Integrating a flexible modeling framework (FMF) with the network security assessment instrument to reduce software security risk

Abstract. Despite showing great success of applications in many commercial fields, machine learning and data science models generally show limited success in many scientific fields, including hydrology (Karpatne et al., 2017). The approach is often criticized for its lack of interpretability and physical consistency. This has led to the emergence of new modelling paradigms, such as theory-guided data science (TGDS) and physics-informed machine learning. The motivation behind such approaches is to improve the physical meaningfulness of machine learning models by blending existing scientific knowledge with learning algorithms. Following the same principles in our prior work (Chadalawada et al., 2020), a new model induction framework was founded on genetic programming (GP), namely the Machine Learning Rainfall–Runoff Model Induction (ML-RR-MI) toolkit. ML-RR-MI is capable of developing fully fledged lumped conceptual rainfall–runoff models for a watershed of interest using the building blocks of two flexible rainfall–runoff modelling frameworks. In this study, we extend ML-RR-MI towards inducing semi-distributed rainfall–runoff models. The meaningfulness and reliability of hydrological inferences gained from lumped models may tend to deteriorate within large catchments where the spatial heterogeneity of forcing variables and watershed properties is significant. This was the motivation behind developing our machine learning approach for distributed rainfall–runoff modelling titled Machine Induction Knowledge Augmented – System Hydrologique Asiatique (MIKA-SHA). MIKA-SHA captures spatial variabilities and automatically induces rainfall–runoff models for the catchment of interest without any explicit user selections. Currently, MIKA-SHA learns models utilizing the model building components of two flexible modelling frameworks. However, the proposed framework can be coupled with any internally coherent collection of building blocks. MIKA-SHA's model induction capabilities have been tested on the Rappahannock River basin near Fredericksburg, Virginia, USA. MIKA-SHA builds and tests many model configurations using the model building components of the two flexible modelling frameworks and quantitatively identifies the optimal model for the watershed of concern. In this study, MIKA-SHA is utilized to identify two optimal models (one from each flexible modelling framework) to capture the runoff dynamics of the Rappahannock River basin. Both optimal models achieve high-efficiency values in hydrograph predictions (both at catchment and subcatchment outlets) and good visual matches with the observed runoff response of the catchment. Furthermore, the resulting model architectures are compatible with previously reported research findings and fieldwork insights of the watershed and are readily interpretable by hydrologists. MIKA-SHA-induced semi-distributed model performances were compared against existing lumped model performances for the same basin. MIKA-SHA-induced optimal models outperform the lumped models used in this study in terms of efficiency values while benefitting hydrologists with more meaningful hydrological inferences about the runoff dynamics of the Rappahannock River basin.

The Internet's sharing and openness have made information interaction more vulnerable to security risks. As a result, a comprehensive evaluation of the security of computer network systems has become a more effective means of preventing various network security problems. In recent years, there have been many network security evaluation methods proposed to address this issue, but not all of them are effective. Therefore, this paper analyzes existing network security evaluation methods and proposes a new model based on BP neural network and AHP jointly. The proposed model combines the advantages of BP neural network and hierarchical analysis (AHP) to provide a comprehensive and accurate evaluation of network security. The BP neural network is used to evaluate the risk level of each security factor, while AHP is used to calculate the weights of each security factor. The weights reflect the relative importance of each factor in determining the overall security level of the network. To verify the applicability of the proposed model, empirical research is conducted. The results demonstrate that the model can effectively evaluate network security comprehensively. The model's accuracy and effectiveness make it a promising approach to evaluate the security of computer network systems. Additionally, it can help in developing strategies to enhance network security by identifying potential vulnerabilities and assessing the effectiveness of security measures implemented. In conclusion, the model provides a useful tool for organizations to manage network security effectively.

Computer and network security are central issues confronting organizations and individuals. This paper explores the use of biology as a reference discipline that can provide meaningful insight and innovation in the area of network security. Specifically, we propose a framework for thinking about network security by examining the similarities between the defense mechanisms of a cell, and the security processes and methodologies of networked computer systems that defend an organization's information resources. Researchers and commercial developers can use this framework to help spark ideas that lead to further research and development in network security. The framework also provides a platform for educators in teaching students about the functions of computer network concepts. Our analysis of defense mechanisms in biological cells showed that security in cells is integrated, ubiquitous, and continuous. An example illustrates how the framework can generate ideas for improving network security.

Threats and attacks that can result in leaks of personal or sensitive data or reduced business performance have a significant impact on the security of networks and information systems. Insider attacks, eavesdropping, misconfiguration, missing functionality, confusion, man-in- attacks, virus attacks, denial of service attacks are some of the dangers that threaten your network security or threaten the security of your network. Attacks are possible. Influencing information systems. Companies risk losing information appropriate security measures, such as network and information system security. You can implement the right security solutions to predict and prevent various security risks and attacks. Confidentiality, integrity, and availability are three characteristics of security, and to determine which security technology best suits your organization's needs, you must first compare the various threats and attacks with the security technologies in use. Recommended security technologies intrusion detection systems (IDS), antivirus programs, and encryption systems. This is because this technology relies on predicting and protecting networks and information systems in many security elements.

In order to solve wireless local area network (WLAN) security problem due to the open-wide nature of wireless radio and the improvement of computing power, a design of WLAN security program based on near field communication (NFC) is presented in this paper. In this paper, the importance of having access to handshake for WPA2 brute force is explained. The proposed design protects the four-way handshake by taking advantage of NFC short-range character to eliminate the risk of intercept. For implementation, Android system is selected as a mobile device development platform. The design is compatible with the IEEE 802.11i which ensures the massive expansion in the future. Furthermore, the design simplifies operations to improve users’ experience without much extra hardware cost and offers an option to the owner of WLAN to control the access physically, which benefits commercialization of NFC. From one perspective, this design can solve the wireless network security problem effectively.KeywordsWireless Local Area NetworkNear Field CommunicationWireless RouterDictionary AttackAndroid SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

With the rapid development of computer technology and big data technology, the security of computer network has become a key problem that restricts its development. The improved new technology also causes huge network security problems. The continuous development of big data will improve the design level of computer network security system. However, as a media, the computer's requirements for computer network security will also increase. Therefore, it is necessary to continuously strengthen the security of computer network system, improve users' usage and improve the network security status. It is a very effective means to improve the network security through legal restrictions, so it has become the first task. With the continuous improvement of information and data transmission speed, information and data will accumulate in the process of information technology utilization, thus causing security problems. The computer network security technology in the big data environment seriously affects the development of information technology and the development of the whole society.

In this chapter we consider a service provider-centric view of network security. We primarily focus on network security given the current Internet architecture, protocols and business relationships. Within this context we first examine the underlying security threats and causes, before articulating the need for a comprehensive security framework to drive provider network security practices. We emphasize the need of wide-ranging network monitoring to provide intelligence concerning security events. We describe several network security systems and the importance of considering network security operations as an integral part of ongoing network operations. Finally, we identify important future network security concerns and directions.

This paper described the current network of primary language XML in network applications, introduced its own XML language features and development to illustrate aspects of XML technology in the application of network security and significance. The network security is a systems engineering which is need to carefully consider the security needs of the system, and a variety of security technologies, such as passwords and technology combine to produce a highly efficient, universal, secure network systems. Secondly, this paper analysis of network security architecture and the current network security system for the protection of technical methods used: the network against viruses, configuration, firewall, intrusion detection systems used, Web, Email, BBS's safety monitoring system, vulnerability scanning systems, IP Theft solution, using network monitoring to maintain system security subnet. Finally, the XML technology for network security enabled areas of security, XML has become a field for the safety of a valuable mechanism for exchange of data, related development is related to XML encryption and XML signature.

It is a multiple criteria problem to evaluate the security of information networks. However, one key issue which is not fully considered in extant studies is how to obtain the values of these multiple evaluation criteria, and in most evaluation models some redundant criteria values are calculated. Motivated by this, in the work we first use the pairwise comparison method to attain the values of each evaluation aspect of the security of information networks, and then develop a novel similarity-based M(1, 2, 3) approach to rate the security of alternative networks. Application study shows that the proposed approach could rate the overall security of alternative information networks and recognize the most vulnerable aspects of each information network, which provides good supports for making policies to enhance the security of alternative information networks.

Modeling the impact of environmental change on infectious diseases

Individual size distributions (ISDs) are prominent in ecological research and may support resource managers with ecosystem-scale objectives. We use a database of individual size measurements for US stream fishes to test for direct and indirect effects of traits, flow regimes, and land use on the interspecific ISD exponent. Path analysis indicates that traits have strong, direct effects on ISD. Flow and land use effects on the exponent are largely indirectly mediated by their influences on species traits. ISD exponents increase (abundances of larger-bodied individuals increase, relative to smaller-bodied) when environments favor higher trophic levels, warmer thermal tolerances, and periodic life histories. Alternatively, ISD exponents decrease in systems that favor opportunistic life histories. Our flexible modeling framework that includes direct and indirect effects of traits, flow regimes, and land use on ISD could be expanded to incorporate additional variables that interact with flow (e.g., temperature and physical habitat) to assess of effects of multiple stressors on aquatic ecosystem functioning.

We propose a generalized mixture integer-valued generalized autoregressive conditional heteroscedastic model to provide a more flexible modeling framework. This model includes many mixture integer-valued models with different distributions already studied in the literature. The conditional and unconditional moments are discussed and the necessary and sufficient first- and second-order stationary conditions are derived. We also investigate the theoretical properties such as strict stationarity and ergodicity for the mixture process. The conditional maximum likelihood estimators via the EM algorithm are derived and the performances of the estimators are studied via simulation. The model can be selected in terms of both the number of mixture regimes and the number of orders in each regime by several different criteria. A real-life data example is also given to assess the performance of the model.

Abstract. This paper presents a new reconstruction of the 20th century global hydrography using fully coupled water balance and transport model in a flexible modeling framework. The modeling framework allows a high level of configurability both in terms of input forcings and model structure. Spatial and temporal trends in hydrological cycle components are assessed under "pre-industrial" conditions (without modern-day human activities) and contemporary conditions (incorporating the effects of irrigation and reservoir operations). The two sets of simulations allow the isolation of the trends arising from variations in the climate input driver alone and from human interventions. The sensitivity of the results to variations in input data was tested by using three global gridded datasets of precipitation. Our findings confirm that the expansion of irrigation and the construction of reservoirs has significantly and gradually impacted hydrological components in individual river basins. Variations in the volume of water entering the oceans annually, however, are governed primarily by variations in the climate signal alone with human activities playing a minor role. Globally, we do not find a significant trend in the terrestrial discharge over the last century. The largest impact of human intervention on the hydrological cycle arises from the operation of reservoirs that drastically changes the seasonal pattern of horizontal water transport in the river system and thereby directly and indirectly affects a number of processes such as ability to decompose organic matter or the cycling of nutrients in the river system.

A model for analyzing multiple categorical dependent variables is presented and developed for use in organizational research. A primary example occurs in the foreign market entry literature, in which choice of ownership (majority, equal, or minority) and function (acquisition or joint venture) are simultaneously endogenous; only separate univariate ownership-based and function-based choice models are considered in the literature. Another example is in the comparison of gender and race across organizational units, controlling for confounders such as experience and qualification. Subsuming univariate categorical dependent variables as a special case, the model unifies existing organizational research methods, mitigates bias associated with univariate methods, provides more powerful testing methods, and provides a flexible modeling framework that allows hypotheses to be modeled and tested that are not possible with univariate models. Standard software may be used for estimation and testing; examples are given.

An in-stream water quality model, QUESTOR (Quality Evaluation and Simulation Tool for River-systems), has been applied to rivers in Belgium, Finland and the United Kingdom as part of a study of the effects of climate change on the quality of freshwater resources in Europe. QUESTOR provides a flexible modelling framework that enables the assessment of alternative model structures based on different process representations. Results are presented from the application of a basic form of the model that includes a limited set of processes. The results for present-day simulations are good on all three catchments although the catchments have very different characteristics. However, the requirement for a more sophisticated model for simulations under possible future climatic conditions is identified.