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With the advancement in information and communication technology, modern society has relied on various computing systems in areas closely related to human life. However, cyberattacks are also becoming more diverse and intelligent, with personal information and human lives being threatened. The moving target defense (MTD) strategy was designed to protect mission-critical systems from cyberattacks. The MTD strategy shifted the paradigm from passive to active system defense. However, there is a lack of indicators that can be used as a reference when deriving general system components, making it difficult to configure a systematic MTD strategy. Additionally, even when selecting system components, a method to confirm whether the systematic components are selected to respond to actual cyberattacks is needed. Therefore, in this study, we surveyed and analyzed existing cyberattack information and MTD strategy research results to configure a component dataset. Next, we found the correlation between the cyberattack information and MTD strategy component datasets and used this to design and implement the MTD-Diorama data visualization engine to configure a systematic MTD strategy. Through this, researchers can conveniently identify the attack surface contained in cyberattack information and the MTD strategies that can respond to each attack surface. Furthermore, it will allow researchers to configure more systematic MTD strategies that can be used universally without being limited to specific computing systems. [ABSTRACT FROM AUTHOR]

With the proliferation of electronic devices and electricity-based mobility solutions, the significance of wireless power transfer technology has increased substantially. However, ensuring secure and reliable power transmission to authorized users remains a significant challenge. Addressing this complex issue requires an integrated approach that balances efficiency, stability, and security considerations. While current efforts primarily focus on improving charging efficiency and user convenience, integrating robust security measures into wireless charging infrastructure is challenging due to its inherently open nature and susceptibility to external interference. Technical advancements are required to strengthen the security of the wireless charging infrastructure; however, these should be balanced with power loss management. This study tackles two core issues: the increasing hardware requirements for billing system authentication protocols and the interception of wireless charging signals by unauthorized users, leading to power theft and subsequent losses. To address these challenges, we propose a mechanism termed "LazyFrog". This mechanism dynamically adjusts the frequency hopping schedule, activating frequency changes only in response to detected threats during remote charging or upon identifying unauthorized access attempts. The proposed mechanism compares the expected power reception at the device with the actual power supplied by the charging station, enabling the detection of abnormal power losses. By minimizing unnecessary frequency changes and optimizing energy consumption, LazyFrog reduces hardware requirements. Moreover, we have implemented a relative distance estimation mechanism to facilitate efficient power transfer as wireless devices move within the charging environment. With these features, LazyFrog demonstrates a secure, flexible, and energy-efficient wireless charging system ready for practical application. [ABSTRACT FROM AUTHOR]

In an internet of things (IoT) platform with a copious number of IoT devices and active variation of operational purpose, IoT devices should be able to dynamically change their system images to play various roles. However, the employment of such features in an IoT platform is hindered by several factors. Firstly, the trivial file transfer protocol (TFTP), which is generally used for network boot, has major security vulnerabilities. Secondly, there is an excessive demand for the server during the network boot, since there are numerous IoT devices requesting system images according to the variation of their roles, which exerts a heavy network overhead on the server. To tackle these challenges, we propose a system termed FLEX-IoT. The proposed system maintains a FLEX-IoT orchestrater which uses an IoT platform operation schedule to flexibly operate the IoT devices in the platform. The IoT platform operation schedule contains the schedules of all the IoT devices on the platform, and the FLEX-IoT orchestrater employs this schedule to flexibly change the mode of system image transfer at each moment. FLEX-IoT consists of a secure TFTP service, which is fully compatible with the conventional TFTP, and a resource-efficient file transfer method (adaptive transfer) to streamline the system performance of the server. The proposed secure TFTP service comprises of a file access control and attacker deception technique. The file access control verifies the identity of the legitimate IoT devices based on the hash chain shared between the IoT device and the server. FLEX-IoT provides security to the TFTP for a flexible IoT platform and minimizes the response time for network boot requests based on adaptive transfer. The proposed system was found to significantly increase the attack-resistance of TFTP with little additional overhead. In addition, the simulation results show that the volume of transferred system images on the server decreased by 27% on average, when using the proposed system. [ABSTRACT FROM AUTHOR]

NAND flash memory-based storage devices are vulnerable to errors induced by NAND flash memory cells. Error-correction codes (ECCs) are integrated into the flash memory controller to correct errors in flash memory. However, since ECCs show inherent limits in checking the excessive increase in errors, a complementary method should be considered for the reliability of flash storage devices. In this paper, we propose a scheme based on lossless data compression that enhances the error recovery ability of flash storage devices, which applies to improve recovery capability both of inside and outside the page. Within a page, ECC encoding is realized on compressed data by the adaptive ECC module, which results in a reduced code rate. From the perspective of outside the page, the compressed data are not placed at the beginning of the page, but rather is placed at a specific location within the page, which makes it possible to skip certain pages during the recovery phase. As a result, the proposed scheme improves the uncorrectable bit error rate (UBER) of the legacy system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mobile devices such as sensors are used to connect to the Internet and provide services to users. Web services are vulnerable to automated attacks, which can restrict mobile devices from accessing websites. To prevent such automated attacks, CAPTCHAs are widely used as a security solution. However, when a high level of distortion has been applied to a CAPTCHA to make it resistant to automated attacks, the CAPTCHA becomes difficult for a human to recognize. In this work, we propose a method for generating a CAPTCHA image that will resist recognition by machines while maintaining its recognizability to humans. The method utilizes the style transfer method, and creates a new image, called a style-plugged-CAPTCHA image, by incorporating the styles of other images while keeping the content of the original CAPTCHA. In our experiment, we used the TensorFlow machine learning library and six CAPTCHA datasets in use on actual websites. The experimental results show that the proposed scheme reduces the rate of recognition by the DeCAPTCHA system to 3.5% and 3.2% using one style image and two style images, respectively, while maintaining recognizability by humans. [ABSTRACT FROM AUTHOR]