The performance of Artificial Intelligence (AI) systems reaches or even exceeds that of humans in an increasing number of complicated tasks. Highly effective non-linear AI models are generally employed in a black-box form nested in their complex structures, which means that no information as to what precisely helps them reach appropriate predictions is provided. The lack of transparency and interpretability in existing Artificial Intelligence techniques would reduce human users’ trust in the models used for cyber defence, especially in current scenarios where cyber resilience is becoming increasingly diverse and challenging. Explainable AI (XAI) should be incorporated into developing cybersecurity models to deliver explainable models with high accuracy that human users can understand, trust, and manage. This paper explores the following concepts related to XAI. A summary of current literature on XAI is discussed. Recent taxonomies that help explain different machine learning algorithms are discussed. These include deep learning techniques developed and studied extensively in other IoT taxonomies. The outputs of AI models are crucial for cybersecurity, as experts require more than simple binary outputs for examination to enable the cyber resilience of IoT systems. Examining the available XAI applications and safety-related threat models to explain resilience towards IoT systems also summarises the difficulties and gaps in XAI concerning cybersecurity. Finally, various technical issues and trends are explained, and future studies on technology, applications, security, and privacy are presented, emphasizing the ideas of explainable AI models.

This article describes a project in which an electrical circuit is designed by which an user can turn on/off any electrical appliances i.e. fans, lights and can lock/unlock windows, doors etc. of his/her house or office through sending SMS using a custom built android application to a specific phone number connected to the microcontroller. In this system an android application is used to send instruction through SMS. At the receiving end, a GSM module receives the SMS and sends the particular hexadecimal codes to a microcontroller. Then the microcontroller reads the code and sends the signals to relays for performing actions according to the specified logic. For designing the system Proteus, a virtual system modeling and circuit simulation application, was used as simulation software. The code for microcontroller was written in mikroC PRO and burnt with PICkit 2 softwares. This system ensures smart safeguarding as well as efficient use of energy for its user's office and living place.