R. Azmi; B. Pishgoo
Abstract
Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the second one which is called ...
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Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the second one which is called danger theory focuses on both adaptive and innate reactions to build a more biologically-realistic model of Human Immune System. Two algorithms named TLR and DCA are proposed in danger theory field that both of them are trying to identify the antigens based on a simple identifier. Both of them suffer from low accuracy and detection rate due to the fact that they are not taking the structure of antigens into account. In this paper, we propose an algorithm called STLR (structural TLR), which is an extended form of TLR algorithm. STLR tries to model the interaction of adaptive and innate biological immune systems and at the same time considers the structure of the antigens. The experimental results show that using the structural aspects of an antigen, STLR can lead to a great increase in the detection rate and accuracy.
H. Afzali; H. Nemati; R. Azmi
Abstract
Nowadays, users of information systems have inclination to use a central server to decrease data transferring and maintenance costs. Since such a system is not so trustworthy, users' data usually upkeeps encrypted. However, encryption is not a nostrum for security problems and cannot guarantee the data ...
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Nowadays, users of information systems have inclination to use a central server to decrease data transferring and maintenance costs. Since such a system is not so trustworthy, users' data usually upkeeps encrypted. However, encryption is not a nostrum for security problems and cannot guarantee the data security. In other words, there are some techniques that can endanger security of encrypted data. Majority of existing methods for encrypted data management have some critical defects such as cryptanalysis attacks, encryption/decryption overhead, and inefficient data storing and retrieval. In this paper, at first we propose a prototype model of private key based search on encrypted data. Then we try to improve it significantly to meet security requirements. Our main goal is to offer a practical method of querying arbitrary words on encrypted data using a minimal trust model. Moreover, we present a model for balancing between performance and security based on user's requirements. In comparison with other methods, query response time is improved and the probability of statistical deductions is reduced.