Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world software.The existing analysis of software security vulnerabilities often focuses on specific features or modules.This partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the software.The key novelty lies in overcoming the constraints of partial approaches.The proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security guidelines.Security guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each product.These guidelines are not only practical but also applicable in real-world software,allowing for prioritized security responses.The proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related software.The analysis resulted in the identification of a total of 121 vulnerabilities.The successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

Examining the Burden Reduction Policy for Primary and Secondary School Teachers in China:A Framework Analysis Centered on the Rational Selection of Institutional Doctrine

The“burden reduction”policy aims to reduce the workload of primary and secondary school teachers to alleviate their burdens.While it has improved the quality of teachers,implementation challenges still exist.This study utilizes rational choice institutionalism and Ostrom’s institutional analysis and development framework to examine the policy.By considering the preferences of the Ministry of Education,local governments,schools,and teachers,it explores interactions and outcomes,identifies challenges,and provides policy suggestions.

System Reliability Analysis for Truss Structures Based on Automatic Updated Model

Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.

Enhanced Sentiment Analysis Algorithms for Multi-Weight Polarity Selection on Twitter Dataset

Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects.Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy.The sentiment analysis accuracy depends mainly on supervised and unsupervised mechanisms.Supervised mechanisms are based on machine learning algorithms that achieve moderate or high accuracy but the manual annotation of data is considered a time-consuming process.In unsupervised mechanisms,a lexicon is constructed for storing polarity terms.The accuracy of analyzing data is considered moderate or low if the lexicon contains small terms.In addition,most research methodologies analyze datasets using only 3-weight polarity that can mainly affect the performance of the analysis process.Applying both methods for obtaining high accuracy and efficiency with low user intervention during the analysis process is considered a challenging process.This paper provides a comprehensive evaluation of polarity weights and mechanisms for recent sentiment analysis research.A semi-supervised framework is applied for processing data using both lexicon and machine learning algorithms.An interactive sentiment analysis algorithm is proposed for distributing multi-weight polarities on Arabic lexicons that contain high morphological and linguistic terms.An enhanced scaling algorithm is embedded in the multi-weight algorithm to assign recommended weight polarities automatically.The experimental results are conducted on two datasets to measure the over-all accuracy of proposed algorithms that achieved high results when compared to machine learning algorithms.

Research evolution of metal organic frameworks: A scientometric approach with human-in-the-loop

Purpose:This paper reports on a scientometric analysis bolstered by human-in-the-loop,domain experts,to examine the field of metal-organic frameworks(MOFs)research.Scientometric analyses reveal the intellectual landscape of a field.The study engaged MOF scientists in the design and review of our research workflow.MOF materials are an essential component in next-generation renewable energy storage and biomedical technologies.The research approach demonstrates how engaging experts,via human-in-the-loop processes,can help develop a comprehensive view of a field’s research trends,influential works,and specialized topics.Design/methodology/approach:Ascientometric analysis was conducted,integrating natural language processing(NLP),topic modeling,and network analysis methods.The analytical approach was enhanced through a human-in-the-loop iterative process involving MOF research scientists at selected intervals.MOF researcher feedback was incorporated into our method.The data sample included 65,209 MOF research articles.Python3 and software tool VOSviewer were used to perform the analysis.Findings:The findings demonstrate the value of including domain experts in research workflows,refinement,and interpretation of results.At each stage of the analysis,the MOF researchers contributed to interpreting the results and method refinements targeting our focus Research evolution of metal organic frameworks:A scientometric approach with human-in-the-loop on MOF research.This study identified influential works and their themes.Our findings also underscore four main MOF research directions and applications.Research limitations:This study is limited by the sample(articles identified and referenced by the Cambridge Structural Database)that informed our analysis.Practical implications:Our findings contribute to addressing the current gap in fully mapping out the comprehensive landscape of MOF research.Additionally,the results will help domain scientists target future research directions.Originality/value:To the best of our knowledge,the number of publications collected for analysis exceeds those of previous studies.This enabled us to explore a more extensive body of MOF research compared to previous studies.Another contribution of our work is the iterative engagement of domain scientists,who brought in-depth,expert interpretation to the data analysis,helping hone the study.

An Analysis Method of Business Application Framework

We discuss the evolution of object oriented software development process based on software pattern. For developing mature software framework and component, we advocate to elicit and incorporate software patterns for ensuing quality and reusability of software frameworks. On the analysis base of requirement specification for business application domain, we present analysis method and basic role model of software framework. We also elicit analysis pattern of framework architecture, and design basic role classes and their structure.

Development of the Data Processing and Analysis System Framework for ICF Experiments

An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.

Using an Interprofessional Lens to Analyze Serious Adverse Events in a Teaching Hospital: An Analysis with the TeamSTEPPS® Framework

This paper explores the contribution of teamwork skills in serious adverse events, using the TeamSTEPPS® framework. Adverse events are the undesirable events that are not due to the natural course of a disease;they are considered serious when they prolong a hospital stay, lead to a physical disability or to death. Failures in teamwork, particularly with interprofessional teams, can lead to potential risks to patient safety. Using a dataset of de-identified reports of serious adverse events in 2016 in a tertiary teaching hospital, we explored the contribution of teamwork skills according to the TeamSTEPPS® framework to these adverse events. We found that 61% of the 41 analyzed events involved failures in teamwork skills, with 80% of these involving communication, 52% in situation monitoring and team structure, 44% in mutual support and 40% in leadership. Sixty-four percent of the events involved more than one teamwork component. Our findings emphasize the need to improve teamwork training in healthcare, focusing not only on communication, but also on other teamwork skills as they often contribute together in adverse events. Future analyses of serious adverse events should include a focus on teamwork competencies, to guide the development of future quality and safety training programs.

Open-Access Framework for Efficient Object-Oriented Development of Video Analysis Software

The increasing use of digital video everyday in a multitude of electronic devices, including mobile phones, tablets and laptops, poses the need for quick development of cross-platform video software. However current approaches to this direction usually require a long learning curve, and their development lacks standardization. This results in software components that are difficult to reuse, and hard to maintain or extend. In order to overcome such issues, we propose a novel object-oriented framework for efficient development of software systems for video analysis. It consists of a set of four abstract components, suitable for the implementation of independent plug-in modules for video acquisition, preprocessing, analysis and output handling. The extensibility of each module can be facilitated by sub-modules specifying additional functionalities. This architecture enables quick responses to changes and re-configurability;thus conforming to the requirements of agile software development practices. Considering the need for platform independency, the proposed Java Video Analysis (JVA) framework is implemented in Java. It is publicly available through the web as open-access software, supported by a growing collection of implemented modules. Its efficiency is empirically validated for the development of a representative video analysis system.

Selecting the Six Sigma Project: A Multi Data Envelopment Analysis Unified Scoring Framework

The importance of the project selection phase in any six sigma initiative cannot be emphasized enough. The successfulness of the six sigma initiative is affected by successful project selection. Recently, Data Envelopment Analysis (DEA) has been proposed as a six sigma project selection tool. However, there exist a number of different DEA formulations which may affect the selection process and the wining project being selected. This work initially applies nine different DEA formulations to several case studies and concludes that different DEA formulations select different wining projects. Also in this work, a Multi-DEA Unified Scoring Framework is proposed to overcome this problem. This framework is applied to several case studies and proved to successfully select the six sigma project with the best performance. The framework is also successful in filtering out some of the projects that have “selective” excellent performance, i.e. projects with excellent performance in some of the DEA formulations and worse performance in others. It is also successful in selecting stable projects;these are projects that perform well in the majority of the DEA formulations, even if it has not been selected as a wining project by any of the DEA formulations.

Financial Analysis of MI’s Company Based on Harvard Analysis Framework

This paper takes the financial statements of MI from 2017to 2019,and uses Harvard analysis framework to analyse the financial situation of MI.The analysis content mainly includes enterprise macro environment,industry competitive analysis and financial ratio analysis.This paper tried to understand the current situation and development prospect of MI.Based on the analysis of MI’s financial situation under the framework of Harvard,we summarized the existing problems and put forward suggestions.

Analysis on Discourse Construction of HK Riots between HK Protesters and China's Mainland Media Based on Fairclough’s Three-dimensional Framework of Critical Discourse Analysis

The Critical Discourse Analysis(CDA)is an interdisciplinary tool in various conditions,which aims to provide a better understanding of sociocultural aspects of texts and accounts of the production of internal structure,and overall organization of texts as well as to provide a critical dimension in its theoretical and descriptive accounts of texts.Since June last year,HK protests or HK violence have been frequently reported by worldwide media.In this paper,the author aims to find out how the HK protesters and the Mainland media describe the same event based on the three-dimensional framework of CDA.At last,the author concludes that the mainland media generally describe the event as violence and riot while the HK protesters define themselves as warriors striving for more freedom,justice and democracy.Besides,on this event,the Mainland media mainly accuses some western countries of interference into HK affairs,which is undoubtedly of China’s internal affairs,and the media give full support to the HK police in safeguarding the peace and stability of Hong Kong.But from the perspective of HK protesters,they firmly believe that they are using their actions to protect all the people of HK,and they are defending their values such as freedom,democracy and justice.These are two totally different systems of language,and the author also gives its potential reasons in the paper so as to offer some viewpoints in this aspect in combination with the CDA theory.

Analysis of a Conceptual Model and Assessment of the e-Procurement System in Bangladesh

The public procurement system in Bangladesh has been running by traditional manual process under the flagship of Public Procurement Act (PPA 2006) and Public Procurement Rules (PPR 2008). Public procurement agencies have been facing challenges in this manual tendering system. To overcome this problem and to bring reality to the “Digital Bangladesh” slogan, the Government of Bangladesh introduced the e-Procurement system under the e-GP (Electronic Government Procurement) guideline 2011. After the inception of e-procurement, there is no e-procurement assessment model to improve the e-GP system. The purpose of this research is to develop a conceptual framework and to design an e-procurement assessment model. With this view, we have considered one of the biggest entity Roads and Highways Department (RHD) of the Government of Bangladesh, for field study. Mixed methods along with FGD (Focus Group Discussion), KII (Key Informant Interview), and survey questionnaires are used to collect data from RHD, and then Statistical Package for Social Science (SPSS) software is used for regression analysis and hypothesis testing to develop the e-Procurement assessment model. The novel contribution of the study lies in the test of the hypothesis that focuses on developing the conceptual model of the e-procurement assessment system in Bangladesh. Findings of the study are essential for all Procurement Entity (PE) and suppliers i.e. contractors of RHD who are engaged in the construction of the infrastructure project development project.

A Network Analysis of Skill Game Dynamics

Casino games can be classified in two main categories, i.e. skill games and gambling. Notably, the former refers to games whose outcome is affected by the strategies of players, the latter to those games whose outcome is completely random. For instance, lotteries are easily recognized as pure gambling, while some variants of Poker (e.g. Texas Hold’em) are usually considered as skill games. In both cases, the theory of probability constitutes the mathematical framework for studying their dynamics, despite their classification. Here, it is worth to consider that when games entail the competition between many players, the structure of interactions can acquire a relevant role. For instance, some games as Bingo are not characterized by this kind of interactions, while other games as Poker, show a network structure, i.e. players interact each other and have the opportunity to share or exchange information. In this paper, we analyze the dynamics of a population composed of two species, i.e. strong and weak agents. The former represents expert players, while the latter beginners, i.e. non-expert ones. Here, pair-wise interactions are based on a very simple game, whose outcome is affected by the nature of the involved agents. In doing so, expert agents have a higher probability to succeed when playing with weak agents, while the success probability is equal when two agents of the same kind face each other. Numerical simulations are performed considering a population arranged in different topologies like regular graphs and in scale-free networks. This choice allows to model dynamics that we might observe on online game platforms. Further aspects as the adaptability of agents are taken into account, e.g. the possibility to improve (i.e. to becomean expert). Results show that complex topologies represent a strong opportunity for experts and a risk for both kinds of agents.

Risk Analysis of Industrial Internet Identity System

The risks of the current identity system represented by Domain Name System(DNS)and Object Identifier(OID)are studied.According to the characteristics of the industrial Internet Identity(Ⅲ)system,four open ecosystem planes are divided,and a corresponding risk analysis view is established to analyze risks for various planes.This paper uses Isaiah Berlin’s definition of liberty to more generally express the concept of security as positive rights and negative rights.In the risk analysis view,the target system is modeled from four dimensions:stakeholders,framework,architecture,and capability delivery.At last,three defensive lines are proposed to establish the identity credit system.

Needs Analysis in the Exploitation of School-based HVE Teaching Materials

Exploitation of School-based HVE(Higher Vocational English) teaching materials must take needs analysis theory as the breakthrough point. This thesis attempts to make up a new exploiting rationale of School-based HVE teaching materials and a needs analysis framework is figured out to be applied to the exploitation for Non-English Majors. According to the theoretical framework, comprehensive needs of School-based HVE teaching materials are mainly described from three aspects: HV(Higher Vocational) students' occupational demands, HV school's exploitation demands, and HVE teaching-and-learning demands.

THE STRATEGIES OF INTEGRATING SPATI AL DATA ANALYSIS AND GIS

The gap between SDA(Spatial Data Analysis)and GIS(Geographical Information Systems )existed for a long time.Presently this problem still remains in spite of a lot of theore tical and practical studies which tr y to find the solu-tion for it.The research background and current situation about how to in tegrate SDA and GIS are introduced at first.The main idea of this article is to make su re what is the best scheme to bridge th e gap between SDA and GIS and how to design it.There are a lot of factors to influ ence the standards to assess such a sc heme,for instance,the attitude of users and GIS developers,the framework and related functions of current available GI S software in the market and so on.But the two most important ones of them are effic iency and flexibility of the scheme i tself.Efficiency can be measured by the conve-nient extent and temporal length when it is used for carrying out SDA.Flex ibility means users can define their own SDA methods.The best integration schem e should satisfy the two standards at the same time.A group of functions,which can be combined to implement any SDA meth od,are defined in order to design such an integration scheme.The functio ns are divided into five classes according to their properties.

An Integrated Multilayered Framework for IoT Security Intrusion Decisions

Security breaches can seriously harm the Internet of Things(IoT)and Industrial IoT(IIoT)environments.The damage can exceedfinancial and material losses to threaten human lives.Overcoming these security risks is challenging given IoT ubiquity,complexity,and restricted resources.Security intrusion man-agement is a cornerstone in fortifying the defensive security process.This paper presents an integrated multilayered framework facilitating the orchestration of the security intrusion management process and developing security decision support systems.The proposed framework incorporates four layers with four dedicated processing phases.This paper focuses mainly on the analytical layer.We present the architecture and models for predictive intrusion analytics for reactive and proactive defense strategies.We differentiate between the device and network levels to master the complexity of IoT infrastructure.Benefiting from the singu-larity of IIoT devices traffic,we approach the reactive security intrusion predic-tion through outlier detection models mean.We thoroughly experiment with ten outlier detection models on the IIoT wustl realistic dataset.The obtained results show the adequacy of the approach with an area under the curve(AUC)results surpassing 98%for several models with a good level of precision and time effi-ciency.Furthermore,we investigate the use of survival analysis semi-parametric predictive models to forecast the security intrusion before its occurrence for the proactive security strategy.The experiments show encouraging results with a con-cordance index(c-Index)reaching 89%and an integrated brier score(IBS)of 0.02.By integrating outlier intrusion detection and survival forecasting,the fra-mework provides a valuable means to monitor the security intrusions in IoT.

A Novel Approach to Design Distribution Preserving Framework for Big Data

In several fields like financial dealing,industry,business,medicine,et cetera,Big Data(BD)has been utilized extensively,which is nothing but a collection of a huge amount of data.However,it is highly complicated along with time-consuming to process a massive amount of data.Thus,to design the Distribution Preserving Framework for BD,a novel methodology has been proposed utilizing Manhattan Distance(MD)-centered Partition Around Medoid(MD–PAM)along with Conjugate Gradient Artificial Neural Network(CG-ANN),which undergoes various steps to reduce the complications of BD.Firstly,the data are processed in the pre-processing phase by mitigating the data repetition utilizing the map-reduce function;subsequently,the missing data are handled by substituting or by ignoring the missed values.After that,the data are transmuted into a normalized form.Next,to enhance the classification performance,the data’s dimensionalities are minimized by employing Gaussian Kernel(GK)-Fisher Discriminant Analysis(GK-FDA).Afterwards,the processed data is submitted to the partitioning phase after transmuting it into a structured format.In the partition phase,by utilizing the MD-PAM,the data are partitioned along with grouped into a cluster.Lastly,by employing CG-ANN,the data are classified in the classification phase so that the needed data can be effortlessly retrieved by the user.To analogize the outcomes of the CG-ANN with the prevailing methodologies,the NSL-KDD openly accessible datasets are utilized.The experiential outcomes displayed that an efficient result along with a reduced computation cost was shown by the proposed CG-ANN.The proposed work outperforms well in terms of accuracy,sensitivity and specificity than the existing systems.