Trusted execution environments (TEEs) provide strong isolation for security-critical applications (enclaves) and their runtime data from potentially malicious operating systems. While TEEs also support secure storage by sealing data and storing it persistently on media, they do not ensure the integrity of sealed data, leaving it vulnerable to deletion or manipulation by an untrusted OS. In this work, we present Trusted Storage, a runtime storage isolation mechanism for TEEs that guarantees the integrity of TEE persistent data. The core design partitions storage into trusted and untrusted regions and enforces access control by locking MMIO regions and monitoring block I/O. To ensure portability, Trusted Storage requires no hardware modifications or additional hardware. We implemented a prototype, Trust-V, on the RISC-V platform. In particular, to support secure operation on legacy devices where security features are limited, Trust-V introduces a Virtual-M mode, a sandboxed privileged execution environment in machine mode, for securely hosting the monitor. Our evaluation demonstrates that, although Trust-V incurs up to 3.86× system overhead, it allows TEE software to reliably store and retrieve persistent data.

Advancements in the Internet of Things (IoT) have resulted in the connection and deployment of numerous smart and embedded devices. Although such devices enable various services such as smart grids, they attract more attackers to the IoT world. A trusted execution environment (TEE), which can be created by using TrustZone technology, is a promising security artifact for protecting critical operations and sensitive data of IoT devices. Unfortunately, although TrustZone is available in most ARM architecture-based devices ranging from microcontrollers to high-end smart devices, it has not been widely adopted by third-party IoT service providers because of its limited access. That is, because the TEE is maintained by the TEE platform vendors to preserve its security. Therefore, third parties must adhere to strict policies and procedures to ensure the deployment of trusted services in the TEE. This aspect hinders the fast development and deployment of IoT services. In this work, we propose 3rdParTEE to address this problem by enabling third-party IoT service providers to readily run their trusted services, thereby minimizing their dependency on the TEE maintainers. Specifically, 3rdParTEE facilitates the secure running of the third-party’s native kernel driver in the TEE without hampering the security of the existing TEE components. To demonstrate the effectiveness of our approach, we ran three kernel drivers for maintaining the IoT services platform (e.g., kernel integrity check) in the TEE. Additionally, during the performance evaluation, we observed a reasonable performance overhead of up to 7% when running the kernel drivers in such a secure manner.

Stack-based memory corruption vulnerabilities have been exploited, allowing attackers to execute arbitrary code and read/write arbitrary memory. Although several solutions have been proposed to prevent memory errors on the stack, they are either limited to a specific type of attack (either spatial or temporal attacks) or cause significant performance degradation. In this article, we introduce SaVioR, an efficient and comprehensive stack protection mechanism. The key technique involves randomization of the stack layout to reduce its predictability and exploitability. SaVioR isolates an individual object from spatially and temporally adjacent vulnerable objects and randomizes each object's location, which prevents attackers from predicting the stack layout and thus reduces the likelihood of memory errors being exploited. We implemented SaVioR based on the LLVM compiler framework and applied it to the SPEC CPU2006 benchmarks and real-world applications. Our security evaluation showed that SaVioR provides a high degree of randomness in the stack layout and thus reduces the likelihood of successful exploitation of spatial and temporal memory errors on the stack. Our performance evaluation also demonstrated that it incurs a modest performance overhead (14 percent) with the SPEC CPU2006 benchmark suite, which improves performance compared to the state-of-the-art stack protection while achieving a comparable security level.

Higher privileged trust anchors such as thin hypervisors and Trust-Zone have been adopted to protect mobile OSs. For instance, the Samsung Knox security platform implements a kernel integrity monitor based on a hardware-assisted virtualization technique for 64-bit devices. Although it protects the OS kernel integrity, the monitoring platform itself can be a target of attackers if it encompasses exploitable bugs. In this paper, we propose SelMon, a portable way of self-protecting kernel integrity monitors without introducing another higher privileged trust anchor. To this end, we first logically separate the regions of the integrity monitor into two parts: privileged and non-privileged regions. Then, we ensure that only the privileged region code can access the critical data objects that can be exploited to compromise the monitor integrity (e.g., the hypervisor page table). The non-critical operations in terms of preserving the monitor integrity are conducted in the non-privileged region. In addition to the privilege separation, we also illustrate how to utilize the general hardware features, watchpoint and data execution prevention (DEP), to ensure the robustness of the separation. In the evaluation, it was found that our approach imposes a negligible overhead of 2% in the worst case with SPEC CPU2006.

ARM TrustZone provides a Trusted Execution Environment (TEE) to isolate security-critical services, which are generally invoked from the Rich Execution Environment (REE) through a communication channel established by executing the Secure Monitor Call (SMC) with the general registers configured as input parameters. Unfortunately, the communication channel has been abused by adversaries to incur misbehavior of the TEE, to analyze the internal working of the TEE, and to exploit its vulnerabilities. We therefore propose the TEE defense (TFence) framework that enables the creation of a partially privileged (par-priv) process, which benefits from the coordination of the system mode and virtualization extension. More specifically, on ARM architecture, direct invocation of hypercall and SMC is not allowed in the user process; however, we limitedly escalate the privilege of the process to enable it to directly communicate with trust anchors such as hypervisor and TrustZone. This approach enabled us to remove the kernel dependency when the process communicates with the TEE, which also reduces the attack surface to the critical part of the application involved in the communication. Besides, direct communication with the hypervisor facilitates the adoption of application-shielding approaches to protect the critical part and to restrict arbitrary access to the TEE.

Memory disclosure vulnerabilities have been exploited in the leaking of application secret data such as crypto keys (e.g., the Heartbleed Bug). To ameliorate this problem, we propose an in-process memory isolation mechanism by leveraging a common hardwarefeature, namely, hardware debugging. Specifically, we utilize a watchpoint to monitor a particular memory region containing secret data. We implemented the PoC of our approach based on the 64-bit ARM architecture, including the kernel patches and user APIs that help developers benefit from isolated memory use. We applied the approach to open-source applications such as OpenSSL and AESCrypt. The results of a performance evaluation show that our approach incurs a small amount of overhead.

Hardware debugging facilities, such as watchpoints, have been used for software development and analysis. In this paper, we expanded the use of watchpoints as a hardware security primitive for enhancing the runtime security of mobile devices. By analyzing the watchpoints in detail, we derived useful watchpoint properties that can be exploited to build security applications. Based on our analysis, we designed example applications for hardening the OS kernel by exploiting watchpoints. The proposed applications were implemented on a Juno development board with 64-bit ARM architecture (ARMv8). Hardening the kernel by fully enabling the proposed schemes was found to impose reasonable overhead, i.e., 3% with SPEC CPU2006.

External hardware-based kernel integrity monitors have been proposed to mitigate kernel-level malwares. However, the existing external approaches have been limited to monitoring the static regions of kernel while the latest rootkits manipulate the dynamic kernel objects. To address the issue, we present KI-Mon, a hardware-based platform that introduces event-triggered monitoring techniques for kernel dynamic objects. KI-Mon advances the bus traffic snooping technique to not only detect memory write traffic on the host bus but also filter out all but meaningful traffic to generate events. We show how kernel invariant verification software can be developed around these events, and also provide a set of APIs for additional invariant verification development. We also report our findings and considerations on the unique challenges for external monitors – such as cache coherency, dynamic object tracing. We introduce host-side kernel changes that alleviate these issues that involve changes in kernel's object allocation and cache policy control. We have built a prototype of KI-Mon on the ARM architecture to demonstrate the efficacy of KI-Mon's event-triggered mechanism in terms of performance overhead for the monitored host system and the processor usage of the KI-Mon processor.

ARM TrustZone is widely used to provide a Trusted Execution Environment (TEE) for mobile devices. However, the use of TrustZone is limited because TrustZone resources are only available for some pre-authorized applications. In other words, only alliances of the TrustZone OS vendors and device manufacturers can use TrustZone to secure their services. To help overcome this problem, we designed the PrivateZone framework to enable individual developers to utilize TrustZone resources. Using PrivateZone, developers can run Security Critical Logics (SCL) in a Private Execution Environment (PrEE). The advantage of PrivateZone is its leveraging of TrustZone resources without undermining the security of existing services in the TEE. To guarantee this, PrivateZone creates a PrEE using a memory region that is isolated from both the Rich Execution Environment (REE) and TEE. In this paper, we describe the design and implementation of PrivateZone. The prototype of PrivateZone was implemented on an Arndale board with a Cortex-A15 dual-core processor. We built PrivateZone by exploring both security and virtualization extensions of the ARM architecture. To illustrate the usage and the efficacy of PrivateZone, we developed an Android application based on PrivateZone framework, and evaluated the performance overhead imposed on the OS in the REE and SCLs in the PrEE.

We propose methods for scheduling multimedia soft real-time tasks in an open system environment. We discuss two issues, guaranteeing the schedulability of every task in the application and meeting the QoS of multimedia soft real-time tasks. First, when a real-time application is composed of a heterogeneous task set, hard real-time tasks and multimedia soft real-time tasks, the operating system must guarantee the schedulability of each task in the application. These guarantees can be achieved by preserving the CPU bandwidth of each task in the application. We have designed a server framework that preserves the CPU bandwidth of each task in the application. Each task can select its own server that can satisfy its time constraints. Second, when an operating system schedules multimedia soft real-time tasks in an open system, it is important for the operating system not only to support sufficient QoS level for the task, but also to utilize the CPU bandwidth of the system efficiently. We invented a new method of utilizing the CPU bandwidth of the system efficiently while supporting the requested QoS level.