인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Information technology provides a service called cloud computing, which offers many beneficial functions. But there are a lot of problems and drawbacks with cloud computing, the most significant of which is the uncertainty and possible danger presented by the privacy and security restrictions. According to reports, there are reportedly fewer real-time cloud apps made exclusively for businesses than there are for consumers. This is allegedly due to concerns about security. When dealing with suppliers that have a questionable reputation, it is essential to ensure that the cloud management and service provider rigorously adheres to the highest standards of security and privacy. This study recommends enhancing the security protocols for sensitive data in cloud computing by using multi-layer encryption methods. The security and privacy of data kept on a cloud server may be greatly improved by using the layer-wise encryption technique. As a consequence, there is an improvement in security for both the cloud provider and the data owner. Users are essentially prevented from accessing the data by this encryption method unless the data owner specifically grants permission. The advanced encryption standard (AES) symmetric encryption method and the Rivest-Shamir Adleman (RSA) asymmetric encryption method are among the suggested approaches. Users who want to receive messages in the symmetric encryption process must exchange a special, unique key. On the other hand, asymmetric encryption encrypts and decrypts communications as they are being sent using both a private key and a public key. Then, a viability analysis is carried out for the two encryption algorithms previously mentioned, which are responsible for protecting the confidentiality and integrity of the data related to the other techniques.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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