International Journal of Sensor Networks and Data Communications

Brain-Computer Interfaces (BCIs) have experienced substantial advancements in recent years, largely propelled by the evolution of Artificial Intelligence (AI) and Machine Learning (ML) techniques. This mini review investigates the convergence of AI and ML with BCIs, examining both invasive and non-invasive BCI modalities. We delineate the contributions of AI and ML in processing and interpreting brain signals, survey diverse algorithms, outline significant discoveries, and suggest prospective research avenues to propel BCI technology forward.

Device-to-Device (D2D) communication is integral to modern wireless networks, facilitating direct communication between proximate devices without relying on base stations. Yet, securing and ensuring the trustworthiness of D2D communication presents substantial challenges. In this mini review, we delve into recent progress in securing D2D communications, focusing on approaches such as leveraging multiple trust levels, implementing adaptable data access controls, deploying resilient trust evaluation methods, and assessing performance through security proofs, analysis, and simulations.

As Controller-Pilot Data Link Communication (CPDLC) becomes the standard in aviation communication, replacing traditional voice-based Air Traffic Control (ATC) systems, the industry benefits from increased resilience and bandwidth efficiency. However, this transition also introduces heightened cybersecurity concerns, with potential cyber-attacks targeting CPDLC infrastructure posing significant risks. In response, AKAASH emerges as a lightweight solution providing robust authentication, key establishment, and handover mechanisms. This mini review examines the importance of CPDLC, the cybersecurity challenges it presents, and the role of AKAASH in enhancing CPDLC communication security.