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Before going further, it s important to understand some key terminology used in this bookThe structure of a DSL is captured in its metamodel, commonly referred to as its abstract syntax A metamodel is just a model that provides the basis for constructing another model Although both are models, one is expressed in terms of the other; in other words, one model is an instance of or conforms to the other In this book, a DSL s abstract syntax is defined using EMF s Ecore model, which is, therefore, its metamodel and the model used to define all DSLs in this book A model created in terms of our DSL s abstract syntax is commonly referred to as an instance model; the DSL is then the metamodel, which makes Ecore the metametamodelThe Ecore model is expressed in terms of itself, but this book doesn t give this a name or assign an absolute numbering scheme to the levels, as the Object Management Group (OMG) does For our purposes, you can simply think of Ecore as the metamodel that a Toolsmith uses to define a DSL s abstract syntax, leaving the Practitioner to create instance models of the DSL The term abstract syntax refers to a metamodel, so it often has a corresponding concrete syntax in the form of text or diagram notation These are referred to as textual concrete syntax and graphical concrete syntax, respectively A textual syntax enables users to work with instance models just as they would other text-based programming languages A graphical syntax enables users to work with instance odels using a diagram surface; the most popular is the UML Abstract syntaxes are defined using Ecore models, which themselves are persisted in XMI format this could technically be considered a concrete syntax, although it s sometimes called a serialization syntax.

One way to make this happen and to defend gainst a possible attack is to observe the behavior of the nodes over time and decide whether to trust them These techniques can be used mainly to protect the Position Computation component, since information gathered from untrusted nodes can simply be ignored when computing the position of the nodes For instance, in Liu et al [28] it is proposed a set of techniques for detecting malicious beacon nodes One technique detects malicious beacon nodes by comparing the distance estimated by using the location information provided by these beacon nodes and the distance estimated by means of the signal (eg, RSSI, TDoA, AoA) Another technique evaluates the round-trip time (RTT) between two neighbors, based on the observation that the replay of a (malicious) beacon signal introduces extra delay.

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Then, the base station (or sink node) uses such information about malicious beacons to reason about the suspiciousness of each beacon node, and then it lters out malicious beacon nodes accordingly Srinivasan et al [29] extends the techniques proposed by Liu et al [28] by using a continuous scale and a reputation- and trust-based mechanism The result is the Distributed Reputation-based Beacon Trust System (DRBTS), which is a distributed security protocol for excluding malicious beacon nodes In DRBTS, each beacon node monitors its neighborhood for suspicious beacon nodes and provides information by maintaining and exchanging a Neighbor-Reputation Table, in such a way that other sensor nodes can choose trustworthy beacons based on a voting approach 1843 Robust Position Computation Robust position computation can be used in order to increase the security of a localization system This technique can be used when both cryptography and misbehavior detection is compromised.

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In 1993 the work on providing lightweight client access o X500 servers resulted in the publication of RFC 1487, X500 Lightweight Access Version 1 of the protocol Paint Barcode In Java Using Barcode printer for Java .

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In this case, a way to deal with malicious nodes is to accept that they will be present in the network and propose robust position computations that can still work in the presence of bogus information This is done mostly by using statistical and outlier ltering techniques In these cases, it is assumed that the benign nodes outnumber the malicious ones These techniques are used to protect against (or be robust to) attacks on the Position Computation and Distance/Angle Estimation components A technique proposed by Li et al [30] uses the principle behind the least squares data fusion technique to propose an adaptive least squares and least median squares Bar Code In NET Framework Using Barcode scanner for Related: NET EAN-8 Generator , UPC-E Generator NET , ISBN Generation NET.

We ve already mentioned that LDAP uses TCP/IP (although it could be made to run on other network protocols) and does not require OSI The encoding of requests and responses also was signi cantly simpli ed X500 allows the data stream of requests and responses to be encoded in many different ways, all of which are variants of the Basic Encoding Rules ( BER) speci cation of Abstract Syntax Notation One ASN1) Although ASN1 is a very powerful and expressive syntax, it requires the client to be capable of interpreting the data types in many different encodings In LDAP, only a small subset of BER is used and required, and most data types are transmitted as strings As a result, LDAP clients do not need to handle the multitude of other encodings and data types required by X500 The authors of LDAP de ned an API for accessing the protocol and assembled an SDK for applications developers X500 lacked a standard client API, which forced client application developers to write most of the code for using the protocol Initially the LDAP speci cations omitted de nitions for data replication, referrals (situations in which a server without the requested information can redirect a client to another server that has the information), access control, chaining (situations in which a server without the requested information contacts another server on behalf of a client), and many other standard X500 features Some of these features have been added to the LDAP speci cations in version 3 or are currently under discussion as proposed additions Other features have been implemented in software from the University of Michigan or from other vendors but have not been standardized Another critical difference between X500 and LDAP is in the understanding of how directories can be combined to form a single globally searchable service The X500 developers envisioned a partition of all directory space in the world on a country basis At the root of the tree in each directory is a null entry that cannot be searched and that has no user attributes It represents a virtual shared root of all directories Under the null node, the directory contains one or more country nodes Under the country nodes, there are organization nodes, which correspond to companies Each company node can contain any structure appropriate to the company Typically this structure consists of a tree of organizational unit nodes, each corresponding to departments or divisions of the company If a request for company information is directed to a particular X500 server, the server can quickly determine that the.

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