WiPiEC Journal - Works in Progress in Embedded Computing Journal

Exposing Vulnerabilities in NMEA Gateways: Insights from Shodan and Honeypot Experiments

2026-06-17T09:14:38+00:00

Abstract—As connectivity increases through the Internet of Things (IoT) and Industry 4.0. Previously isolated systems gained remote access capabilities and became more exposed to cyberattacks. For example, in the maritime domain, the Global Maritime Transportation System (GMTS) is considered a high-potential target. Attacking a GMTS system with malware has been shown to influence ships or disrupt onboard operations. Another significant component of the ship network is an NMEA gateway. Prior research has shown evidence of NMEA gateways being exposed to the Internet, and our previous work experimentally demonstrated four practical attack vectors against such gateways: GPS spoofing, AIS injection, autopilot manipulation, and resource exhaustion. However, it remains unclear whether they have been targeted by adversaries or how an attacker could exploit them.

In this work, an NMEA gateway honeypot is designed, implemented, and deployed. The design of the honeypot is inspired by using Shodan, which is used to identify real and exposed NMEA gateways. Our Shodan results show that Internet-exposed NMEA gateways are widely spread. For instance, the refined $GPRMC-based Shodan query identified 4,305 unique endpoints that transmitted NMEA messages during the observation period, of which 1,542 were analyzed in detail to identify their vulnerabilities and other parameters, such as the attack window. As per the honeypot, although no attacks against the specific NMEA gateway were captured, the honeypot logs captured other types of attacks, such as automated scanning and reconnaissance efforts. These findings indicate that NMEA gateways could become real targets in the near future if not configured or secured properly.

Efficient Coins Selection for UTXOs through Evolutionary and Random Draw Methods

2026-06-17T09:14:45+00:00

This study proposes and evaluates a novel hybrid optimization framework that integrates stochastic Random Draw sampling with Evolutionary Algorithms (EA) to address the multi-objective challenges of Unspent Transaction Output (UTXO) selection. In digital asset management, selecting an optimal subset of coins from fragmented wallet pools requires balancing transaction privacy, economic efficiency, and computational throughput-a task complicated by a combinatorial search space exceeding 10^41 possibilities. The proposed methodology utilizes a random-draw seeding mechanism to bypass initial combinatorial complexity, followed by iterative evolutionary refinement. Results demonstrate that this hybrid approach achieves a 97% success rate and a convergence speed 43% faster than standard optimization techniques, reaching optimal solutions in an average of 14 ms. Furthermore, the inclusion of mutation and crossover operators ensures high UTXO diversity, significantly enhancing privacy by mitigating identifiable transaction patterns common in deterministic heuristics. This research concludes that the hybrid model provides a robust, scalable solution for real-time wallet infrastructures, effectively reconciling the trade-offs between long-term wallet health and immediate transaction requirements.

Ensuring Noise Immunity of The Modbus Industrial Communication Protocol Based on Linear LDPC and BCH Codes

2026-06-17T09:14:30+00:00

This paper presents a modernization of the Modbus industrial communication protocol using Low Density Parity Check and Bose–Chaudhuri–Hocquenghem linear block error-correcting codes. While traditional Modbus relies on basic checksum algorithms, the proposed approach replaces these with advanced linear codes to enhance noise immunity. This paper describes these algorithms and provide a comparative analysis of their performance. Results demonstrate that this modernized framework allows for reliable Modbus communication.

A Method of Increasing the Integrity of Stored Information at the RAID 6 Level Using the Reed-Solomon Code and Combination of Syndrome and Probabilistic Decoding

2026-06-16T09:13:22+00:00

Currently, the volumes of information that need to be stored are growing. To store such data, specialized storage systems are used — they are capable of accommodating ever‑increasing amounts of data. During storage and transmission, errors may occur, which can lead to data corruption or loss. The technology of adding redundant disks to a RAID disk array is widely known — it is used to subsequently recover lost information. This article proposes a method that combines the Reed‑Solomon code (used at the RAID 6 level) with a decoding technique that is a combination of syndrome‑based and probabilistic decoding methods.