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Spectre attack exploits the vulnerability in speculative execution, an optimization technique for modern superscalar processors. Among the attack variants, Spectre-BTB and Spectre-RSB are the most threatening because they allow adversaries to execute arbitrary code in the transient execution context. However, there are few mitigation techniques for these Spectre variants due to the high degree of implementation difficulty. In this paper, we propose MicroCFI, a hardware/software co-design approach to mitigate Spectre-BTB and Spectre-RSB. The main idea of MicroCFI is to enforce control-flow integrity (CFI) in microarchitectural level of a program’s execution. Specifically, MicroCFI strictly limits possible forward and backward indirect branch targets predicted by BTB and RSB by imposing CFI properties on all potential targets. As indirect branches only have destinations to valid targets that satisfy these properties, MicroCFI significantly reduces the chance of arbitrary code execution in Spectre attacks. We implemented a prototype of MicroCFI using an LLVM compiler and performed an evaluation on MARSSx86, a simulator for x86 microarchitectures. The security evaluation shows that MicroCFI reduces the number of available Spectre gadgets by more than 90%, significantly increasing the complexity of the attack. The performance evaluation using the SPEC CPU 2017 benchmarks shows that MicroCFI introduces negligible performance overhead.

Modern OSs expose an interface for monitoring CPU temperature to unprivileged users for effective user decision-based thermal management. Due to the low sampling rate and resolution, thermal sensors have generally been restricted to the construction of covert channels. However, exposing the thermal interface to unprivileged users may be problematic, because the heat emission inside a CPU core is affected by program execution on the core; an attacker may be able to infer the secret information of the program by exploiting the thermal interface as a side-channel. In this paper, we extensively analyze digital thermal sensors in Intel CPUs and show that it is possible to implement a software-based thermal side-channel attack. Specifically, by analyzing some properties of the thermal sensors, we inferred that the thermal sensor makes it possible to distinguish between a cache hit and a physical memory access in memory load operations. Based on the analysis results, we implement ThermalBleed, a thermal side-channel attack that breaks kernel address space layout randomization (KASLR) in Linux systems. Moreover, by conducting an in-depth analysis, we identify useful hidden properties of the Intel thermal sensors. Our analysis establishes a stepping stone to build a more precise and effective thermal side-channel attack in the future. To the best of our knowledge, this is the first work that extends a thermal covert channel to a practical side-channel attack by exploring the properties of Intel digital thermal sensors.

Crypto libraries such as OpenSSL and Libgcrypt are essential building blocks for implementing secure cloud services. Unfortunately, these libraries are subject to cache side-channel attacks, which are more devastating in cloud environments where inevitable cache contention among different tenants occurs. Previous approaches for mitigating cache side-channel attacks have limitations in terms of the deployability and security; these hinder utilization in cloud services. In this paper, we propose an R2-relocator, a novel library protection technique based on moving target defence. When injected into a running process, the R2-relocator performs randomized relocation of the library during runtime. By doing this, it transforms a vulnerable crypto library into one that randomly changes its memory (cache) location, thereby preventing the delivery of cache side-channel attacks against the library. The proposed technique achieves robust protection against cache side-channel attacks for all crypto libraries, even those containing unpatched critical vulnerabilities, without the need for reconfiguration of the library. Extensive evaluations of security, performance, and deployability of the R2-relocator demonstrate its effectiveness for secure cloud services.

Microarchitectural data sampling (MDS) attacks leak secret data from the internal buffers of a processor to the attacker during transient execution. Because of the narrow window of transient execution, previous MDS attacks relied on repetitive sampling to obtain arbitrarily sized data from the buffer. However, as an MDS attacker cannot control the address for data leakage, such an approach significantly degrades the signal-to-noise ratio in the sampled data. In this paper, we propose a novel multibyte microarchitectural data sampling technique for performing MDS attacks. The proposed technique allows several continuous bytes to be captured in one execution without repetition of sampling. The implementation of the technique is quite challenging, because a transient execution window is not sufficiently large to allow multibyte sampling to be completed. We address this problem by leveraging a return stack buffer-based speculation technique, which originally was used for variants of Spectre-type attacks. We repurpose it to enlarge the transient execution window in our attack. Our implementations can capture data of up to 16 bytes in length in one execution from a line-fill buffer. To validate the effectiveness of the multibyte sampling technique, we demonstrate session key extraction attacks against secure network protocols. In particular, our objective is to extract AES-128 and AES-256 keys from TLS and SSH applications. To recover session keys in a postprocessing phase efficiently, we also propose a novel clustering-based search method that assembles the bytes of interest from the noisy sampled data. The experimental results show that our technique can successfully extract AES-128/256 session keys from victim applications with a probability of at least 98% and a reasonable search complexity.

Meltdown is a microarchitectural side-channel attack that extracts sensitive data in the kernel space of operating systems (OSs). Meltdown deliberately creates transient executions by exploiting an out-of-order execution technique and obtains the execution results through a cache covert channel. In a previous attack, an OS signal handler and hardware transactional memory support (i.e., Intel TSX) were used to establish the cache covert channel. However, both methods restricted the effectiveness of the attack owing to the large amount of system noise caused by the context switching of signal handlers and the narrow range of TSX-enabled processors. Hence, we propose a new variant of the Meltdown attack using a return stack buffer (RSB). The RSB enables the establishment of a low-noise cache covert channel without relying on processor-specific hardware features, such as TSX. The wide usage of the RSB in commodity processors further improves the effectiveness of the proposed attack. We present the details of our implementation of the attack and evaluate the performance. Furthermore, we overview several existing countermeasures against the proposed attack.

Mail user agent (MUA) programs provide an integrated interface for email services. Many MUAs support email encryption functionality to ensure the confidentiality of emails. In practice, they encrypt the content of an email using email encryption standards such as OpenPGP or S/MIME, mostly implemented using GnuPG. Despite their widespread deployment, there has been insufficient research on their software structure and the security dependencies among the software components of MUA programs. In order to understand the security implications of the structures and analyze any possible vulnerabilities of MUA programs, we investigated a number of MUAs that support email encryption. As a result, we found severe vulnerabilities in a number of MUAs that allow cache side-channel attacks in virtualized desktop environments. Our analysis reveals that the root cause originates from the lack of verification and control over the third-party cryptographic libraries that they adopt. In order to demonstrate this, we implemented a cache side-channel attack on RSA in GnuPG and then conducted an evaluation of the vulnerability of 13 MUAs that support email encryption in Ubuntu 14.04, 16.04 and 18.04. Based on our experiment, we found that 10 of these MUA programs (representing approximately 77% of existing MUA programs) allow the installation of a vulnerable version of GnuPG, even when the latest version of GnuPG, which is secure against most cache side-channel attacks, is in use. In order to substantiate the importance of the vulnerability we discovered, we conducted a FLUSH+RELOAD attack on these MUA programs and demonstrated that the attack restored 92% of the bits of the 2048-bit RSA private key when the recipients read a single encrypted email.

Nowadays, various computing services are often hosted on cloud platforms for their availability and cost effectiveness. However, such services are frequently exposed to vulnerabilities. Therefore, many countermeasures have been invented to defend against software hacking. At the same time, more complicated attacking techniques have been created. Among them, code-reuse attacks are still an effective means of abusing software vulnerabilities. Although state-of-the-art address space layout randomization (ASLR) runtime-based solutions provide a robust way to mitigate code-reuse attacks, they have fundamental limitations; for example, the need for system modifications, and the need for recompiling source codes or restarting processes. These limitations are not appropriate for mission-critical services because a seamless operation is very important. In this paper, we propose a novel ASLR technique to provide memory rerandomization without interrupting the process execution. In addition, we describe its implementation and evaluate the results. In summary, our method provides a lightweight and seamless ASLR for critical service applications.

Cache side channel attacks extract secret information by monitoring the cache behavior of a victim. Normally, this attack targets an L3 cache, which is shared between a spy and a victim. Hence, a spy can obtain secret information without alerting the victim. To resist this attack, many detection techniques have been proposed. However, these approaches have limitations as they do not operate in real time. This article proposes a real-time detection method against cache side channel attacks. The proposed technique performs the detection of cache side channel attacks immediately after observing a variation of the CPU counters. For this, Intel PCM (Performance Counter Monitor) and machine learning algorithms are used to measure the value of the CPU counters. Throughout the experiment, several PCM counters recorded changes during the attack. From these observations, a detecting program was implemented by using these counters. The experimental results show that the proposed detection technique displays good performance for real-time detection in various environments.

Remote code execution attacks against network devices become major challenges in securing networking environments. In this paper, we propose a detection framework against remote code execution attacks for closed source network devices using virtualization technologies. Without disturbing a target device in any way, our solution deploys an emulated device as a virtual machine (VM) instance running the same firmware image as the target in a way that ingress packets are mirrored to the emulated device. By doing so, remote code execution attacks mounted by maliciously crafted packets will be captured in memory of the VM. This way, our solution enables successful detection of any kind of intrusions that leaves memory footprints.

With the successful proliferation of data outsourcing services, security and privacy issues have drawn significant attention. Data authentication in particular plays an essential role in the storage of outsourced digital content and keeping it safe from modifications by inside or outside adversaries. In this paper, we focus on online data authentication using a Merkle (hash) tree to guarantee data integrity. By conducting in-depth diagnostics of the side channels of the Merkle tree-based approach, we explore novel solutions to improve the security and reliability of the maintenance of outsourced data. Based on a thorough review of previous solutions, we present a new method of inserting auxiliary random sources into the integrity verification proof on the prover side. This prevents the exposure of partial information within the tree structure and consequently releases restrictions on the number of verification execution, while maintaining desirable security and reliability of authentication for the long run. Based on a rigorous proof, we show that the proposed scheme maintains consistent reliability without being affected by continuous information leakage caused by repetitions of the authentication process. In addition, experimental results comparing with the proposed scheme with other state-of-the-art studies demonstrate its efficiency and practicality.

Constant-time technique is of crucial importance to prevent secrets of cryptographic algorithms from leakage by cache attacks. In this paper, we propose Permute-Scatter-Gather, a novel constant-time method for the modular exponentiation that is used in the RSA cryptosystem. On the basis of the scatter-gather design, our method utilizes pseudo-random permutation to obfuscate memory access patterns. Based on this strategy, the resistance against fine-grained cache attacks is ensured, i.e., providing the higher level of security than the existing scatter-gather implementations. Evaluation shows that our method outperforms the OpenSSL library at most 11% in the mainstream Intel processors.

The smart grid is a promising electrical grid paradigm for enhancing flexibility and reliability in power transmission through two-way communications among grid entities. In the smart grid system, the privacy of usage information measured by individual smart meters has gained significant attention, owing to the possibility of personal information inference. Moreover, efficient and reliable power provisioning can be seriously impeded through illicit manipulations of aggregated data under the influence of malicious adversaries. Due to such potential risks, it becomes an important requirement for the smart grid to preserve privacy of metering data by secure aggregation and to authenticate the aggregated result in an efficient manner within large scale environments. From this perspective, this paper investigates the current status of security and privacy in smart grid systems and representative state-of-the-art studies in secure aggregation and authentication of metering data for future directions of a smart grid.