VLANs: This topic explains the VLAN capabilities of Cisco security appliances. With Cisco PIX Security Appliance Software v6.3 and higher and Cisco PIX and ASA Security Appliance Software v7.0 and higher, the administrator can assign VLANs to physical interfaces on the security appliance or configure multiple logical interfaces on a single physical interface and assign each logical interface to a specific VLAN. A VLAN connects devices on one or more physical LAN segments so that the VLAN can act as though it is attached to the same physical LAN. VLANs make this connection based on logical (software) connections instead of physical connections, which makes them extremely flexible because you can configure and reconfigure which segments belong to which VLAN entirely through software. Cisco PIX Series 500 Security Appliances (except for the 501, 506, and 506E) and Cisco ASA 5500 Series Adaptive Security Appliances support only 802.1q VLANs. Specifically, they support multiple 802.1q VLANs on a physical interface and the ability to receive and send 802.1q-tagged packets. VLANs are not supported on the Cisco PIX 501, 506, and 506E Security Appliances. Cisco security appliances do not currently support executable commands for LAN trunks (the physical and logical connection between two switches) because the security appliances do not negotiate or participate in any bridging protocols. The security appliances display the VLANs only on the LAN trunk. It considers the state of the LAN trunk to be the same as the state of the physical interface. If the link is up on the physical Ethernet, then the security appliance considers the trunk as up as soon as a VLAN has been assigned or configured for it. Additionally, the VLAN is active as soon as you assign or configure a VLAN identifier (ID) on the physical Ethernet interface of the security appliance.
Security Context Overview: This topic provides an overview of security contexts. You can partition a single security appliance into multiple virtual firewalls, known as security contexts. Each context is an independent firewall, with its own security policy, interfaces, and administrators. Having multiple contexts is similar to having multiple stand-alone firewalls. Each context has its own configuration that identifies the security policy, interfaces, and almost all the options you can configure on a stand-alone firewall. If desired, you can allow individual context administrators to implement the security policy on the context. Some resources are controlled by the overall system administrator, such as VLANs and system resources, so that one context cannot affect other contexts inadvertently. The system administrator adds and manages contexts by configuring them in the system configuration, which identifies basic settings for the security appliance. The system administrator has privileges to manage all contexts. The system configuration does not include any network interfaces or network settings for itself; rather, when the system needs to access network resources (such as downloading the contexts from the server), it uses one of the contexts that is designated as the admin context. The admin context is just like any other context, except that when a user logs into the admin context, that user has system administrator rights and can access the system execution space and all other contexts. Typically, the admin context provides network access to network-wide resources, such as a syslog server or context configuration server.
Activity Procedure: Answer these questions based on the figures. Write your answers in the appropriate spaces. Q1) In the figure, label these elements: A) Enterprise Campus B) Enterprise Edge C) Service Provider Edge Q2) In the figure, label these elements: A) Enterprise Campus B) Enterprise Edge C) Edge Distribution D) Service Provider Edge Q3) In the figure, label these elements: A) core B) distribution C) access
Implementing Secure Converged Wide Area Networks (ISCW) is an advanced course that introduces techniques and features enabling or enhancing WAN and remote access solutions. The course focuses on using one or more of the available WAN connection technologies for remote access between enterprise sites. This course includes cable modems and DSL with Network Address Translation (NAT), Multiprotocol Label Switching (MPLS), virtual private networks (VPNs), and network security using VPNs with IPSec encryption and Internet Key Exchange (IKE) keys. After taking this course, learners will be able to secure the network environment using existing Cisco IOS security features, and configure the three primary components of the Cisco IOS Firewall Feature set: firewall, intrusion prevention system (IPS), and authentication, authorization, and accounting (AAA). This task-oriented course teaches the knowledge and skills needed to secure Cisco IOS router networks using features and commands in Cisco IOS software, and using a router configuration application. ISCW is part of the recommended learning path for students seeking the Cisco Certified Network Professional (CCNP).
Social network research focuses on the study of social systems by conceptualizing their internal structure in terms of sets of complex dependencies among social agents in the form of dyadic social ties. Typically, models for social networks incorporate additional features such as actor attributes. Models for social networks may also be extended in various ways by considering, for example, multiplex or bipartite representations. However, incorrect inferences can be drawn from social network analysis if the system is conceptualized in an overly simplistic way. This can happen if crucial elements of social structure are ignored when the data are collected, or are mis-specified in the model used for the analysis. As social network researchers, we know this well, because we avoid individualistic analysis of attributes when social structure is relevant. In one of the foundational articles of contemporary social network analysis, Harrison White and co-authors warned against relying on social classification as the sole basis for understanding social structure: “. . .largely categorical descriptions of social structure have no solid theoretical grounding; . . . network concepts may provide the only way to construct a theory of social structure” (White et al., 1976, p.732). Network researchers (but not all social scientists) have learnt that lesson well.
In the past few years, we have seen a rapid expansion in the field of mobile computing due to the proliferation of inexpensive, widely available wireless devices. However, current devices, applications and protocols are solely focused on cellular or wireless local area networks (WLANs), not taking into account the great potential offered by mobile ad hoc networking. A mobile ad hoc network is an autonomous collection of mobile devices (laptops, smart phones ,sensors, etc.) that communicate with each other over wireless links and cooperate in a distributed manner in order to provide the necessary network functionality in the absence of a fixed infrastructure. This type of network, operating as a stand-alone network or with one or multiple points of attachment to cellular networks or the Internet, paves the way for numerous new and exciting applications. Application scenarios include, but are not limited to: emergency and rescue operations, conference or campus settings, car networks, personal networking, etc. This paper provides insight into the potential applications of ad hoc networks and discusses the technological challenges that protocol designers and network developers are faced with. These challenges include routing, service and resource discovery, Internet connectivity, billing and security.
The use of wireless sensor networks in home automation (WSNHA) is attractive due to their characteristics of self-organization, high sensing fidelity, low cost, and potential for rapid deployment. Although the AODVjr routing algorithm in IEEE 802.15.4/ZigBee and other routing algorithms have been designed for wireless sensor networks, not all are suitable for WSNHA .In this paper, we propose a location-based self-adaptive routing algorithm for WSNHA called WSNHA-LBAR. It confines route discovery flooding to a cylindrical request zone, which reduces the routing overhead and decreases broadcast storm problems in the MAC layer. It also automatically adjusts the size of the request zone using a self-adaptive algorithm based on Bayes’ theorem .This makes WSNHA-LBAR more adaptable to the changes of the network state and easier to implement. Simulation results show improved network reliability as well as reduced routing overhead.
With the formidable growth of various booming wireless communication services that require ever increasing data throughputs, the conventional microwave band below 10 GHz, which is currently used by almost all mobile communication systems, is going to reach its saturation point within just a few years. Therefore, the attention of radio system designers has been pushed toward ever higher segments of the frequency spectrum in a quest for increased capacity. In this article we investigate the feasibility, advantages, and challenges of future wireless communications over the Eband frequencies. We start with a brief review of the history of the E-band spectrum and its light licensing policy as well as benefits/challenges. Then we introduce the propagation characteristics of E-band signals, based on which some potential fixed and mobile applications at the E-band are investigated. In particular, we analyze the achievability of a nontrivial multiplexing gain in fixed point-to-point E-band links, and propose an E-band mobile broadband (EMB) system as a candidate for the next generation mobile communication networks. The channelization and frame structure of the EMB system are discussed in detail .
Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.
We address the problem of compressing large and distributed signals monitored by a Wireless Sensor Network (WSN) and recovering them through the collection of a small number of samples.