You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Remote mobile and embedded devices are used to deliver increasingly impactful services, such as medical rehabilitation and assistive technologies. Secure system logging is beneficial in these scenarios to aid audit and forensic investigations particularly if devices bring harm to end-users. Logs should be tamper-resistant in storage, during execution, and when retrieved by a trusted remote verifier. In recent years, Trusted Execution Environments (TEEs) have emerged as the go-to root of trust on constrained devices for isolated execution of sensitive applications. Existing TEE-based logging systems, however, focus largely on protecting server-side logs and offer little protection to constrained source devices. In this paper, we introduce EmLog -- a tamper-resistant logging system for constrained devices using the GlobalPlatform TEE. EmLog provides protection against complex software adversaries and offers several additional security properties over past schemes. The system is evaluated across three log datasets using an off-the-shelf ARM development board running an open-source, GlobalPlatform-compliant TEE. On average, EmLog runs with low run-time memory overhead (1MB heap and stack), 430--625 logs second throughput, and five-times persistent storage overhead versus unprotected logs.

Cited Abstract(s):
[1]: We propose a dynamic trust management protocol for Internet of Things (IoT) systems to deal with misbehaving nodes whose status or behavior may change dynamically. We consider an IoT system being deployed in a smart community where each node autonomously performs trust evaluation. We provide a formal treatment of the convergence, accuracy, and resilience properties of our dynamic trust management protocol and validate these desirable properties through simulation. We demonstrate the effectiveness of our dynamic trust management protocol with a trust-based service composition application in IoT environments. Our results indicate that trust-based service composition significantly outperforms non-trust-based service composition and approaches the maximum achievable performance based on ground truth status. Furthermore, our dynamic trust management protocol is capable of adaptively adjusting the best trust parameter setting in response to dynamically changing environments to maximize application performance.

[2]: The emergence of powerful, sensor-rich devices has led to the development of continuous authentication (CA) schemes using off-the-shelf hardware, where user behaviour is compared to past experience to produce an authentication decision with the aim of addressing challenges with traditional authentication schemes. Current CA proposals, however, have largely neglected adversaries present in a real-world deployment, namely the ubiquity of mal ware and software attacks. This has particular importance when a device cannot be trusted by a third-party, such as a corporation, that controls access to assets based on that decision. A software compromise, either on the scheme implementation or platform, may enable an adversary to modify authentication scores to alter the status of the device in reality, give insights into user behaviour, or gain unauthorised access to restricted assets. Hence, for the first time, we examine two standardised constructs that offer isolated and trusted execution - Secure Elements (SEs) and Trusted Execution Environments (TEEs) - even when an adversary has root-level privileges, and propose measures for providing trusted CA while retaining deployability. Based on these, we implement the first system for evaluating TEE-based CA on a consumer mobile device using Intel SGX, thus providing confidentiality, integrity and trust while removing the main platform from the TCB. We present an empirical evaluation of TEE-and non-TEE performance using methods proposed in related CA schemes. Our results indicate that trusted CA can be provided with no significant performance penalty, and may even offer performance benefits.

[3]: System logs are the greatest forensics assets that capture how an operating system or a program behaves. System logs are often the next immediate attack target once a system is compromised, and it is thus paramount to protect them. This paper introduces SGX-Log, a new logging system that ensures the integrity and confidentiality of log data. The key idea is to redesign a logging system by leveraging a recent hardware extension, called Intel SGX, which provides a secure enclave with sealing and unsealing primitives to protect program code and data in both memory and disk from being modified in an unauthorized manner even from high privilege code. We have implemented SGX-Log atop the recent Ubuntu 14.04 for secure logging using real SGX hardware. Our evaluation shows that SGX-Log introduces no observable performance overhead to the programs that generate the log requests, and it also imposes very small overhead to the log daemons.

[4]: 

[5]: Auditing system logs is an important means of ensuring systems' security in situations where run-time security mechanisms are not sufficient to completely prevent potentially malicious activities. A fundamental requirement for reliable auditing is the integrity of the log entries. This paper presents an infrastructure for secure logging that is capable of detecting the tampering of logs by powerful adversaries residing on the device where logs are generated. We rely on novel features of trusted hardware TPM to ensure the continuity of the logging infrastructure across power cycles without help from a remote server. Our infrastructure also addresses practical concerns including how to handle high-frequency log updates, how to conserve disk space for storing logs, and how to efficiently verify an arbitrary subset of the log. Importantly, we formally state the tamper-proofness guarantee of our infrastructure and verify that our basic secure logging protocol provides the desired guarantee. To demonstrate that our infrastructure is practical, we implement a prototype and evaluate its performance.

[6]: Trustable log data is essential in digital forensic investigations in order to allow reliable reconstruction of events. Existing solutions do not provide adequate protection, exposing the log-producing application to software-based attacks. In this paper we provide a solution based on Trusted Computing using a Trusted Platform Module (TPM) and AMD’s Secure Virtual Machine technology (SVM). While current solutions only protect against manipulation of existing logs, we go one step further by establishing hardware-based trust in the log producing application. Our solution ensures confidentiality, integrity and non-repudiation during creation, storage and transmission of log data.

[7]: A logger in the cloud capable of keeping a secure, time-synchronized and tamper-evident log of medical device and patient information allows efficient forensic analysis in cases of adverse events or attacks on interoperable medical devices. A secure logger as such must meet requirements of confidentiality and integrity of message logs and provide tamper-detection and tamper-evidence. In this paper, we propose a design for such a cloud-based secure logger using the Intel Software Guard Extensions (SGX) and the Trusted Platform Module (TPM). The proposed logger receives medical device information from a dongle attached to a medical device. The logger relies on SGX, TPM and standard encryption to maintain a secure communication channel even on an untrusted network and operating system. We also show that the logger is resilient against different kinds of attacks such as Replay attacks, Injection attacks and Eavesdropping attacks.
Modern TPM- and TEE-based approaches [7] [3] [5] [5]5 still fall short of satisfying many desirable properties identified in past work. Public verifiability of origin, as in [5]5 , has not been addressed in recent TEE loggers, which could be potentially useful to authenticate system data from remote devices, e.g. generating trust scores from log data for access control [1] and continuous authentication [4] [2] . Recent TEE-based schemes, i.e. [3] and [7] , focus primarily on protecting logs being received by a server-side log processing application; an attacker on the source device may simply tamper the logs before reaching the server that applies some tamper-resistance algorithm. To complicate matters, source devices are unlikely to transmit logs in real-time to minimise network and computational overhead, and so secure storage methods should be used to preserve unsent logs. Additionally, TEEs typically contain other security-critical applications, e.g. for fingerprint matching (as in Android https: source.android.com security authentication fingerprint-hal ) and payment tokenisation (see Samsung Pay http: developer.samsung.com tech-insights pay device-side-security ). As a result, a TEE-based logging mechanism should operate with reasonable resource consumption, e.g. run-time memory, to limit the rise of Denial of Service (DoS) conditions.