In-vehicle communications are not designed for message exchange between the vehicles and outside systems originally. Thus, the security design of message protection is insufficient. Moreover, the internal devices do not have enough resources to process the additional security operations. Nonetheless, due to the characteristic of the in-vehicle network in which messages are broadcast, secure message transmission to specific receivers must be ensured. With consideration of the facts aforementioned, this work addresses resource problems by offloading secure operations to high-performance devices, and uses attribute-based access control to ensure the confidentiality of messages from attackers and unauthorized users. In addition, we reconfigure existing access control based cryptography to address new vulnerabilities arising from the use of edge computing and attribute-based access control. Thus, this paper proposes an edge computing-based security protocol with fine-grained attribute-based encryption using a hash function, symmetric-based cryptography, and reconfigured cryptographic scheme. In addition, this work formally proves the reconfigured cryptographic scheme and security protocol, and evaluates the feasibility of the proposed security protocol in various aspects using the CANoe software.

As ransomware attacks have been prevalent, it becomes crucial to make anti-ransomware solutions that defend against ransomwares these days. In this paper, we propose a new SSD-assisted ransomware defense system, called SSD-Insider++, which prevents users' files from being damaged by ransomware attacks. SSD-Insider++ is composed of two novel features, ransomware detection and perfect data recovery, which are implemented in an SSD controller. The detection algorithm observes I/O patterns of a host system and decides whether or not the host is being attacked by ransomwares in an early stage. Once an encryption attack is detected, the recovery algorithm is triggered to recover original files by leveraging a delayed deletion feature of an SSD at a low cost. We have implemented SSD-Insider++ in an open-channel SSD platform and carried out a set of experiments with eight real-world and three in-house ransomwares. Our experimental results show that SSD-Insider++ achieves high accuracy of detecting ransomwares with 0% FRR/FAR in most cases and provides an instant data recovery with 0% data loss in 1 second. The performance impact of running SSD-Insider++ in an SSD controller is negligible — only 80 ns and 226 ns are spent more for handling 4-KB reads and writes, respectively.

Mobile devices, such as smartphones, have become a necessity in our daily life. However, users may notice that after being used for a long time, mobile devices begin to experience sluggish response. Based on an empirical study on a set of aged mobile devices, we identified that file fragmentation is among the key factors that contribute to the progressive degradation of response time. This study takes a three-step approach: First, we designed a set of reproducible file-system aging processes based on User-Interface (UI) script replay. Through the aging processes, we confirmed that file fragmentation quickly emerged, and SQLite files were among the most severely fragmented files. Second, based on the workloads of a selection of popular mobile applications, we observed that file fragmentation did impact on user-perceived latencies. Specifically, the launching time of Chrome on an aged file system was 79\% slower than it was on a pristine file system. Third, we evaluated existing treatments of file fragmentation, including space preallocation, persistent journal space, and file defragmentation to understand their efficacies and limitations. We also evaluated a state-of-the-art copyless defragmenter, janusd, to show its advantage over the existing methods.

With increase in real-time systems, users have come to demand information with low latency. However, as the blocklength becomes finite to reduce communication duration, the decoding error probability is newly considered. In this letter, we consider downlink cellular networks, where base stations (BSs) periodically transmit information with finite blocklength to a user. To analyze the freshness of information, we derive the average age of information (AoI) and the AoI violation probability in a closed-form using the upper bound of the average decoding error probability. Finally, we show that an optimal blocklength that minimizes the AoI exists.

This article traces the evolution of SSD (solid-state drive) interfaces, examining the transition from the block storage paradigm inherited from hard disk drives to SSD-specific standards customized to flash memory. Early SSDs conformed to the block abstraction for compatibility with the existing software storage stack, but studies and deployments show that this limits the performance potential for SSDs. As a result, new SSD-specific interface standards emerged to not only capitalize on the low latency and abundant internal parallelism of SSDs, but also include new command sets that diverge from the longstanding block abstraction. We first describe flash memory technology in the context of the block storage abstraction and the components within an SSD that provide the block storage illusion. We then describe the genealogy and relationships among academic research and industry standardization efforts for SSDs, along with some of their rise and fall in popularity. We classify these works into four evolving branches: (1) extending block abstraction with host-SSD hints/directives; (2) enhancing host-level control over SSDs; (3) offloading host-level management to SSDs; and (4) making SSDs byte-addressable. By dissecting these trajectories, the article also sheds light on the emerging challenges and opportunities, providing a roadmap for future research and development in SSD technologies.

Key-value store based on a log-structured merge-tree (LSM-tree) is preferable to hash-based key-value store, because an LSM-tree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD), and, consequently, KV-SSDs typically use hash-based schemes. We present PinK , a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99th percentile tail latency by 73%, improves average read latency by 42%, and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree. We also find that PinK is able to provide a flexible design space for a wide range of KV workloads by leveraging the read-write tradeoff in LSM-trees.