Potential software weakness, which can lead to exploitable security vulnerabilities, continues to pose a risk to computer systems. According to Common Vulnerability and Exposures, 14,714 vulnerabilities were reported in 2017, more than twice the number reported in 2016. Automated vulnerability detection was recommended to efficiently detect vulnerabilities. Among detection techniques, static binary analysis detects software weakness based on existing patterns. In addition, it is based on existing patterns or rules, making it difficult to add and patch new rules whenever an unknown vulnerability is encountered. To overcome this limitation, we propose a new method—Instruction2vec—an improved static binary analysis technique using machine. Our framework consists of two steps: (1) it models assembly code efficiently using Instruction2vec, based on Word2vec; and (2) it learns the features of software weakness code using the feature extraction of Text-CNN without creating patterns or rules and detects new software weakness. We compared the preprocessing performance of three frameworks—Instruction2vec, Word2vec, and Binary2img—to assess the efficiency of Instruction2vec. We used the Juliet Test Suite, particularly the part related to Common Weakness Enumeration(CWE)-121, for training and Securely Taking On New Executable Software of Uncertain Provenance (STONESOUP) for testing. Experimental results show that the proposed scheme can detect software vulnerabilities with an accuracy of 91% of the assembly code.

This paper presents a hybrid flash file system (HFFS) based on both NOR flash and NAND flash memory. In a conventional NAND flash-based flash file system, there is a trade-off between life span and durability in the frequent writing of small amounts of data. Because NAND flash supports only a page-level I/O, at least one page is wasted in the synchronous writing of small amounts of data. The wasting of pages reduces the utilization and life span of the NAND flash. To alleviate the utilization problem, some NAND flash-based flash file systems write small amounts of data asynchronously with RAM buffers, though buffering in RAM decreases the durability of the system. Our HFFS eliminates the trade-off between life span and durability. It synchronously stores data as a log in the NOR flash, whenever we append small amounts of data to a file. The merged logs are then flushed to the NAND flash in a page-aligned fashion. The implementation of our HFFS is based on our previous NAND flash-based file system, called CFFS, The experimental results reveal that our HFFS provides a longer life span than a conventional NAND flash-based synchronous flash file system with a similar level of durability.

Fine particulate matter (PM) is associated with an increased risk of respiratory and cardiovascular diseases. Fine PM absorbs water molecules at high relative humidity, and then their size grows. Such hygroscopic growth causes a large error when monitoring PM concentrations. To lower the relative humidity, monitors use an indirect heating device, which is large and consumes large amounts of power. The problem with conventional particle separators is that their efficiency depends on temperature and humidity, and their traditional structure, which lets air flow downward. As such, this paper addresses these problems and presents a PM monitor with a new type of dryer that is free from these problems. The proposed monitor requires less energy and has an efficient dehumidifier and a new structure in which air flows upward. The presented experiments were conducted to compare the proposed device with a reference monitor managed by a governmental institute, and to evaluate the effect of the dehumidifier, the relative precision of the proposed devices, and the correlation with the reference monitor. The experimental results showed that the proposed monitor satisfies the U.S. EPA indicators for class III monitors.

Flash-based storage is considered to be a de facto storage module for sustainable Internet of things (IoT) platforms under a harsh environment due to its relatively fast speed and operational stability compared to disk storage. Although their performance is considerably faster than disk-based mechanical storage devices, the read and write latency still could not catch up with that of Random-access memory (RAM). Therefore, RAM could be used as storage devices or systems for time-critical IoT applications. Despite such advantages of RAM, a RAM-based storage system has limitations in its use for sustainable IoT devices due to its nature of volatile storage. As a remedy to this problem, this paper presents a durable hybrid RAM disk enhanced with a new read interface. The proposed durable hybrid RAM disk is designed for sustainable IoT devices that require not only high read/write performance but also data durability. It includes two performance improvement schemes: rapid resilience with a fast initialization and direct byte read (DBR). The rapid resilience with a fast initialization shortens the long booting time required to initialize the durable hybrid RAM disk. The new read interface, DBR, enables the durable hybrid RAM disk to bypass the disk cache, which is an overhead in RAM-based storages. DBR performs byte–range I/O, whereas direct I/O requires block-range I/O; therefore, it provides a more efficient interface than direct I/O. The presented schemes and device were implemented in the Linux kernel. Experimental evaluations were performed using various benchmarks at the block level till the file level. In workloads where reads and writes were mixed, the durable hybrid RAM disk showed 15 times better performance than that of Solid-state drive (SSD) itself.

KSII Transactions on Internet and Information Systems TIIS Paper Details