Quantum cryptography is the most convenient resolution for information security systems that presents an ultimate approach for key distribution. Today, the most viable key distribution resolutions for information security systems are those based on quantum cryptography. It is based on the quantum rules of physics rather than the assumed computational complexity of mathematical problems. But, the initial BB84 quantum key distribution protocol which is the raw key exchange of S13 quantum key distribution protocol has weakness of disclosure of large portion of secrete key or eavesdropping. Also, it cannot make use of most of the generated random bit. This paper enhanced S13 quantum key distribution protocol by employing polarization, secrete key disclosure and non-repudiation. The use of biometric or MAC address ensures non-repudiation. The row key exchange part of the S13 quantum key distribution which is the same as BB84 is enhanced by employing polarization techniques to make use of most of the generated random bit. Then, the tentative final key generated at the end of error estimation phase should be divided into blocks, padding, inverting the last bit of each block and XORing the block to generate a totally different key from the tentative one. Also, the random bits will be from biometric or serve MAC address respectively. The enhanced S13 quantum key is evaluated using cryptanalysis which shows that the enhanced protocol ensures disclosures of large portion of secrete key to prevent eavesdropping, utilization of most of the chosen binary strings to generate strong key and safeguarding against impersonation attack.

Modeling the uncertain aspect of the world in ontologies is attracting a lot of interests to ontologies builders especially in the World Wide Web community. This paper defines a way of handling uncertainty in description logic ontologies without remodeling existing ontologies or altering the syntax of existing ontologies modeling languages. We show that the source of vagueness in an ontology is from vague attributes and vague roles. Therefore, to have a clear separation between crisp concepts and vague concepts, the set of roles R is split into two distinct sets〖 R〗_c and R_v representing the set of crisp roles and the set of vague roles respectively. Similarly, the set of attributes A was split into two distinct sets A_c and A_v representing the set of crisp attributes and the set of vague attributes respectively. Concepts are therefore clearly classified as crisp concepts or vague concepts depending on whether vague attributes or vague roles are used in its conceptualization or not. The concept of rough set introduced by Pawlak is used to measure the degree of satisfiability of vague concepts as well as vague roles. In this approach, the cost of reengineering existing ontologies in order to cope with reasoning over the uncertain aspects of the world is minimal.