Convenience is very important element in the home network service. But it is more important that protect home network service users from attackers than the former. And, home network has two features; the one is various communication protocols of home network service constituent devices, and the other is home network service user in the more different age groups than general Internet service users. We solve these problems with home server and biometric recognition. That is, home server connects the home appliances to communicate with each other. And biometric recognition gives safety and user convenience. In this paper, we describe a home network service model and propose a user authentication mechanism using biometric recognition

To minimize cybersecurity risks in weapon systems, the implementation of the Ko-rean Risk Management Framework (K-RMF) has become essential. However, a significant 'strategic gap' exists between high-level RMF controls and technical MITRE ATT&CK techniques, rendering manual mapping labor-intensive. This study proposes an automated mitigation-driven pipeline that integrates Sentence-BERT (SBERT) with the struc-tural defense relationships of the ATT&CK knowledge graph. To address the data cover-age limitations of the CTID silver standard, we introduce Recall@restricted as a calibrated performance metric. Experimental evaluation demonstrated that the proposed ensemble framework achieves a Recall@restricted of 0.74, significantly outperforming baseline SBERT-only models. These findings suggest that deterministic mitigation relationships effectively complement semantic representations, providing a robust framework for aligning RMF controls with adversarial behaviors.

Currently, home network devices use various communication methods. And there exist many communication standards between home appliances. It leads some problem in home network. This paper proposed a home network model which is star-topology and centers home server on the home network. And we also describe user authentication mechanism using user's biometric information on our home network. In this paper, home server is very important. So it must be secure from attack, and we assume that it is secure

To minimize cybersecurity risks in weapon systems, the implementation of the Korean Risk Management Framework (K-RMF) has become imperative. However, a significant “strategic gap” exists between high-level RMF controls and technical MITRE ATT&CK techniques, rendering manual mapping labor-intensive. This study proposes an automated mitigation-driven pipeline that integrates Sentence-BERT (SBERT) with the structural defense relationships of the ATT&CK knowledge graph. To address the data coverage limitations of the Center for Threat-Informed Defense (CTID) silver standard, we introduce Recall@restricted as a calibrated performance metric. Experimental evaluations demonstrate that the proposed ensemble framework achieves a Recall@restricted of 0.74, significantly outperforming baseline SBERT-only models. These findings suggest that deterministic mitigation relationships effectively complement semantic representations, providing a robust framework for aligning RMF controls with adversarial behaviors.