In recent years, a growing number of breaches targeting cryptocurrency exchanges have damaged the credibility of the entire cryptocurrency ecosystem. To prevent further harm, it’s crucial to detect the anomalous beha...
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Honeywords is a simple and efficient method that can help the authentication server to detect password leaks. The indistinguishability between generated honeywords and real passwords is the key to the honeywords gener...
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Security strings are often needed in identity authentication mechanism. Security strings recovery is a reverse process, which does much calculations on a large amount of possible strings to find the right one, so that...
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In the network with flow control, the output usually feedbacks some information to the input, controlling the data transmission and preventing buffer overflow. Flow control transforms the traditional forward networks ...
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Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration *** rule mining,a data mining technique,has been studied and explor...
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Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration *** rule mining,a data mining technique,has been studied and explored for a long ***,few studies have focused on knowledge discovery in the penetration testing *** experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent *** address this problem,a Bayesian inference based penetration semantic knowledge mining algorithm is ***,a directed bipartite graph model,a kind of Bayesian network,is constructed to formalize penetration testing ***,we adopt the maximum likelihood estimate method to optimize the model parameters and decompose a large Bayesian network into smaller networks based on conditional independence of variables for improved solution ***,irrelevant variable elimination is adopted to extract penetration semantic knowledge from the conditional probability distribution of the *** experimental results show that the proposed method can discover penetration semantic knowledge from raw penetration testing data effectively and efficiently.
Recently, the need for real-time deep learning applications, such as face recognition system, implement on the embedded devices is increasing. At the system level, caching system is one of the most effective ways to r...
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In 2010, Rosario Gennaro et al. revisited the old and elegant Okamoto-Tanaka scheme and presented a variant of it called mOT. How-ever the compromise of ephemeral private key will lead to the leakage of the session ke...
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When dealing with the large-scale program,many automatic vulnerability mining techniques encounter such problems as path explosion,state explosion,and low *** of large-scale programs based on safety-sensitive function...
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When dealing with the large-scale program,many automatic vulnerability mining techniques encounter such problems as path explosion,state explosion,and low *** of large-scale programs based on safety-sensitive functions helps solve the above *** manual identification of security-sensitive functions is a tedious task,especially for the large-scale *** study proposes a method to mine security-sensitive functions the arguments of which need to be checked before they are *** argument-checking identification algorithms are proposed based on the analysis of two implementations of argument *** on these algorithms,security-sensitive functions are detected based on the ratio of invocation instances the arguments of which have been protected to the total number of *** results of experiments on three well-known open-source projects show that the proposed method can outperform competing methods in the literature.
Entity and relation extraction is a basic task of information extraction in natural language processing. At present, Entity and relation extraction based on artificial intelligence has been widely studied, but most me...
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Machine Learning algorithms have been wildly applied in the intrusion detection system(IDS). However, in the IoT environment where the resources are limited and the flow data is of huge amount, we need more efficient ...
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