The recent rapid growth in Internet of Things (IoT) technologies is enriching our daily lives but significant information security risks in IoT fields have become apparent. In fact, there have been large-scale botnet attacks that exploit undiscovered vulnerabilities, known as zero-day attacks. Several intrusion detection methods based on network traffic monitoring have been proposed to address this issue. These methods employ federated learning to share learned attack information among multiple IoT networks, aiming to improve collective detection capabilities against attacks including zero-day attacks. Although their ability to detect zero-day attacks with high precision has been confirmed, challenges such as autonomous labeling of attacks from traffic information and attack information sharing between different device types still remain. To resolve the issues, this paper proposes IDAC, a novel intrusion detection method with autonomous attack candidate labeling and federated learning-based attack candidate sharing. The labeling of attack candidates in IDAC is executed using information autonomously extracted from traffic information, and the labeling can also be applied to zero-day attacks. The federated learning-based attack candidate sharing enables candidate aggregation from multiple networks, and it executes attack determination based on the aggregated similar candidates. Performance evaluations demonstrated that IDS with IDAC within networks based on attack candidates is feasible and achieved comparable detection performance against multiple attacks including zero-day attacks compared to the existing methods while suppressing false positives in the extraction of attack candidates. In addition, the sharing of autonomously extracted attack candidates from multiple networks improves both detection performance and the required time for attack detection.

We have developed a flat device structure, which we call “FLAT”, with no isolation grooves/ridges and no Si substrate etching in the imaging area of the CMOS Image Sensor (CIS). We employed this FLAT structure to achieve a 1.12 μm pitch pixel CIS with a 1.25 transistor/pixel architecture and excellent image quality. It uses FLAT transistors(Trs) that generate greatly-reduced 1/f noise, and FLAT isolators (Isos) that increase the saturation capacity (Qs) due to increasing both effective photodiode (PD) area and PD potential under low dark current.

Multi-hop networks, such as WSNs, become an object of increasing attention as an emerging technology which plays an important role for practical IoT applications. These multi-hop networks generally consist of mobile and small terminals with limited resources, which makes them vulnerable to various network status changes. Moreover, the limited nature of terminal resources available, especially in terms of battery capacity, is one of the most important issues to be addressed in order to prolong their operating time. In order to ensure efficient communications in such networks, much research has already been conducted, especially in the field of routing and transmission technologies. However, conventional approaches adopted in the routing field still suffer from the so-called energy hole problem, usually caused by unbalanced communication loads existing due to difficulties in adaptive route management. To address this issue, the present paper proposes a novel routing algorithm that utilizes ACO-inspired routing based on residual energy of terminals. Operational evaluation reveals its potential to ensure balanced energy consumption and to boost network performance.

The potential of ad hoc networks, which enable flexible and dynamic network establishment only by mobile terminals equipped with wireless communication devices, has recently attracted attention for the coming IoT era. Although the nature of ad hoc networks shows the advantages of their autonomous and distributed network management, a manifestation of drawbacks owing to the nature of wireless communication and the mobility of terminals are inevitable. Many routing protocols have already been proposed to address the issues by adapting to nature and achieving a certain level of improvement. However, the routing protocols still suffer from difficulties in information collection for routing and adaptive route management during communication. Moreover, there is another issue that end pair-based routing procedures prevent other end pairs from reusing the routing information effectively. To address the drawbacks of conventional routing protocols, this paper proposes VORTEX, a novel routing protocol that employs an opportunistic routing strategy using hierarchization. One of the characteristic features of VORTEX is its network-driven opportunistic forwarding, in which packets travel toward destination terminals using hierarchy as a guide without conventional route discovery procedures. Moreover, another characteristic feature of VORTEX is that the hierarchical structure also contributes to adapting to communication environment changes in an autonomous manner. In other words, VORTEX enables flexible network-wide information-based routing only with the locally collected information. The simulation results show that the proposed VORTEX could provide better service quality and reliability with improved efficiency compared to the conventional routing protocols. Furthermore, the most significant contribution is not only in the communication performance but also VORTEX omits route discovery or route maintenance from routing protocols, and formed networks themselves have a function to deliver packets toward destination terminals.

Current AI&IoT edge devices run complex applications and are under the threat of stealthy attacks that are not easily detected by traditional security systems. Provenance auditing is a promising technique for determining the ramification of an attack from DAG (Directed Acyclic Graph) of event logs. However, the original provenance auditing was designed for personal computers and is not suitable for edge devices. Therefore, introducing provenance auditing on edge devices raises the following three problems. (1) Current edge devices have relatively powerful CPUs, but they are not enough for provenance auditing. (2) Most provenance auditing tools are developed as normal applications, and the log data is exposed to an untrusted area. (3) Most edge devices are used outdoors without an administrator (e.g., smart city) and must be managed by secure M2M (Machine to Machine). To prove these problems, we propose TEE-PA to securely collect system call logs on an edge device using TEE (Trusted Execution Environment) and send them to a remote provenance auditing on a powerful server. The system call logs are directly transferred from the kernel to the TEE and are not exposed to administrators as well as attackers, making it more secure than traditional provenance auditing. Although the kernel runs in an untrusted REE (Rich Execution Environment) and has a semantic gap from the TEE, TEE-PA offers a semi-TCB (Trusted Computing Base) that measures the kernel integrity check mechanism from the TEE at boot time and partially trusts the kernel. Operational correctness is periodically confirmed by unpredictable heartbeat messages sent from the remote provenance auditing server. If the correctness is not confirmed in the logs on the server, heartbeat message is not sent, triggering an autonomous recovery with a system reset of the watchdog timer protected by the TEE. We implemented a prototype of TEE-PA on the Arm TrustZone of Raspberry Pi3 with SPADE and LKRG (Linux Kernel Runtime Guard) as remote provenance auditing and kernel integrity check. We demonstrate that TEE-PA can determine the ramifications of stealthy attacks (fileless malware and shell command attacks) with acceptable performance. The performance evaluation estimates that remote provenance auditing is 19 times faster than on-board provenance auditing.

In ad hoc networks, broadcast-based forwarding protocols called opportunistic routing have been proposed. In general backoff-based opportunistic routing protocols, each receiver autonomously makes a forwarding decision using a random backoff time based on logical distance. However, each potential forwarder must wait for the expiration of the backoff timer before the packet forwarding. Moreover, they cannot gain forwarding path diversity in sparse environments. In this paper, we propose a novel forwarder selection method for opportunistic routing. In the proposed method, a terminal called, a prioritized forwarder, and which is selected from among neighbours and can forward packets without using the backoff time. In addition, we integrate a hop-by-hop retransmission control in the proposed method, which improves the packet transmission success rate in sparse environments. We evaluate the proposed method in comparison with the conventional protocols in computer simulations.