To reduce the false negative rate in power data anomaly detection, enhance the overall detection accuracy and reliability, and create a more stable data detection environment, this paper designs a power big data anomaly detection method based on improved support vector machine technology. The abnormal features are extracted in advance, combined with the changes of power data, the multi-target anomaly detection nodes are laid, and on this basis, the improved support vector machine anomaly detection model is constructed. The anomaly detection is realized by combining the normalization processing of the equivalent vector. The final test results show that compared with the traditional clustering algorithm big data anomaly detection test group and the traditional multi-domain feature extraction big data anomaly detection test group, the final false negative rate of the improved support vector machine big data exception detection test group designed in this paper is only 2.04, which shows that the effect of the anomaly detection method is better. It is more accurate and reliable for testing in a complex power environment and has practical application value.
This study explores international Chinese students’ experiences of Korean as a Medium of Instruction (KMI) course in a Korean university. This study focuses on the KMI course that allows students to simultaneously learn Korean academic language and content knowledge. Thus, this study examines the effectiveness of the KMI course for Chinese international students and proposes effective teaching methods that will enable international students to perform academic studies in the future successfully. This study is conducted at the graduate school of W University in Korea. The KMI method is applied to two graduate courses with 15 Chinese international students during the 2021 Fall semester. By using mixed-method, the survey is conducted to determine the perception and satisfaction of the international Chinese students’ experiences in the KMI course related to content knowledge, cognitive ability, and multicultural understanding. Among survey participants, interview applicants are selected and conducted in-depth interviews. The results as shown below. First, Chinese international students develop various content knowledge through the KMI course. Second, Chinese international students can improve their Korean language ability through the KMI course. Third, bilingual KMI courses are more effective in learning Korean vocabulary and grammar than monolingual KMI courses. Third, Chinese international students understand Korean culture and university life through the KMI course. Fourth, Chinese international students are generally satisfied with the KMI course. However, Chinese international students face a challenge that quickly improves their Korean academic ability through the KMI. The conclusions as shown below. First, the KMI course positively affects the content knowledge of Chinese international students. Second, the KMI course has a positive effect on improving the Korean ability of Chinese international students. Third, the KMI course positively affects international students’ understanding of multiculturalism. However, the KMI course may not dramatically impact international students’ academic Korean language skills in a short period.
With the growing number of online accounts a user possesses, managing passwords has been unprecedentedly challenging. Users are prone to sacrifice security for usability, leaving their accounts vulnerable to various attacks. While replacing text-based password with a new universally applicable authentication scheme still seems unlikely in the foreseeable future, password managers have emerged to help users managing their passwords. However, state-of-the-art cloud based password managers are vulnerable to data breach and a master password becomes a single point of failure. To address these security vulnerabilities, we propose BluePass, a password manager that stores the password vault (i.e., the set of all the encrypted site passwords of a user) locally in a mobile device and a decryption key to the vault in the user computer. BluePass partially inherits the security characteristics of 2-Factor authentication by requiring both a mobile device and a master password to retrieve and decrypt the site passwords. BluePass leverages short-range nature of Bluetooth to automatically retrieve site passwords and fill the login fields, providing a hand-free user experience. Thus, BluePass enhances both security and usability. We implement a BluePass prototype in Android and Google Chrome platforms and evaluate its efficacy in terms of security, usability, and overhead.
With the popularity and development of the network, the support of the high-performance computer technology becomes increasingly important as the huge information storage and the convenience of Information retrieval function of the internet that attracts more and more people join the netizens team. Therefore, I proposed an Information Processing Platform based on the high performance data mining in order to improve the Internet mass information intelligence parallel processing functions and the integrated development of the systems information storage, management, integration, intelligence processing, data mining and utilization. The propose of this system is to provide certain references and guidance for the technology implementation and realization of the high performance and high efficiency network massive Information Processing Platform as on the one hand, I have analyzed the key technology of the implementation of the platform, on the other hand briefly introduced the implementation of the RDIDC.
Protocol and typestate analyses often report some sequences of statements ending at a program point P that needs to be scrutinized, since P may be erroneous or imprecisely analyzed. slicing focuses only on the behavior at P by computing a slice of the program affecting the values at P. In our companion paper Program Tailoring: Slicing by Sequential Criteria, we propose to focus on the subset of that behavior at P affected by one or several statement sequences, called a sequential criterion (SC). By leveraging the ordering information in a SC, e.g., the temporal order in a few valid/invalid API method invocation sequences, we introduce a new technique, program tailoring, to compute a tailored program that comprises the statements in all possible execution paths passing through at least one sequence in SC in the given order.
This artifact is based on TAILOR, a prototyping implementation of program tailoring, to evaluate the usefulness of TAILOR in practice. The provided package is designed to support repeatability of all the experiments of our companion paper. Specifically, it allows users to reproduce the results for all the three research questions addressed in the evaluation section of our companion paper. In addition, an extensive set of extra results, which are not described in the companion paper, are also included, in order to help users better understand this work.
While numerous flaws have been recognized in using passwords as a method of authentication, passwords still remain the de-facto authentication standard in use today. Though password managers can ameliorate password fatigue, the vast majority of password managers require the user to choose and maintain a strong master password while offering little to no recourse in the event that the master password is compromised. The wide-application of cloud-based password managers congregate passwords in an encrypted database, which becomes an attractive target for attackers and also represents a single point of failure. In this paper, we propose Amnesia, a bilateral generative password manager that requires both the knowledge of the master password and the possession of the user's smartphone to generate website passwords for the user. Our generative password manager is not vulnerable to the password database leakage, since it generates the requested password on demand using both the master password and the secret information on the smartphone. An attacker wishing to steal the user's website passwords has to compromise both the user's smartphone and the master password. Amnesia also has strong recovery capability when either the master password is compromised or the smartphone is lost/stolen. By using an Amnesia server, a user can have the access to the password manager on multiple computers without installing any software on those computers. We implemented an Amnesia system prototype using Android and Cherrypy web framework and evaluated it in terms of security, usability, and overhead. A user study of 31 testers shows that Amnesia increases password security while maintaining reasonable user convenience.
AADL is used to design embedded software in ever-increasing mission-critical applications.With the complexity of embedded software increasing, integration testing and system testing based on codes are becoming more difficult.This paper describes a systematic test cases generation approach using AADL for embedded software.The approach uses hierarchical testing model to generate test cases which is fully automatic model-driven.This paper designs one set of mapping rules from AADL to hierarchical testing model for constructing it automatically.The case study shows experimental process of the test model construction and test case generation.Automatic generation of systematic test cases using AADL for Embedded Software is feasible.
The postMessage feature in HTML5 allows web components of different origins to communicate with each other. However, the message receivers do not differentiate the origins of a message, making information leakage possible. Being aware of this vulnerability, We examine its implication under the context of Single Sign On (SSO) mechanism. Nowadays, many websites integrate SSO to facilitate easier user authentication by relying on an identifier provider such as Facebook to provide the identity of a user. However, many websites with SSO log-on rely on postMessage to transmit the Access Token. We identify the problem and demonstrate that any postMessage Receiver on this web page can eavesdrop on the token and hijack the user account. As a result, significant information leakage and account takeover are likely to happen.
It makes possible that it can do basic uncertain inference and directly read/write some table contents of MySQL database with improved ESTA 4.5 (Expert System Shell for Text Animation) based on Visual Prolog 6.3 and Windows, namely adding some uncertain inference functions and some interaction functions with MySQL to the ESTA. It put forward also an uncertain inference method in the ESTA 4.5 based on Visual Prolog 5.2 and Web. It had designed and implemented a condition evaluation expert system of substation DC (Direct Current) system based on the improved ESTA and the enterprise standards (Q/GDW 607-2011) of State Grid. The test shows that the uncertain inference of improved ESTA has feasibility, the interaction with MySQL simplifies some rules of writing and enhances flexibility of it, and the expert system is effective and practical.
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