigurable modules but lack compatibility with established l

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Choi, Joseph I., and Kevin R. B. Butler. "Secure Multiparty Computation and Trusted Hardware: Examining Adoption Challenges and Opportunities." Security and Communication Networks 2019 (April 2, 2019): 1–28. http://dx.doi.org/10.1155/2019/1368905.

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When two or more parties need to compute a common result while safeguarding their sensitive inputs, they use secure multiparty computation (SMC) techniques such as garbled circuits. The traditional enabler of SMC is cryptography, but the significant number of cryptographic operations required results in these techniques being impractical for most real-time, online computations. Trusted execution environments (TEEs) provide hardware-enforced isolation of code and data in use, making them promising candidates for making SMC more tractable. This paper revisits the history of improvements to SMC o

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Ritesh, Kumar. "Confidential Computing in Public Cloud: Architectures for Privacy-Preserving Workloads." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 11, no. 3 (2025): 1–11. https://doi.org/10.5281/zenodo.15437185.

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Confidential computing is rapidly emerging as a critical technology for enabling privacy-preserving workloads in public cloud environments. By leveraging hardware-based trusted execution environments (TEEs), sensitive data can remain encrypted in memory during processing, significantly mitigating risks associated with cloud provider access, malicious insiders, and advanced persistent threats. This paper explores architectural patterns and design considerations for deploying privacy-sensitive applications utilizing confidential computing capabilities offered by major public cloud providers. We

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Ravindar, Reddy Gopireddy. "Confidential Computing: The Key to Secure Data Collaboration in the Cloud." Journal of Scientific and Engineering Research 10, no. 6 (2023): 271–76. https://doi.org/10.5281/zenodo.13348618.

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Data security and privacy are becoming particularly Read more... While most traditional security mechanisms address data at rest and in transit, they rarely help protect data during use. Confidential computing eliminates this key barrier by using hardware-based Trusted Execution Environments (TEEs) and secure enclaves to guard data at every stage of its journey. This research article decodes the principles and technology on which confining computing is founded, lately its utilization for augmenting cloud security, complications with solutions. Using some real-life cases and current trend analy

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Li, Xiang, Fabing Li, and Mingyu Gao. "Flare: A Fast, Secure, and Memory-Efficient Distributed Analytics Framework." Proceedings of the VLDB Endowment 16, no. 6 (2023): 1439–52. http://dx.doi.org/10.14778/3583140.3583158.

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As big data processing in the cloud becomes prevalent today, data privacy on such public platforms raises critical concerns. Hardware-based trusted execution environments (TEEs) provide promising and practical platforms for low-cost privacy-preserving data processing. However, using TEEs to enhance the security of data analytics frameworks like Apache Spark involves challenging issues when separating various framework components into trusted and untrusted domains, demanding meticulous considerations for programmability, performance, and security. Based on Intel SGX, we build Flare, a fast, sec

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Fei, Shufan, Zheng Yan, Wenxiu Ding, and Haomeng Xie. "Security Vulnerabilities of SGX and Countermeasures." ACM Computing Surveys 54, no. 6 (2021): 1–36. http://dx.doi.org/10.1145/3456631.

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Trusted Execution Environments (TEEs) have been widely used in many security-critical applications. The popularity of TEEs derives from its high security and trustworthiness supported by secure hardware. Intel Software Guard Extensions (SGX) is one of the most representative TEEs that creates an isolated environment on an untrusted operating system, thus providing run-time protection for the execution of security-critical code and data. However, Intel SGX is far from the acme of perfection. It has become a target of various attacks due to its security vulnerabilities. Researchers and practitio

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Janak Bharat Bhalla. "Safeguarding sensitive data with confidential computing." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 421–27. https://doi.org/10.30574/wjaets.2025.15.2.0505.

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Confidential computing emerges as a transformative solution in modern data protection, addressing critical vulnerabilities in cloud environments and digital infrastructure. By implementing hardware-based security mechanisms through Trusted Execution Environments (TEEs), organizations can now protect sensitive information throughout their entire computational lifecycle. The technology revolutionizes secure data processing across healthcare, financial services, government, and IoT sectors, enabling unprecedented levels of privacy and security. With innovations in homomorphic encryption, confiden

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Aliyu, Ahmed Abubakar, Mohammed Ibrahim, and Sa’adatu Abdulkadir. "A Blockchain‑Enhanced Deep Learning Approach for Intrusion Detection in Trusted Execution Environments." Digital Technologies Research and Applications 4, no. 1 (2025): 135–57. https://doi.org/10.54963/dtra.v4i1.962.

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Traditional Intrusion Detection Systems (IDSs) face significant challenges in keeping pace with the rapidly evolving landscape of cyber threats, primarily due to limitations in continuous learning and the accuracy of data classification and analysis. This often results in delayed detection and leaves networks susceptible to severe attacks. This paper introduces an innovative IDS empowered by blockchain technology to mitigate these shortcomings, leveraging continuous learning and self‑adaptive neural networks. The proposed system adopts a proactive approach by continuously assimilating intrusio

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Ashwini B N and Yashodha H R. "Optimizing data privacy and security in heterogeneous edge-to-cloud architectures: Leveraging confidential computing to enable secure distributed computations in decentralized environments." World Journal of Advanced Research and Reviews 6, no. 2 (2020): 275–80. https://doi.org/10.30574/wjarr.2020.6.2.0125.

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Data privacy and security in heterogeneous edge-to-cloud architectures have become increasingly critical due to the distributed nature of modern computing environments. Confidential computing techniques, such as trusted execution environments (TEEs) and homomorphic encryption, provide a promising approach to secure sensitive data while it is being processed across edge and cloud systems. However, challenges persist in achieving efficient and secure computations due to the dynamic and decentralized characteristics of these environments. This research proposes a novel framework that leverages co

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Reddy, Annapureddy Venkata Sai Kumar, and Gourinath Banda. "ElasticPay: Instant Peer-to-Peer Offline Extended Digital Payment System." Sensors 24, no. 24 (2024): 8034. https://doi.org/10.3390/s24248034.

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The widespread reliance on paper-based currency poses significant drawbacks, such as counterfeiting, lack of transparency, and environmental impacts. While Central Bank Digital Currencies (CBDCs) address many of these issues, their dependence on continuous internet connectivity limits their usability in scenarios with poor or no network access. To overcome such limitations, this paper introduces ElasticPay, a novel Peer-to-Peer (P2P) Offline Digital Payment System that leverages advanced hardware security measures realised through Trusted Platform Modules (TPMs), Trusted Execution Environments

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Gao, Haotian, Cong Yue, Tien Tuan Anh Dinh, Zhiyong Huang, and Beng Chin Ooi. "Enabling Secure and Efficient Data Analytics Pipeline Evolution with Trusted Execution Environment." Proceedings of the VLDB Endowment 16, no. 10 (2023): 2485–98. http://dx.doi.org/10.14778/3603581.3603589.

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Modern data analytics pipelines are highly dynamic, as they are constantly monitored and fine-tuned by both data engineers and scientists. Recent systems managing pipelines ease creating, deploying, and tracking their evolution. However, privacy concerns emerge as many of them are deployed on the public cloud with less or no trust. Unfortunately, the unique nature of pipelines prevents the adoption of existing confidential computing techniques with different computational patterns and large performance overhead. Being a potential approach, trusted execution environments (TEEs) are efficient in

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Koutroumpouchos, Nikolaos, Christoforos Ntantogian, and Christos Xenakis. "Building Trust for Smart Connected Devices: The Challenges and Pitfalls of TrustZone." Sensors 21, no. 2 (2021): 520. http://dx.doi.org/10.3390/s21020520.

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TrustZone-based Trusted Execution Environments (TEEs) have been utilized extensively for the implementation of security-oriented solutions for several smart intra and inter-connected devices. Although TEEs have been promoted as the starting point for establishing a device root of trust, a number of published attacks against the most broadly utilized TEE implementations request a second view on their security. The aim of this research is to provide an analytical and educational exploration of TrustZone-based TEE vulnerabilities with the goal of pinpointing design and implementation flaws. To th

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Peringanji, Deepika. "Unlocking the Future: Privacy-Preserving ML Experimentation." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 350–56. http://dx.doi.org/10.22214/ijraset.2024.60969.

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Abstract: Experiments with machine learning (ML) have become a key source of new ideas in many fields. However, growing worries about data privacy have made it clear that we need ML testing methods that protect privacy. There are new technologies in this piece that let you play around with machine learning without putting your data at risk. Differential privacy, secure multiparty computation (SMPC), homomorphic encryption, federated learning, trusted execution environments (TEEs), making fake data, and using temporary and nameless IDs are some of these technologies. By using these privacy-prot

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Jones, Michael, Matthew Johnson, Mark Shervey, Joel T. Dudley, and Noah Zimmerman. "Privacy-Preserving Methods for Feature Engineering Using Blockchain: Review, Evaluation, and Proof of Concept." Journal of Medical Internet Research 21, no. 8 (2019): e13600. http://dx.doi.org/10.2196/13600.

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Background The protection of private data is a key responsibility for research studies that collect identifiable information from study participants. Limiting the scope of data collection and preventing secondary use of the data are effective strategies for managing these risks. An ideal framework for data collection would incorporate feature engineering, a process where secondary features are derived from sensitive raw data in a secure environment without a trusted third party. Objective This study aimed to compare current approaches based on how they maintain data privacy and the practicalit

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KUM BERTRAND KUM, Dr. Austin Oguejiofor Amaechi, and Prof Tonye Emmanuel. "Securing National Cloud and Edge Infrastructure: A Case Study Inspired by Camtel (Cameroon)." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 5 (2025): 514–27. https://doi.org/10.51583/ijltemas.2025.140500054.

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Abstract: As cloud and edge computing evolve into foundational elements of national digital infrastructure, security concerns remain at the forefront, particularly in emerging markets like Cameroon. This study examines the security challenges within Camtel’s cloud-edge ecosystem, identifying critical vulnerabilities, evaluating mitigation strategies, and proposing a multi-layered security framework. We integrate AI-enhanced Intrusion Detection Systems (AI-IDS), Trusted Execution Environments (TEEs), and Blockchain-based audit logging to strengthen authentication, data integrity, and threat det

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Samarth Shah and Neil Choksi. "Confidential computing for serverless workloads: Secure and scalable data processing in untrusted environments." World Journal of Advanced Engineering Technology and Sciences 14, no. 3 (2025): 086–104. https://doi.org/10.30574/wjaets.2025.14.3.0067.

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Confidential Computing for Serverless Workloads: Secure and Scalable Data Processing in Untrusted Environments As the adoption of serverless architectures grows, the need to address data privacy and security concerns in cloud-based environments becomes critical. Serverless workloads, by design, allow developers to focus on code without managing infrastructure, leading to operational efficiency and scalability. However, this model introduces challenges related to the trustworthiness of the cloud provider, where sensitive data may be exposed to malicious actors within the system. Confidential co

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Stavrakakis, Dimitrios, Dimitra Giantsidi, Maurice Bailleu, Philip Sändig, Shady Issa, and Pramod Bhatotia. "Anchor: A Library for Building Secure Persistent Memory Systems." Proceedings of the ACM on Management of Data 1, no. 4 (2023): 1–31. http://dx.doi.org/10.1145/3626718.

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Cloud infrastructure is experiencing a shift towards disaggregated setups, especially with the introduction of the Compute Express Link (CXL) technology, where byte-addressable ersistent memory (PM) is becoming prominent. To fully utilize the potential of such devices, it is a necessity to access them through network stacks with equivalently high levels of performance (e.g., kernel-bypass, RDMA). While, these advancements are enabling the development of high-performance data management systems, their deployment on untrusted cloud environments also increases the security threats. To this end, w

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Kapsoulis, Nikolaos, Alexandros Psychas, Antonios Litke, and Theodora Varvarigou. "Reinforcing SLA Consensus on Blockchain." Computers 10, no. 12 (2021): 159. http://dx.doi.org/10.3390/computers10120159.

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Cloud Infrastructure as a Service (IaaS) Service Level Agreements (SLAs) assessment constitutes the de facto area of interest and applications in the public cloud infrastructure. However, the domination of colossal corporations tends to monopolize the way metrics and Key Performance Indicators (KPIs) are measured and determined, leading to governed environments where the clientele is unable to obtain accurate and unbiased assessment of SLAs. Leaning toward SLA self-assessment, this paper provides a fair SLA consensus approach with innate transparency and privacy by leveraging permissioned bloc

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Sabbani, Goutham. "Confidential Computing in the Cloud: An Overview." International Journal of Computing and Engineering 6, no. 3 (2024): 43–48. http://dx.doi.org/10.47941/ijce.2179.

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Major financial institutions like Goldman Sachs and JP Morgan have employed these hardware-based trusted execution environments (TEEs) and reported a 50% reduction in data breaches and a 40% increase in customer trust. Daily, these companies do billions of transactions in the cloud, leveraging confidentiality computing to ensure the privacy and integrity of their sensitive data. Over the years, confidential computing has evolved significantly, and the emergence of technology to safeguard sensitive information from malicious insiders and external threats now encompasses advanced and complex cry

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Kato, Fumiyuki, Yang Cao, and Masatoshi Yoshikawa. "Olive: Oblivious Federated Learning on Trusted Execution Environment against the Risk of Sparsification." Proceedings of the VLDB Endowment 16, no. 10 (2023): 2404–17. http://dx.doi.org/10.14778/3603581.3603583.

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Combining Federated Learning (FL) with a Trusted Execution Environment (TEE) is a promising approach for realizing privacy-preserving FL, which has garnered significant academic attention in recent years. Implementing the TEE on the server side enables each round of FL to proceed without exposing the client's gradient information to untrusted servers. This addresses usability gaps in existing secure aggregation schemes as well as utility gaps in differentially private FL. However, to address the issue using a TEE, the vulnerabilities of server-side TEEs need to be considered---this has not bee

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Cabrera-Gutiérrez, Antonio J., Encarnación Castillo, Antonio Escobar-Molero, Juan Cruz-Cozar, Diego P. Morales, and Luis Parrilla. "Secure Sensor Prototype Using Hardware Security Modules and Trusted Execution Environments in a Blockchain Application: Wine Logistic Use Case." Electronics 12, no. 13 (2023): 2987. http://dx.doi.org/10.3390/electronics12132987.

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The security of Industrial Internet of Things (IIoT) systems is a challenge that needs to be addressed immediately, as the increasing use of new communication paradigms and the abundant use of sensors opens up new opportunities to compromise these types of systems. In this sense, technologies such as Trusted Execution Environments (TEEs) and Hardware Security Modules (HSMs) become crucial for adding new layers of security to IIoT systems, especially to edge nodes that incorporate sensors and perform continuous measurements. These technologies, coupled with new communication paradigms such as B

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Gaud, Prof V. Y. "SeGShare: Secure Group File Sharing in the Cloud using Enclaves." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 1047–52. https://doi.org/10.22214/ijraset.2025.70327.

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File sharing applications using cloud storage are in- creasingly popular for personal and business use. Due to data pro- tection concerns, end-to-end encryption is often a desired feature of these applications. Many attempts at designing cryptographic solutions fail to be adopted due to missing relevant features. We present SeGShare, a new architecture for end-toend encrypted, group-based file sharing using trusted execution environments (TEE), e.g., Intel SGX. SeGShare is the first solution to protect the confidentiality and integrity of all data and management files; enforce immediate permis

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Malkoochi, Ramchander. "Confidential Computing for Privacy-Preserving Fraud Analytics." European Journal of Computer Science and Information Technology 13, no. 24 (2025): 115–228. https://doi.org/10.37745/ejcsit.2013/vol13n24115228.

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Confidential computing represents a transformative paradigm in fraud analytics, providing robust protection for sensitive financial data throughout the processing lifecycle. By leveraging Trusted Execution Environments (TEEs) such as Intel SGX and AMD SEV, financial institutions can analyze transaction patterns, detect anomalies, and collaborate across organizational boundaries while maintaining data confidentiality. The technology addresses the fundamental tension between effective fraud detection and privacy protection through hardware-based isolation mechanisms that secure data even during

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Mahbub, Khaled, Antonio Nehme, Mohammad Patwary, Marc Lacoste, and Sylvain Allio. "FIVADMI: A Framework for In-Vehicle Anomaly Detection by Monitoring and Isolation." Future Internet 16, no. 8 (2024): 288. http://dx.doi.org/10.3390/fi16080288.

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Self-driving vehicles have attracted significant attention in the automotive industry that is heavily investing to reach the level of reliability needed from these safety critical systems. Security of in-vehicle communications is mandatory to achieve this goal. Most of the existing research to detect anomalies for in-vehicle communication does not take into account the low processing power of the in-vehicle Network and ECUs (Electronic Control Units). Also, these approaches do not consider system level isolation challenges such as side-channel vulnerabilities, that may arise due to adoption of

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Qiu, Lina, Georgios Kellaris, Nikos Mamoulis, Kobbi Nissim, and George Kollios. "Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures." Proceedings of the VLDB Endowment 16, no. 13 (2023): 4160–73. http://dx.doi.org/10.14778/3625054.3625055.

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Most cloud service providers offer limited data privacy guarantees, discouraging clients from using them for managing their sensitive data. Cloud providers may use servers with Trusted Execution Environments (TEEs) to protect outsourced data, while supporting remote querying. However, TEEs may leak access patterns and allow communication volume attacks, enabling an honest-but-curious cloud provider to learn sensitive information. Oblivious algorithms can be used to completely hide data access patterns, but their high overhead could render them impractical. To alleviate the latter, the notion o

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Wilke, Luca, Jan Wichelmann, Anja Rabich, and Thomas Eisenbarth. "SEV-Step A Single-Stepping Framework for AMD-SEV." IACR Transactions on Cryptographic Hardware and Embedded Systems 2024, no. 1 (2023): 180–206. http://dx.doi.org/10.46586/tches.v2024.i1.180-206.

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The ever increasing popularity and availability of Trusted Execution Environments (TEEs) had a stark influence on microarchitectural attack research in academia, as their strong attacker model both boosts existing attack vectors and introduces several new ones. While many works have focused on Intel SGX, other TEEs like AMD SEV have recently also started to receive more attention. A common technique when attacking SGX enclaves is single-stepping, where the system’s APIC timer is used to interrupt the enclave after every instruction. Single-stepping increases the temporal resolution of subseque

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Muñoz, Antonio. "Cracking the Core: Hardware Vulnerabilities in Android Devices Unveiled." Electronics 13, no. 21 (2024): 4269. http://dx.doi.org/10.3390/electronics13214269.

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As Android devices become more prevalent, their security risks extend beyond software vulnerabilities to include critical hardware weaknesses. This paper provides a comprehensive and systematic review of hardware-related vulnerabilities in Android systems, which can bypass even the most sophisticated software defenses. We compile and analyze an extensive range of reported vulnerabilities, introducing a novel categorization framework to facilitate a deeper understanding of these risks, classified by affected hardware components, vulnerability type, and the potential impact on system security. T

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Wang, Yanping, Xiaosong Zhang, Xiaofen Wang, Teng Hu, Peng Lu, and Mingyong Yin. "Security Enhancements for Data-Driven Systems: A Blockchain-Based Trustworthy Data Sharing Scheme." Security and Communication Networks 2022 (October 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/1317626.

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With the increasingly prominent value of big data, data sharing within enterprises and organizations has become increasingly popular, and many institutions have established data centers to achieve effective data storage and sharing. Meanwhile, cyberspace data security and privacy have become the most critical issue that people are concerned about since shared data often involves commercial secrets and sensitive information. At present, data encryption techniques have been applied to protect the security of the sensitive data stored in and shared by the data centers. However, the challenges of

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Köhler, Jens, and Henry Förster. "Trusted Execution Environments im Fahrzeug." ATZelektronik 11, no. 5 (2016): 38–43. http://dx.doi.org/10.1007/s35658-016-0080-0.

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Köhler, Jens, and Henry Förster. "Trusted Execution Environments in Vehicles." ATZelektronik worldwide 11, no. 5 (2016): 36–41. http://dx.doi.org/10.1007/s38314-016-0074-y.

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Kohlbrenner, David, Shweta Shinde, Dayeol Lee, Krste Asanovic, and Dawn Song. "Building Open Trusted Execution Environments." IEEE Security & Privacy 18, no. 5 (2020): 47–56. http://dx.doi.org/10.1109/msec.2020.2990649.

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Anciaux, Nicolas, Luc Bouganim, Philippe Pucheral, lulian Sandu Popa, and Guillaume Scerri. "Personal database security and trusted execution environments." Proceedings of the VLDB Endowment 12, no. 12 (2019): 1994–97. http://dx.doi.org/10.14778/3352063.3352118.

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Jauernig, Patrick, Ahmad-Reza Sadeghi, and Emmanuel Stapf. "Trusted Execution Environments: Properties, Applications, and Challenges." IEEE Security & Privacy 18, no. 2 (2020): 56–60. http://dx.doi.org/10.1109/msec.2019.2947124.

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Witharana, Hasini, Hansika Weerasena, and Prabhat Mishra. "Formal Verification of Virtualization-Based Trusted Execution Environments." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 43, no. 11 (2024): 4262–73. http://dx.doi.org/10.1109/tcad.2024.3443008.

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Zeng, Fanlang, Rui Chang, and Hongjian Liu. "Freesia: Verifying Correctness of TEE Communication with Concurrent Separation Logic." Proceedings of the ACM on Software Engineering 2, ISSTA (2025): 2045–67. https://doi.org/10.1145/3728967.

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The Trusted Execution Environment (TEE), a security extension in modern processors, provides a secure runtime environment for sensitive code and data. Although TEEs are designed to protect applications and their private data, their large code bases often harbor vulnerabilities that could compromise data security. Even though some formal verification efforts have been directed toward the functionality and security of TEE standards and implementations, the verification of TEE correctness in concurrent scenarios remains insufficient. This paper introduces an enhancement for ensuring concurrency s

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