Ontology-based Secure Retrieval of Semantically Significant Visual Contents

Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presented various low-level features-based techniques for classifying images into different categories. However, efficient and effective classification and retrieval is still a challenging problem due to complex nature of visual contents. In addition, the traditional information retrieval techniques are vulnerable to security risks, making it easy for attackers to retrieve personal visual contents such as patient’s records 1) Corresponding author 논문투고일자 : 2015. 06. 09 심사일자 : 2015. 06. 09 게재확정일자 : 2015. 06. 24 【논 문】 한국차세대컴퓨팅학회 논문지 2015년 6월 88 and law enforcement agencies’ databases. Therefore, we propose a novel ontology-based framework using image steganography for secure image classification and information retrieval. The proposed framework uses domain-specific ontology for mapping the low-level image features to high-level concepts of ontologies which consequently results in efficient classification. Furthermore, the proposed method utilizes image steganography for hiding the image’s semantics as a secret message inside them, making the information retrieval process secure from third parties. The proposed framework minimizes the computational complexity of traditional techniques, increasing its suitability for secure and real-time visual contents retrieval from personalized image databases. Experimental results confirm the efficiency, effectiveness, and security of the proposed framework as compared with other state-of-the-art systems. 키워드: 정보검색, 온톨로지, 이미지 스테가노그라피, 정보 보안 Keyword: Information retrieval, ontology, image steganography, information security