Academic literature on the topic 'Trusted Execution Environments (TEEs)'
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Journal articles on the topic "Trusted Execution Environments (TEEs)"
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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 also assist ensure that facts aren't always compromised at some stage in transmission. TEEs typically applied the employment of specialized hardware that would offer a better degree of protection than software program-most effective solutions. Hardware-primarily based total TEEs can also offer better overall performance and power efficiency than software-handiest solutions. There are some particular TEE implementations to be had, which incorporates Intel’s TXT, ARM’s TrustZone, and Samsung’s KNOX. Each of those implementations has its very personal strengths and weaknesses, so it's miles more crucial to pick the right TEE on your precise software. reckoning on execution environments are becoming an increasing number of necessities because the amount of touchy facts that's processed and stored electronically continues growing. TEEs can assist shield facts from being accessed or modified by means of way of unauthorized customers, and might also help make sure that records aren't compromised at some point of transmission. TEEs normally implemented the employment of specialized hardware, which will offer a far better degree of protection than software program-only answers. To research how this period has been implemented to the exceptional IoT eventualities, which normally address unique characteristics which incorporate device useful resource constraints, we allotted a scientific literature evaluation.
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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 prototyping environment for developing trusted applications while safeguarding against existing threats. At Verifoxx Ltd, our architecture relies on TEEs to handle sensitive data, encompassing tasks such as extracting client secrets, managing commitments, sharding and executing cryptographic operations for zero-knowledge responses. The proposed approach holds promise where TEEs can enhance transaction security and enterprises seeking data protection. Our approach introduces in-enclave compartments with controlled communication, facilitating domain transitions through sealed data capability delegations and hardware-assisted call/return mechanisms. This enables application layer compartmentalization by modularly separating concerns within the secure world, emphasising single responsibility, least privileges, and information hiding from unprivileged compartments. Furthermore, we ensure the integrity of lower-layer hardware and OS properties, effectively thwarting compromise attempts.
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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 research in the context of TEE. The unique software architecture of TrustZone-assisted TEE complicates the direct application of traditional fuzzing methods. Moreover, simplistic approaches, such as feeding random input values into TEE through the API functions of the rich operating system, fail to uncover deeper, latent bugs within the TEE code. In this paper, we present a fuzzing strategy for TrustZone-assisted TEE that utilizes inferred dependencies between Trusted Kernel system calls to uncover deep-seated TEE bugs. We implemented our approach on OP-TEE, where it successfully identified 17 crashes, including one previously undetected kernel bug.
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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 may influence comfort with data collection and use. We find that cloud-based TEEs significantly increase user comfort across information flows. These increases are more pronounced for devices manufactured by smaller companies and show that cloud-based TEEs can bridge the previously-documented gulfs in user trust between small and large companies. Sentiments around consent, bystander data, and indefinite retention are unaffected by the presence of TEEs, indicating the centrality of these norms.
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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 schemes, and (3) distributed scheduling strategies. From the profiling study, we observe three major high-performance impediments: (a) the computational overhead introduced with cryptographic primitives associated with page swapping operations, (b) the restrictive Enclave Page Cache (EPC) size that limits the supported amount of in-memory processing, and (c) the lack of vertical scalability to support the increasing workload often required for near real-time applications. Addressing these issues allowed us to design SecJoin, a more efficient parallel stream join algorithm that exploits modern scale-out architectures with TEEs rendering no trade-offs on security whilst optimizing performance. We present our model-driven parameterization of SecJoin and share our experimental results which have shown up to 4-folds of improvements in terms of throughput and latency.
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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 among participants leading to the potential disclosure of private keys, high computational costs, and decreased efficiency. The advent of trusted execution environments (TEEs) offers a solution by protecting computations involving private data through hardware isolation, thereby eliminating reliance on trusted third parties, preventing malicious collusion, and improving efficiency. Nevertheless, TEEs are vulnerable to side-channel attacks. In this work, we propose an enhanced PPRL method based on TEE technology. Our methodology involves processing plaintext data within a TEE using the inner product mask technique, which effectively obfuscates the data, making it impervious to side-channel attacks. The experimental results demonstrate that our approach not only significantly improves resistance to side-channel attacks but also enhances efficiency, showing better performance and privacy preservation compared to existing methods. This work provides a robust solution to the challenges faced by current PPRL methods and sets the stage for future research aimed at further enhancing scalability and security.
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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 vulnerable.
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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 challenges when executing relational equi-joins in TEEs. For this, we introduce TEEbench, a framework for unified benchmarking of relational operators in TEEs, and use it for conducting our experimental evaluation. In a nutshell, we perform the following experimental analysis for eight core join algorithms: off-the-shelf performance; the performance implications of data sealing and obliviousness; sensitivity and scalability. The results show that all eight join algorithms significantly suffer from different performance bottlenecks in TEEs. They can be up to three orders of magnitude slower in TEEs than on plain CPUs. Our study also indicates that existing join algorithms need a complete, hardware-aware redesign to be efficient in TEEs, and that, in secure query plans, managing TEE features is equally important to join selection.
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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 the last years adopted the integration of dedicated resources to provide Trusted Execution Environments (TEEs) or secure zones. TEEs are built layer by layer on top of an implicitly trusted component, the Root-of-Trust (RoT). Since each security chain is only as strong as its weakest link, each element involved in the construction of a TEE starting from the RoT must be bulletproof as much as possible. In this work, we revise and propose a design methodology to implement in both hardware (HW) and software (SW) highly featured and robust security blocks by highlighting the key points that designers should take care of, and the key metrics that should be used to evaluate the security level of the developed modules. We also include an analysis of the state of the art concerning RoT-based TEEs, and we illustrate a case study that documents the implementation of a cryptographic coprocessor for the secure subsystem of the Rhea GPP from the European Processor Initiative (EPI) project, according to the presented methodology. This work can be used by HW/SW security module designers as a cutting-edge guideline.
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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 secure and nonsecure software stack. This is crucial due to the diversity of device manufacturers and component suppliers in the market, which manifests trust issues, especially when third-party peripherals are incorporated into a TEE. Compromised TEEs can be misused for industrial espionage, data exfiltration through system backdoors, and illegal data sharing. It is of utmost importance here that system peripheral behaviour in terms of resource access is in accordance with their intended usage that is specified during integration. We propose TEE-Watchdog, a lightweight framework that establishes MPU protections for secure system peripherals in TrustZone-enabled low-end IoT devices. TEE-Watchdog ensures blocking unauthorized peripheral accesses and logging of application misbehaviour running in the TEE based on a manifest file. We define lightweight specifications and structure for the application manifest file enlisting permissions for critical system peripherals using concise binary object representation (CBOR). We implement and evaluate TEE-Watchdog using a Musca-A2 test chipboard. Our microbenchmark evaluations on CPU time and RAM usage demonstrated the practicality of TEE-Watchdog. Securing the system peripherals using TEE-Watchdog protections induced a 1.4% overhead on the latency of peripheral accesses, which was 61 microseconds on our test board. Our optimized CBOR-encoded manifest file template also showed a decrease in manifest file size by 40% as compared to the standard file formats, e.g., JSON.
Dissertations / Theses on the topic "Trusted Execution Environments (TEEs)"
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Cole, Nigel. "Arguing Assurance in Trusted Execution Environments using Goal Structuring Notation." Thesis, Linköpings universitet, Programvara och system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177923.
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A trusted execution environment (TEE) is an isolated environment used for trusted execution. TEE solutions are usually proprietary and specific for a certain hardware specification, thereby limiting developers that use those TEEs. A potential solution to this issue is the use of open-source alternatives such as the TEE framework Keystone and the Reduced Instruction Set Computer V (RISC-V) hardware. These alternatives are rather young and are not as well established as the variants developed by ARM and Intel. To this end, the assurance in Keystone and RISC-V are analysed by studying a remote attestation assurance use case using the goal structuring notation (GSN) method. The aim is to investigate how GSN can be utilised to build assurance cases for TEEs on RISC-V. This thesis presents a process of how GSNs can be created to argue assurance for a TEE solution. Furthermore, Keystone operates under a specific threat model with made assumptions that may have a large impact depending on the use case. Therefore, Keystone is analysed to understand whether the framework mitigates existing vulnerabilities in TEEs. It is concluded that GSN is a viable method for arguing assurance in TEEs, providing great freedom in the creation of the GSN model. The freedom is also its weakness since the argument composition has a high impact on the argument. Furthermore, we conclude that Keystone mitigates multiple known vulnerabilities primarily through made assumptions in its threat model. These cases need to be considered by developers utilising Keystone to determine whether or not the assumptions are valid for their use case.
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Da, Silva Mathieu. "Securing a trusted hardware environment (Trusted Execution Environment)." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTS053/document.
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Ce travail de thèse a pour cadre le projet Trusted Environment Execution eVAluation (TEEVA) (projet français FUI n°20 de Janvier 2016 à Décembre 2018) qui vise à évaluer deux solutions alternatives de sécurisation des plateformes mobiles, l’une est purement logicielle, la Whitebox Crypto, alors que l’autre intègre des éléments logiciels et matériels, le Trusted Environment Execution (TEE). Le TEE s’appuie sur la technologie TrustZone d’ARM disponible sur de nombreux chipsets du marché tels que des smartphones et tablettes Android. Cette thèse se concentre sur l’architecture TEE, l’objectif étant d’analyser les menaces potentielles liées aux infrastructures de test/debug classiquement intégrées dans les circuits pour contrôler la conformité fonctionnelle après fabrication.Le test est une étape indispensable dans la production d’un circuit intégré afin d’assurer fiabilité et qualité du produit final. En raison de l’extrême complexité des circuits intégrés actuels, les procédures de test ne peuvent pas reposer sur un simple contrôle des entrées primaires avec des patterns de test, puis sur l’observation des réponses de test produites sur les sorties primaires. Les infrastructures de test doivent être intégrées dans le matériel au moment du design, implémentant les techniques de Design-for-Testability (DfT). La technique DfT la plus commune est l’insertion de chaînes de scan. Les registres sont connectés en une ou plusieurs chaîne(s), appelé chaîne(s) de scan. Ainsi, un testeur peut contrôler et observer les états internes du circuit à travers les broches dédiées. Malheureusement, cette infrastructure de test peut aussi être utilisée pour extraire des informations sensibles stockées ou traitées dans le circuit, comme par exemple des données fortement corrélées à une clé secrète. Une attaque par scan consiste à récupérer la clé secrète d’un crypto-processeur grâce à l’observation de résultats partiellement encryptés.Des expérimentations ont été conduites sur la carte électronique de démonstration avec le TEE afin d’analyser sa sécurité contre une attaque par scan. Dans la carte électronique de démonstration, une contremesure est implémentée afin de protéger les données sensibles traitées et sauvegardées dans le TEE. Les accès de test sont déconnectés, protégeant contre les attaques exploitant les infrastructures de test, au dépend des possibilités de test, diagnostic et debug après mise en service du circuit. Les résultats d’expérience ont montré que les circuits intégrés basés sur la technologie TrustZone ont besoin d’implanter une contremesure qui protège les données extraites des chaînes de scan. Outre cette simple contremesure consistant à éviter l’accès aux chaînes de scan, des contremesures plus avancées ont été développées dans la littérature pour assurer la sécurité tout en préservant l’accès au test et au debug. Nous avons analysé un état de l’art des contremesures contre les attaques par scan. De cette étude, nous avons proposé une nouvelle contremesure qui préserve l’accès aux chaînes de scan tout en les protégeant, qui s’intègre facilement dans un système, et qui ne nécessite aucun redesign du circuit après insertion des chaînes de scan tout en préservant la testabilité du circuit. Notre solution est basée sur l’encryption du canal de test, elle assure la confidentialité des communications entre le circuit et le testeur tout en empêchant son utilisation par des utilisateurs non autorisés. Plusieurs architectures ont été étudiées, ce document rapporte également les avantages et les inconvénients des solutions envisagées en terme de sécurité et de performance<br>This work is part of the Trusted Environment Execution eVAluation (TEEVA) project (French project FUI n°20 from January 2016 to December 2018) that aims to evaluate two alternative solutions for secure mobile platforms: a purely software one, the Whitebox Crypto, and a TEE solution, which integrates software and hardware components. The TEE relies on the ARM TrustZone technology available on many of the chipsets for the Android smartphones and tablets market. This thesis focuses on the TEE architecture. The goal is to analyze potential threats linked to the test/debug infrastructures classically embedded in hardware systems for functional conformity checking after manufacturing.Testing is a mandatory step in the integrated circuit production because it ensures the required quality and reliability of the devices. Because of the extreme complexity of nowadays integrated circuits, test procedures cannot rely on a simple control of primary inputs with test patterns, then observation of produced test responses on primary outputs. Test facilities must be embedded in the hardware at design time, implementing the so-called Design-for-Testability (DfT) techniques. The most popular DfT technique is the scan design. Thanks to this test-driven synthesis, registers are connected in one or several chain(s), the so-called scan chain(s). A tester can then control and observe the internal states of the circuit through dedicated scan pins and components. Unfortunately, this test infrastructure can also be used to extract sensitive information stored or processed in the chip, data strongly correlated to a secret key for instance. A scan attack consists in retrieving the secret key of a crypto-processor thanks to the observation of partially encrypted results.Experiments have been conducted during the project on the demonstrator board with the target TEE in order to analyze its security against a scan-based attack. In the demonstrator board, a countermeasure is implemented to ensure the security of the assets processed and saved in the TEE. The test accesses are disconnected preventing attacks exploiting test infrastructures but disabling the test interfaces for testing, diagnosis and debug purposes. The experimental results have shown that chips based on TrustZone technology need to implement a countermeasure to protect the data extracted from the scan chains. Besides the simple countermeasure consisting to avoid scan accesses, further countermeasures have been developed in the literature to ensure security while preserving test and debug facilities. State-of-the-art countermeasures against scan-based attacks have been analyzed. From this study, we investigate a new proposal in order to preserve the scan chain access while preventing attacks, and to provide a plug-and-play countermeasure that does not require any redesign of the scanned circuit while maintaining its testability. Our solution is based on the encryption of the test communication, it provides confidentiality of the communication between the circuit and the tester and prevents usage from unauthorized users. Several architectures have been investigated, this document also reports pros and cons of envisaged solutions in terms of security and performance
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Mishra, Tanmaya. "Parallelizing Trusted Execution Environments for Multicore Hard Real-Time Systems." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/89889.
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Real-Time systems are defined not only by their logical correctness but also timeliness.
Modern real-time systems, such as those controlling industrial plants or the flight controller
on UAVs, are no longer isolated. The same computing resources are shared with a variety
of other systems and software. Further, these systems are increasingly being connected
and made available over the internet with the rise of Internet of Things and the need for
automation. Many real-time systems contain sensitive code and data, which not only need to
be kept confidential but also need protection against unauthorized access and modification.
With the cheap availability of hardware supported Trusted Execution Environments (TEE)
in modern day microprocessors, securing sensitive information has become easier and more
robust. However, when applied to real-time systems, the overheads of using TEEs make
scheduling untenable. However, this issue can be mitigated by judiciously utilizing TEEs
and capturing TEE operation peculiarities to create better scheduling policies. This thesis
provides a new task model and scheduling approach, Split-TEE task model and a scheduling
approach ST-EDF. It also presents simulation results for 2 previously proposed approaches
to scheduling TEEs, T-EDF and CT-RM.<br>Master of Science<br>Real-Time systems are computing systems that not only maintain the traditional purpose of any computer, i.e, to be logically correct, but also timeliness, i.e, guaranteeing an output in a given amount of time. While, traditionally, real-time systems were isolated to reduce interference which could affect the timeliness, modern real-time systems are being increasingly connected to the internet. Many real-time systems, especially those used for critical applications like industrial control or military equipment, contain sensitive code or data that must not be divulged to a third party or open to modification. In such cases, it is necessary to use methods to safeguard this information, regardless of the extra processing time/resource consumption (overheads) that it may add to the system. Modern hardware support Trusted Execution Environments (TEEs), a cheap, easy and robust mechanism to secure arbitrary pieces of code and data. To effectively use TEEs in a real-time system, the scheduling policy which decides which task to run at a given time instant, must be made aware of TEEs and must be modified to take as much advantage of TEE execution while mitigating the effect of its overheads on the timeliness guarantees of the system. This thesis presents an approach to schedule TEE augmented code and simulation results of two previously proposed approaches.
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Fischer, Andreas [Verfasser]. "Computing on encrypted data using trusted execution environments / Andreas Fischer." Paderborn : Universitätsbibliothek, 2021. http://d-nb.info/1234058790/34.
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Elbashir, Khalid. "Trusted Execution Environments for Open vSwitch : A security enabler for the 5G mobile network." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218070.
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The advent of virtualization introduced the need for virtual switches to interconnect virtual machines deployed in a cloud infrastructure. With Software Defined Networking (SDN), a central controller can configure these virtual switches. Virtual switches execute on commodity operating systems. Open vSwitch is an open source project that is widely used in production cloud environments. If an adversary gains access with full privileges to the operating system hosting the virtual switch, then Open vSwitch becomes vulnerable to a variety of different attacks that could compromise the whole network. The purpose of this thesis project is to improve the security of Open vSwitch implementations in order to ensure that only authenticated switches and controllers can communicate with each other, while maintaining code integrity and confidentiality of keys and certificates. The thesis project proposes a design and shows an implementation that leverages Intel® Safe Guard Extensions (SGX) technology. A new library, TLSonSGX, is implemented. This library replaces the use of the OpenSSL library in Open vSwitch. In addition to implementing standard Transport Level Security (TLS) connectivity, TLSonSGX confines TLS communication in the protected memory enclave and hence protects TLS sensitive components necessary to provide confidentiality and integrity, such as private keys and negotiated symmetric keys. Moreover, TLSonSGX introduces new, secure, and automatic means to generate keys and obtain signed certificates from a central Certificate Authority that validates using Linux Integrity Measurements Architecture (IMA) that the Open vSwitch binaries have not been tampered with before issuing a signed certificate. The generated keys and obtained certificates are stored in the memory enclave and hence never exposed as plaintext outside the enclave. This new mechanism is a replacement for the existing manual and unsecure procedures (as described in Open vSwitch project). A security analysis of the system is provided as well as an examination of performance impact of the use of a trusted execution environment. Results show that generating keys and certificates using TLSonSGX takes less than 0.5 seconds while adding 30% latency overhead for the first packet in a flow compared to using OpenSSL when both are executed on Intel® CoreTM i7-6600U processor clocked at 2.6 GHz. These results show that TLSonSGX can enhance Open vSwitch security and reduce its TLS configuration overhead.<br>Framkomsten av virtualisering införde behovet av virtuella växlar för att koppla tillsammans virtuella maskiner placerade i molninfrastruktur. Med mjukvarubaserad nätverksteknik (SDN), kan ett centralt styrenhet konfigurera dessa virtuella växlar. Virtuella växlar kör på standardoperativsystem. Open vSwitch är ett open-source projekt som ofta används i molntjänster. Om en motståndare får tillgång med fullständiga privilegier till operativsystemet där Open vSwitch körs, blir Open vSwitch utsatt för olika attacker som kan kompromettera hela nätverket. Syftet med detta examensarbete är att förbättra säkerheten hos Open vSwitch för att garantera att endast autentiserade växlar och styrenheter kan kommunicera med varandra, samtidigt som att upprätthålla kod integritet och konfidentialitet av nycklar och certifikat. Detta examensarbete föreslår en design och visar en implementation som andvändar Intel®s Safe Guard Extensions (SGX) teknologi. Ett nytt bibliotek, TLSonSGX, är implementerat. Detta bibliotek ersätter biblioteket OpenSSL i Open vSwitch. Utöver att det implementerar ett standard “Transport Layer Security” (TLS) anslutning, TLSonSGX begränsar TLS kommunikation i den skyddade minnes enklaven och skyddar därför TLS känsliga komponenter som är nödvändiga för att ge sekretess och integritet, såsom privata nycklar och förhandlade symmetriska nycklar. Dessutom introducerar TLSonSGX nya, säkra och automatiska medel för att generera nycklar och få signerade certifikat från en central certifikatmyndighet som validerar, med hjälp av Linux Integrity Measurements Architecture (IMA), att Open vSwitch-binärerna inte har manipulerats innan de utfärdade ett signerat certifikat. De genererade nycklarna och erhållna certifikat lagras i minnes enklaven och är därför aldrig utsatta utanför enklaven. Denna nya mekanism ersätter de manuella och osäkra procedurerna som beskrivs i Open vSwitch projektet. En säkerhetsanalys av systemet ges såväl som en granskning av prestandaffekten av användningen av en pålitlig exekveringsmiljö. Resultaten visar att använda TLSonSGX för att generera nycklar och certifikat tar mindre än 0,5 sekunder medan det lägger 30% latens overhead för det första paketet i ett flöde jämfört med att använda OpenSSL när båda exekveras på Intel® Core TM processor i7-6600U klockad vid 2,6 GHz. Dessa resultat visar att TLSonSGX kan förbättra Open vSwitch säkerhet och minska TLS konfigurationskostnaden.
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Sundblad, Anton, and Gustaf Brunberg. "Secure hypervisor versus trusted execution environment : Security analysis for mobile fingerprint identification applications." Thesis, Linköpings universitet, Databas och informationsteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139227.
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Fingerprint identification is becoming increasingly popular as a means of authentication for handheld devices of different kinds. In order to secure such an authentication solution it is common to use a TEE implementation. This thesis examines the possibility of replacing a TEE with a hypervisor-based solution instead, with the intention of keeping the same security features that a TEE can offer. To carry out the evaluation a suitable method is constructed. This method makes use of fault trees to be able to find possible vulnerabilities in both systems, and these vulnerabilities are then documented. The vulnerabilities of both systems are also compared to each other to identify differences in how they are handled. It is concluded that if the target platform has the ability to implement a TEE solution, it can also implement the same solution using a hypervisor. However, the authors recommend against porting a working TEE solution, as TEEs often offer finished APIs for common operations that would require re-implementation in the examined hypervisor.
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Dhar, Siddharth. "Optimizing TEE Protection by Automatically Augmenting Requirements Specifications." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98730.
Full textAbstract:
An increasing number of software systems must safeguard their confidential data and code, referred to as critical program information (CPI). Such safeguarding is commonly accomplished by isolating CPI in a trusted execution environment (TEE), with the isolated CPI becoming a trusted computing base (TCB). TEE protection incurs heavy performance costs, as TEE-based functionality is expensive to both invoke and execute. Despite these costs, projects that use TEEs tend to have unnecessarily large TCBs. As based on our analysis, developers often put code and data into TEE for convenience rather than protection reasons, thus not only compromising performance but also reducing the effectiveness of TEE protection.
In order for TEEs to provide maximum benefits for protecting CPI, their usage must be systematically incorporated into the entire software engineering process, starting from Requirements Engineering.
To address this problem, we present a novel approach that incorporates TEEs in the Requirements Engineering phase by using natural language processing (NLP) to classify those software requirements that are security critical and should be isolated in TEE. Our approach takes as input a requirements specification and outputs a list of annotated software requirements. The annotations recommend to the developer which corresponding features comprise CPI that should be protected in a TEE. Our evaluation results indicate that our approach identifies CPI with a high degree of accuracy to incorporate safeguarding CPI into Requirements Engineering.<br>Master of Science<br>An increasing number of software systems must safeguard their confidential data like passwords, payment information, personal details, etc.
This confidential information is commonly protected using a Trusted Execution Environment (TEE), an isolated environment provided by either the existing processor or separate hardware that interacts with the operating system to secure sensitive data and code.
Unfortunately, TEE protection incurs heavy performance costs, with TEEs being slower than modern processors and frequent communication between the system and the TEE incurring heavy performance overhead.
We discovered that developers often put code and data into TEE for convenience rather than protection purposes, thus not only hurting performance but also reducing the effectiveness of TEE protection.
By thoroughly examining a project's features in the Requirements Engineering phase, which defines the project's functionalities, developers would be able to understand which features handle confidential data.
To that end, we present a novel approach that incorporates TEEs in the Requirements Engineering phase by means of Natural Language Processing (NLP) tools to categorize the project requirements that may warrant TEE protection.
Our approach takes as input a project's requirements and outputs a list of categorized requirements defining which requirements are likely to make use of confidential information. Our evaluation results indicate that our approach performs this categorization with a high degree of accuracy to incorporate safeguarding the confidentiality related features in the Requirements Engineering phase.
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Lim, Steven. "Recommending TEE-based Functions Using a Deep Learning Model." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104999.
Full textAbstract:
Trusted execution environments (TEEs) are an emerging technology that provides a protected hardware environment for processing and storing sensitive information. By using
TEEs, developers can bolster the security of software systems. However, incorporating
TEE into existing software systems can be a costly and labor-intensive endeavor. Software
maintenance—changing software after its initial release—is known to contribute the majority of the cost in the software development lifecycle. The first step of making use of a TEE
requires that developers accurately identify which pieces of code would benefit from being
protected in a TEE. For large code bases, this identification process can be quite tedious and
time-consuming. To help reduce the software maintenance costs associated with introducing
a TEE into existing software, this thesis introduces ML-TEE, a recommendation tool that
uses a deep learning model to classify whether an input function handles sensitive information or sensitive code. By applying ML-TEE, developers can reduce the burden of manual
code inspection and analysis. ML-TEE's model was trained and tested on functions from
GitHub repositories that use Intel SGX and on an imbalanced dataset. The accuracy of
the final model used in the recommendation system has an accuracy of 98.86% and an F1
score of 80.00%. In addition, we conducted a pilot study, in which participants were asked
to identify functions that needed to be placed inside a TEE in a third-party project. The
study found that on average, participants who had access to the recommendation system's
output had a 4% higher accuracy and completed the task 21% faster.<br>Master of Science<br>Improving the security of software systems has become critically important. A trusted
execution environment (TEE) is an emerging technology that can help secure software that
uses or stores confidential information. To make use of this technology, developers need to
identify which pieces of code handle confidential information and should thus be placed in
a TEE. However, this process is costly and laborious because it requires the developers to
understand the code well enough to make the appropriate changes in order to incorporate a
TEE. This process can become challenging for large software that contains millions of lines
of code. To help reduce the cost incurred in the process of identifying which pieces of code
should be placed within a TEE, this thesis presents ML-TEE, a recommendation system
that uses a deep learning model to help reduce the number of lines of code a developer
needs to inspect. Our results show that the recommendation system achieves high accuracy
as well as a good balance between precision and recall. In addition, we conducted a pilot
study and found that participants from the intervention group who used the output from
the recommendation system managed to achieve a higher average accuracy and perform the
assigned task faster than the participants in the control group.
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Fuhry, Benny [Verfasser], and Frederik [Akademischer Betreuer] Armknecht. "Secure and efficient processing of outsourced data structures using trusted execution environments / Benny Fuhry ; Betreuer: Frederik Armknecht." Mannheim : Universitätsbibliothek Mannheim, 2021. http://d-nb.info/1229835911/34.
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Arfaoui, Ghada. "Conception de protocoles cryptographiques préservant la vie privée pour les services mobiles sans contact." Thesis, Orléans, 2015. http://www.theses.fr/2015ORLE2013/document.
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Avec l'émergence de nouvelles technologies telles que le NFC (Communication à champ proche) et l'accroissement du nombre de plates-formes mobiles, les téléphones mobiles vont devenir de plus en plus indispensables dans notre vie quotidienne. Ce contexte introduit de nouveaux défis en termes de sécurité et de respect de la vie privée. Dans cette thèse, nous nous focalisons sur les problématiques liées au respect de la vie privée dans les services NFC ainsi qu’à la protection des données privées et secrets des applications mobiles dans les environnements d'exécution de confiance (TEE). Nous fournissons deux solutions pour le transport public: une solution utilisant des cartes d'abonnement (m-pass) et une autre à base de tickets électroniques (m-ticketing). Nos solutions préservent la vie privée des utilisateurs tout en respectant les exigences fonctionnelles établies par les opérateurs de transport. À cette fin, nous proposons de nouvelles variantes de signatures de groupe ainsi que la première preuve pratique d’appartenance à un ensemble, à apport nul de connaissance, et qui ne nécessite pas de calculs de couplages du côté du prouveur. Ces améliorations permettent de réduire considérablement le temps d'exécution de ces schémas lorsqu’ils sont implémentés dans des environnements contraints par exemple sur carte à puce. Nous avons développé les protocoles de m-passe et de m-ticketing dans une carte SIM standard : la validation d'un ticket ou d'un m-pass s'effectue en moins de 300ms et ce tout en utilisant des tailles de clés adéquates. Nos solutions fonctionnent également lorsque le mobile est éteint ou lorsque sa batterie est déchargée. Si les applications s'exécutent dans un TEE, nous introduisons un nouveau protocole de migration de données privées, d'un TEE à un autre, qui assure la confidentialité et l'intégrité de ces données. Notre protocole est fondé sur l’utilisation d’un schéma de proxy de rechiffrement ainsi que sur un nouveau modèle d’architecture du TEE. Enfin, nous prouvons formellement la sécurité de nos protocoles soit dans le modèle calculatoire pour les protocoles de m-pass et de ticketing soit dans le modèle symbolique pour le protocole de migration de données entre TEE<br>The increasing number of worldwide mobile platforms and the emergence of new technologies such as the NFC (Near Field Communication) lead to a growing tendency to build a user's life depending on mobile phones. This context brings also new security and privacy challenges. In this thesis, we pay further attention to privacy issues in NFC services as well as the security of the mobile applications private data and credentials namely in Trusted Execution Environments (TEE). We first provide two solutions for public transport use case: an m-pass (transport subscription card) and a m-ticketing validation protocols. Our solutions ensure users' privacy while respecting functional requirements of transport operators. To this end, we propose new variants of group signatures and the first practical set-membership proof that do not require pairing computations at the prover's side. These novelties significantly reduce the execution time of such schemes when implemented in resource constrained environments. We implemented the m-pass and m-ticketing protocols in a standard SIM card: the validation phase occurs in less than 300ms whilst using strong security parameters. Our solutions also work even when the mobile is switched off or the battery is flat. When these applications are implemented in TEE, we introduce a new TEE migration protocol that ensures the privacy and integrity of the TEE credentials and user's private data. We construct our protocol based on a proxy re-encryption scheme and a new TEE model. Finally, we formally prove the security of our protocols using either game-based experiments in the random oracle model or automated model checker of security protocols
Books on the topic "Trusted Execution Environments (TEEs)"
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Shepherd, Carlton, and Konstantinos Markantonakis. Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9.
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Shepherd, Carlton. Trusted Execution Environments. Springer International Publishing AG, 2024.
Find full textBook chapters on the topic "Trusted Execution Environments (TEEs)"
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Yu, Geunyeol, Seunghyun Chae, Kyungmin Bae, and Sungkun Moon. "Formal Specification of Trusted Execution Environment APIs." In Fundamental Approaches to Software Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57259-3_5.
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AbstractTrusted execution environments (TEEs) have emerged as a key technology in the cybersecurity domain. A TEE provides an isolated environment in which sensitive computations can be executed securely. Trusted applications running in TEEs are developed using standardized APIs that many hardware platforms for TEE adhere to. However, formal models tailored to standard TEE APIs are not well developed. In this paper, we present a formal specification of TEE APIs using Maude. We focus on Trusted Storage API and Cryptographic Operations API, which are foundational to mobile and IoT applications. The effectiveness of our approach is demonstrated through formal analysis of MQT-TZ, an open-source TEE application for IoT. Our formal analysis has revealed security vulnerabilities in the implementation of MQT-TZ, and we patch and confirm its integrity using model checking.
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Szefer, Jakub. "Trusted Execution Environments." In Principles of Secure Processor Architecture Design. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-031-01760-5_4.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Trusted World Systems." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_6.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Deployment Issues, Attacks, and Other Challenges." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_8.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Background Material." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_2.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Isolated Hardware Execution Platforms." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_4.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Operating System Controls." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_3.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Building Execution Environments from the Trusted Platform Module." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_5.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Introduction." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_1.
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Shepherd, Carlton, and Konstantinos Markantonakis. "Conclusion." In Trusted Execution Environments. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-55561-9_9.
Full textConference papers on the topic "Trusted Execution Environments (TEEs)"
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Radaljac, Teodora, Danko Miladinović, Žarko Stanisavljević, and Pavle Vuletić. "Secure Distributed Computing in Cloud Using Trusted Execution Environments." In 2024 32nd Telecommunications Forum (TELFOR). IEEE, 2024. https://doi.org/10.1109/telfor63250.2024.10819070.
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De Meulemeester, Jesse, Luca Wilke, David Oswald, Thomas Eisenbarth, Ingrid Verbauwhede, and Jo Van Bulck. "BadRAM: Practical Memory Aliasing Attacks on Trusted Execution Environments." In 2025 IEEE Symposium on Security and Privacy (SP). IEEE, 2025. https://doi.org/10.1109/sp61157.2025.00104.
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D'Onghia, Grazia, Flavio Ciravegna, Giacomo Bruno, Mattin Antartiko Elorza Forcada, Antonio Pastor, and Antonio Lioy. "Securing 5G: Trusted Execution Environments for Centrally Controlled IPsec Integrity." In 2024 IFIP Networking Conference (IFIP Networking). IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619852.
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Puddu, Ivan, Moritz Schneider, Daniele Lain, Stefano Boschetto, and Srdjan Čapkun. "On (the Lack of) Code Confidentiality in Trusted Execution Environments." In 2024 IEEE Symposium on Security and Privacy (SP). IEEE, 2024. http://dx.doi.org/10.1109/sp54263.2024.00259.
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Birgersson, Marcus, Cyrille Artho, and Musard Balliu. "Sharing without Showing: Secure Cloud Analytics with Trusted Execution Environments." In 2024 IEEE Secure Development Conference (SecDev). IEEE, 2024. http://dx.doi.org/10.1109/secdev61143.2024.00016.
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Zhao, Ziming, Md Armanuzzaman, Xi Tan, and Zheyuan Ma. "Trusted Execution Environments in Embedded and IoT Systems: A CactiLab Perspective." In 2024 International Symposium on Secure and Private Execution Environment Design (SEED). IEEE, 2024. http://dx.doi.org/10.1109/seed61283.2024.00020.
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Felde, Hendrik Meyer Zum, and Andrei-Cosmin Aprodu. "MAXPOWR: Memory Attestation and Export in Process-based Trusted Execution Environments." In 2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2024. https://doi.org/10.1109/trustcom63139.2024.00030.
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Zhang, Xiaolei, Zhaoyu Chen, Guangpu Chen, Xinyu Feng, Qingni Shen, and Zhonghai Wu. "RPPFL: Robust and Privacy-Preserving Federated Learning via Trusted Execution Environments." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889398.
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Lee, Junmo, Seongjun Kim, Sanghyeon Park, and Soo-Mook Moon. "RouTEE: Secure, Scalable, and Efficient Off-Chain Payments using Trusted Execution Environments." In 2024 Annual Computer Security Applications Conference (ACSAC). IEEE, 2024. https://doi.org/10.1109/acsac63791.2024.00048.
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Kumar, Santosh. "A Verifiable Framework using Trusted Execution Environments for Privacy-Preserving Machine Learning." In 2024 International Conference on Engineering and Emerging Technologies (ICEET). IEEE, 2024. https://doi.org/10.1109/iceet65156.2024.10913696.
Full textReports on the topic "Trusted Execution Environments (TEEs)"
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Pei, M., H. Tschofenig, D. Thaler, and D. Wheeler. Trusted Execution Environment Provisioning (TEEP) Architecture. RFC Editor, 2023. http://dx.doi.org/10.17487/rfc9397.
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Akram, Ayaz, Anna Giannakou, Venkatesh Akella, Jason Lowe-Power, and Sean Peisert. Performance Analysis of Scientific Computing Workloads on Trusted Execution Environments. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1768054.
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