Enterprise Network Management Research Articles

The Integration of Artificial Intelligence in Secure Access Service Edge: Enhancing Network Security and Performance

Integrating Artificial Intelligence (AI) with Secure Access Service Edge (SASE) architecture represents a significant advancement in enterprise network security and management. This article examines the transformative impact of AI technologies on SASE implementations, focusing on enhanced threat detection capabilities, dynamic network optimization, and automated compliance management. The article comprehensively analyzes AI-driven security features, including real-time threat detection, zero-trust implementation, and privacy-preserving security measures. Through extensive evaluation of deployment scenarios and performance metrics, our research demonstrates significant improvements in security effectiveness and operational efficiency, including a 90% reduction in threat detection time, a 45% decrease in network latency, and a 65% reduction in manual configuration tasks. The article highlights the system's capability to maintain robust security while preserving data privacy through advanced encrypted traffic analysis techniques. The article addresses current integration challenges and provides insights into successful implementation strategies. This article contributes to the growing body of knowledge on AI-enhanced network security architectures and provides valuable insights for organizations seeking to modernize their security infrastructure while maintaining operational efficiency and compliance with evolving regulatory requirements.

Revolutionizing Enterprise Network Management: The Role of Ai-Driven Solutions in Modern Computer Networking

In the rapidly evolving landscape of enterprise network management, artificial intelligence (AI) is emerging as a transformative force. This paper, titled "Revolutionizing Enterprise Network Management: The Role of AI-Driven Solutions in Modern Computer Networking," delves into the significant impact of AI technologies on the efficiency, security, and scalability of enterprise networks. By integrating AI-driven solutions, organizations can achieve unprecedented levels of automation, predictive maintenance, and real-time anomaly detection, thus enhancing overall network performance. This study provides a comprehensive analysis of the latest AI techniques employed in network management, including machine learning algorithms, neural networks, and advanced data analytics. Through case studies and empirical data, we demonstrate how AI enhances network security, reduces downtime, and optimizes resource allocation. Our findings suggest that the adoption of AI in network management not only improves operational efficiency but also offers a competitive advantage in the digital economy. Keywords: AI-driven network management, enterprise network security, machine learning in networking, predictive maintenance, network automation, real-time anomaly detection, computer networking, digital transformation.

Research on the Teaching Reform of Computer Network in the New Era

The Computer Network course is widely offered in colleges and universities. This course is both theoretical and practical. It organically combines theory and practice in order to achieve the goal of teaching. The main objective of the course is to train students to have various skills, including those of enterprise scale network construction, network management, and network maintenance. Influenced by traditional teaching for a long time, the existing teaching of the course in colleges and universities urgently needs reform; otherwise, it will not be able to meet the social demand for talents in the new era. This paper focuses on the practical problems of the Computer Network teaching reform and proposes some effective reform suggestions, hoping to engender an efficient link among the Computer Network course teaching, talent training, and the social needs in colleges and universities.

Research on high security of IP tunnel in virtual private network

IPSec encrypts and authenticates the packets of IP protocol. Both sides of IP network layer communication use encryption authentication, data source authentication and integrity verification to ensure the integrity, confidentiality and anti replay of IP protocol packet transmission. In enterprise network management, we can usually use IPSec VPN technology to establish a secure channel to realize the secure communication between headquarters and branches.[1]

Enterprise Integration Patterns in SDN: A Reliable, Fault-Tolerant Communication Framework

In today’s era, large data centers are drawn toward the two popular technologies, i.e., enterprise integration patterns (EIP) and software defined networking (SDN). The former is the combination of design patterns which integrates the new and existing business applications in an enterprise environment, whereas the latter is a rapidly evolving networking paradigm that has reshaped the large enterprise network management by introducing the programmable planes and centralized control. The promising features of EIP, i.e., asynchronous communication, reliability and that of SDN, namely, robustness, network programmability, agility, and global visibility can be merged in order to cope with growing network demands and security. In this article, we propose a communication framework that incorporates both EIP and SDN in an enterprise environment. The architecture of the propose communication framework consists of adaptive virtual local area network (VLAN) module to install and delete VLANs reactively using EIP. Furthermore, to enable communication between applications from different networks in an enterprise environment, this framework also contains a packet forwarding module where hosts IP addresses are concealed from each other. In the end, we demonstrate through simulations that how the proposed integrated design can be helpful in improving the security, efficiency, and reliability aspects of the enterprise network. As proof of concept, we also discuss the deployment of our proposed framework in IoT-based Smart Cities, which is the extension of EIP on a large scale.

Dynamic Contract Design for Systemic Cyber Risk Management of Interdependent Enterprise Networks

The interconnectivity of cyber and physical systems and Internet of things has created ubiquitous concerns of cyber threats for enterprise system managers. It is common that the asset owners and enterprise network operators need to work with cybersecurity professionals to manage the risk by remunerating them for their efforts that are not directly observable. In this paper, we use a principal-agent framework to capture the service relationships between the two parties, i.e., the asset owner (principal) and the cyber risk manager (agent). Specifically, we consider a dynamic systemic risk management problem with asymmetric information where the principal can only observe cyber risk outcomes of the enterprise network rather than directly the efforts that the manager expends on protecting the resources. Under this information pattern, the principal aims to minimize the systemic cyber risks by designing a dynamic contract that specifies the compensation flows and the anticipated efforts of the manager by taking into account his incentives and rational behaviors. We formulate a bi-level mechanism design problem for dynamic contract design within the framework of a class of stochastic differential games. We show that the principal has rational controllability of the systemic risk by designing an incentive compatible estimator of the agent's hidden efforts. We characterize the optimal solution by reformulating the problem as a stochastic optimal control program which can be solved using dynamic programming. We further investigate a benchmark scenario with complete information and identify conditions that yield zero information rent and lead to a new certainty equivalence principle for principal-agent problems. Finally, case studies over networked systems are carried out to illustrate the theoretical results obtained.

Neuro fuzzy cognitive connection functional point for enterprise network management

Neuro fuzzy cognitive connection functional point for enterprise network management

Multi-layer Virtual Transport Network management

Nowadays there is an increasing need for a general paradigm which can simplify network management and further enable network innovations. Software Defined Networking (SDN) is an efficient way to make the network programmable and reduce management complexity, however existing SDN solutions do not realize the full potential of SDN because of their lack of scoping in network management. In response to limitations of current Software Defined Networking (SDN) management solutions, we propose a recursive approach to enterprise network management, where network management is done through managing various Virtual Transport Networks (VTNs) over different scopes (i.e., regions of operation).Our approach offers a generalized and structured framework to realize the full potential of SDN using recursive scoped management, and our VTN-based approach provides communication service with explicit Quality-of-Service (QoS) support for applications via transport flows. Each VTN involves all mechanisms (e.g., addressing, routing, error and flow control, resource allocation) needed to support such transport flows. Based on this approach, we design and implement a management architecture, which recurses the same VTN-based management mechanism for enterprise network management. Our experimental results show that our management architecture achieves better performance demonstrated through unicast and multicast video applications.

Adaptive Distributed Enterprise Network Management Model Based on Physical Topology

Adaptive Distributed Enterprise Network Management Model Based on Physical Topology

Towards flexible management in enterprise network: an enhanced routing protocol

With the development of the Internet, people put more demands on networks. Among different networks, enterprise network faces more challenges, because of its large scale and diverse goals. Configuration of enterprise network is always daunting for network operators. In this paper, we propose a new routing protocol called TwoD-IP routing to facilitate enterprise network management. With TwoD-IP routing, we can achieve flexible management by providing different views on the same network for different users. We design the routing protocol algorithm, and implement it on a quagga-based router. Finally, we evaluate our mechanism using simulations with BRITE generated topologies. The results show that our mechanism can greatly reduce the network configuration complexities.

학내 망 자원 효율화를 위한 빅 데이터 트래픽 분석

급하게 일어나는 인터넷의 활성화는 그 어느 때보다 효율적인 엔터프라이즈 망 운영 방안을 필요로 하고 있다. 효율적인 망 운영을 위해서는 장기간의 트래픽 분석을 통해 망의 특성을 정확히 반영한 운영 정책 적용이 필요하다. 하지만 기존에는 급격하게 증가하는 장기간 트래픽 데이터의 처리가 불가능했고, 다양한 분석 결과를 낼 수 없는 단기간 분석만 이루어졌다. 최근 빅 데이터 분석 플랫폼과 도구의 개발로 인해 장기간 트래픽 분석이 가능하게 되었고, 이를 이용해 망의 특성을 정확히 반영할 수 있는 장기간 트래픽 분석을 통한 엔터프라이즈 망 자원효율화 방안이 요구되고 있다. 본 논문에서는 엔터프라이즈 망에서 발생한 장기간의 트래픽을 수집하고 저장 및 관리하는 방안에 대해 제안한다. 또한 분류기준을 정의하였으며, 수집된 빅 데이터 트래픽을 각 분류 기준으로 분류한 뒤 다각적인 통계 분석을 통해 망 자원을 효율화 하는 방안을 제안한다. 제안하는 방법을 학내 망에 적용하여 실험하였으며, 통계 분석 결과 시간과 공간, 그리고 사용목적에 따라 Quality of Service(QoS)정책을 달리 적용해야 함을 확인하였다. The importance of efficient enterprise network management has been emphasized continuously because of the rapid utilization of Internet in a limited resource environment. For the efficient network management, the management policy that reflects the characteristics of a specific network extracted from long-term traffic analysis is essential. However, the long-term traffic data could not be handled in the past and there was only simple analysis with the shot-term traffic data. However, as the big data analytics platforms are developed, the long-term traffic data can be analyzed easily. Recently, enterprise network resource efficiency through the long-term traffic analysis is required. In this paper, we propose the methods of collecting, storing and managing the long-term enterprise traffic data. We define several classification categories, and propose a novel network resource efficiency through the multidirectional statistical analysis of classified long-term traffic. The proposed method adopted to the campus network for the evaluation. The analysis results shows that, for the efficient enterprise network management, the QoS policy must be adopted in different rules that is tuned by time, space, and the purpose.

Research of Unified Authentication System Based on LDAP

With the development of Internet technology, the increasing of the application service makes the enterprise network management and security more and more complex. Based on it, the enterprise portal needs a system with high performance for identity authentication management. In this, implements the research of unified identify authentication system through LDAP, designs a rational structure of the directory tree. Thus, All the application servers use the user information in the same directory. By the manner, the problem of disagreement and larger maintenance burden can be solved and the system security can be improved.

TIE: Traffic Identification Engine

Traffic Classification is a hot topic in many different contexts, such as management of enterprise networks, and scientific research on the Internet and on aspects related to network neutrality and censorship. Despite the large quantity of works published in the past few years on traffic classification, aside from port-based classifiers and those based on payload inspection (having well-known issues related to privacy of users and computational cost), there are few implementations made available to the community – for experimenting – and to Telecom Operators – for controlling their networks – that target alternative and novel approaches for traffic classification. In order to experiment with new algorithms and approaches and to correctly operate real networks, there is a strong need for open platforms.

The Entreprise Network, a Managerial Assumption in the Social Market Economy

The network of enterprises in various forms existed before the advent of computing, and consisted of a business. Network businesses are based on the idea of sharing and trust, they are valid attributes for internal computer networks and network o f partners. The main problem is the management of enterprise networks and interdependence between the formulation of management strategies, skills development, technology development and human resource management systems.

Research and Implementation of Product Lifecycle Management Platform Based on Teamcenter

Product lifecycle management (PLM) is a kind of solution, software technology and a business strategy, which play an indispensable role in the enterprise informatization and network management. In this paper, Teamcenter management software of SIEMENS is applied as basic platform of implementing PLM project, the fundamental network structure and main functions and solutions are introduced, furthermore, it also mainly researches the implementation strategies and process of PLM project and analyses the application values and advantages of PLM project for the enterprises.

Network exception handlers

Enterprise network architecture and management have followed the Internet's design principles despite different requirements and characteristics: enterprise hosts are administered by a single authority, which intrinsically assigns different values to traffic from different business applications. We advocate a new approach where hosts are no longer relegated to the network's periphery, but actively participate in network-related decisions. To enable host participation, network information, such as dynamic network topology and per-link characteristics and costs, is exposed to the hosts, and network administrators specify conditions on the propagated network information that trigger actions to be performed while a condition holds. The combination of a condition and its actions embodies the concept of the network exception handler, defined analogous to a program exception handler. Conceptually, network exception handlers execute on hosts with actions parameterized by network and host state. Network exception handlers allow hosts to participate in network management, traffic engineering and other operational decisions by explicitly controlling host traffic under predefined conditions. This flexibility improves overall performance by allowing efficient use of network resources. We outline several sample network exception handlers, present an architecture to support them, and evaluate them using data collected from our own enterprise network.

Innovation paths management in collaborative enterprise clusters

Current scenario in supply chains and logistic networks is characterised by industrial districts, SMEs clusters and networking organisations, which are formal or informal connected to follow the common aim of development improvement. In this paper, particular reference is made to collaborative demand and supply networks, where main problems concern the coordination of distributed and autonomous agents and the application of suitable methodologies and models able to represent cooperative behaviour and to evaluate global performances. In particular, a conceptual model of a SMEs network is presented and the approach of the European project CO-DESNET is illustrated. Then, the adoption of information and communication technologies for the innovation path development in the management of enterprise networks is discussed. Finally, a case study is outlined relative to the transition to the Net Economy of SMEs in the Lazio Region in Italy.

Detecting Internet worms at early stage

Managing the security of enterprise networks has emerged to be a critical problem in the era of Internet economy. Arising as a leading threat, worms repetitively caused enormous damage to the Internet community during the past years. A new security service that monitors the ongoing worm activities on the Internet will greatly contribute to the security management of modern enterprise networks. This paper proposes an Internet-worm early warning system that automatically detects concerted scan activities and derives possible signatures of worm attacks. Its goal is to issue warning at the early stage of worm propagation and to provide necessary information for security analysts to control the damage. It reduces false positives by filtering out false scan sources. The system is locally deployable or can be codeployed amongst a group of enterprise networks. We provide both analytical and simulation studies on the responsiveness of this early warning system.

DETECTION OF ABNORMAL CHANGE IN A TIME SERIES OF GRAPHS

In the management of large enterprise communication networks, it becomes difficult to detect and identify causes of abnormal change in traffic distributions when the underlying logical topology is dynamic. This paper describes a novel approach to abnormal network change detection by representing periodic observations of logical communications within a network as a time series of graphs. A number of graph distance measures are proposed to assess the difference between successive graphs and identify abnormal behaviour. Localisation techniques have also been described to show where in the network most change occurred.

Projecting advanced enterprise network and service management to active networks

Active networks is a promising technology that allows us to control the behavior of network nodes by programming them to perform advanced operations and computations. Active networks are changing considerably the scenery of computer networks and, consequently, affect the way network management is conducted. Current management techniques can be enhanced and their efficiency can be improved, while novel techniques can be deployed. This article discusses the impact of active networks on current network management practice by examining network management through the functional areas of fault, configuration, accounting, performance and security management. For each one of these functional areas, the limitations of the current applications and tools are presented, as well as how these limitations can be overcome by exploiting active networks. To illustrate the presented framework, several applications are examined. The contribution of this work is to analyze, classify, and assess the various models proposed in this area, and to outline new research directions.