HOP-BY-HOP MESSAGE AUTHENTICATION AND SOURCE PRIVACY IN WIRELESS SENSOR NETWORKS
By
A
PROJECT REPORT
Submitted to the Department of Computer Science & Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY
In partial fulfillment of the requirements for the award of the degree
Of
MASTER OF TECHNOLOGY
IN
COMPUTER SCIENCE & ENGINEERING
APRIL 2015
BONAFIDE CERTIFICATE
Certified that this project report titled “HOP-BY-HOP MESSAGE AUTHENTICATION AND SOURCE PRIVACY IN WIRELESS SENSOR NETWORKS” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.
Signature of the Guide Signature of the H.O.D
Name Name
CHAPTER 1
ABSTRACT:
Message authentication is one of the most effective ways to thwart unauthorized and corrupted messages from being forwarded in wireless sensor networks (WSNs). For this reason, many message authentication schemes have been developed, based on either symmetric-key cryptosystems or public-key cryptosystems. Most of them, however, have the limitations of high computational and communication overhead in addition to lack of scalability and resilience to node compromise attacks. To address these issues, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial: when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial.
In this paper, we propose a scalable authentication scheme based on elliptic curve cryptography (ECC). While enabling intermediate nodes authentication, our proposed scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. In addition, our scheme can also provide message source privacy. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based approach in terms of computational and communication overhead under comparable security levels while providing message source privacy.
INTRODUCTION:
MESSAGE authentication plays a key role in thwarting unauthorized and corrupted messages from being forwarded in networks to save the precious sensor energy. For this reason, many authentication schemes have been proposed in literature to provide message authenticity and integrity verification for wireless sensor networks (WSNs) .These schemes can largely be divided into two categories: public-key based approaches and symmetric-key based approaches. The symmetric-key based approach requires complex key management, lacks of scalability, and is not resilient to large numbers of node compromise attacks since the message sender and the receiver have to share a secret key. The shared key is used by the sender to generate a message authentication code (MAC) for each transmitted message. However, for this method, the authenticity and integrity of the message can only be verified by the node with the shared secret key, which is generally shared by a group of sensor nodes. An intruder can compromise the key by capturing a single sensor node.
In addition, this method does not work in multicast networks. To solve the scalability problem, a secret polynomial based message authentication scheme was introduced in. The idea of this scheme is similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial. This approach offers information-theoretic security of the shared secret key when the number of messages transmitted is less than the threshold. The intermediate nodes verify the authenticity of the message through a polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. An alternative solution was proposed in to thwart the intruder from recovering the polynomial by computing the coefficients of the polynomial. The idea is to add a random noise, also called a perturbation factor, to the polynomial so that the coefficients of the polynomial cannot be easily solved. However, a recent study shows that the random noise can be completely removed from the polynomial using error-correcting code techniques . For the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. One of the limitations of the public-key based scheme is the high computational overhead. The recent progress on elliptic curve cryptography (ECC) shows that the public key schemes can be more advantageous in terms of key by capturing a single sensor node. In addition, this method does not work in multicast networks. To solve the scalability problem, a secret polynomial based message authentication scheme was introduced in. The idea of this scheme is similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial.
This approach offers information-theoretic security of the shared secret key when the number of messages transmitted is less than the threshold. The intermediate nodes verify the authenticity of the message through a polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. An alternative solution was proposed in to thwart the intruder from recovering the polynomial by computing the coefficients of the polynomial. The idea is to add a random noise, also called a perturbation factor, to the polynomial so that the coefficients of the polynomial cannot be easily solved. However, a recent study shows that the random noise can be completely removed from the polynomial using error-correcting code techniques. For the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. One of the limitations of the public-key based scheme is the high computational overhead. The recent progress on elliptic curve cryptography (ECC) shows that the public key schemes can be more advantageous in terms of computational complexity, memory usage, and security resilience, since public-key based approaches have a simple and clean key management.
In this paper, we propose an unconditionally secure and efficient source anonymous message authentication (SAMA) scheme based on the optimal modified ElGamal signature (MES) scheme on elliptic curves. This MES scheme is secure against adaptive chosen-message attacks in the random oracle model. Our scheme enables the intermediate nodes to authenticate the message so that all corrupted message can be detected and dropped to conserve the sensor power. While achieving compromiseresiliency, flexible-time authentication and source identity protection, our scheme does not have the threshold problem. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based algorithms under comparable security levels.
The major contributions of this paper are the following: 1. We develop a source anonymous message authentication code (SAMAC) on elliptic curves that can provide unconditional source anonymity. 2. We offer an efficient hop-by-hop message authentication mechanism for WSNs without the threshold limitation. 3. We devise network implementation criteria on source node privacy protection in WSNs. 4. We propose an efficient key management framework to ensure isolation of the compromised nodes. 5. We provide extensive simulation results under ns-2 and TelosB on multiple security levels. To the best of our knowledge, this is the first scheme that provides hop-by-hop node authentication without the threshold limitation, and has performance better than the symmetric-key based schemes.
The distributed nature of our algorithm makes the scheme suitable for decentralized networks. The remainder of this paper is organized as follows: Section 2 presents the terminology and the preliminary that will be used in this paper. Section 3 discusses the related work, with a focus on polynomial-based schemes. Section 4 describes the proposed source anonymous message authentication scheme on elliptic curves. Section 5 discusses the ambiguity set (AS) selection strategies for source privacy. Section 6 describes key management and compromised node detection. Performance analysis and simulation results are provided in Section 7. We conclude in Section 8. through multi-hop communications. We assume there is a security server (SS) that is responsible for generation, storage and distribution of the security parameters among the network.
This server will never be compromised. However, after deployment, the sensor nodes may be captured and compromised by attackers. Once compromised, all information stored in the sensor nodes can be accessed by the attackers. The compromised nodes can be reprogrammed and fully controlled by the attackers. However, the compromised nodes will not be able to create new public keys that can be accepted by the SS and other nodes. Based on the above assumptions, this paper considers two types of attacks launched by the adversaries: Passive attacks. Through passive attacks, the adversaries could eavesdrop on messages transmitted in the network and perform traffic analysis. Active attacks. Active attacks can only be launched from the compromised sensor nodes. Once the sensor nodes are compromised, the adversaries will obtain all the information stored in the compromised nodes, including the security parameters of the compromised nodes. The adversaries can modify the contents of the messages, and inject their own messages.
LITRATURE SURVEY:
ATTACKING CRYPTOGRAPHIC SCHEMES BASED ON ‘PERTURBATION POLYNOMIALS
AUTHOR: M. Albrecht, C. Gentry, S. Halevi, and J. Katz,
PUBLISH: Report 2009/098, http://eprint.iacr.org/, 2009.
We show attacks on several cryptographic schemes that have recently been proposed for achieving various security goals in sensor networks. Roughly speaking, these schemes all use “perturbation polynomials” to add “noise” to polynomial-based systems that oer information- theoretic security, in an attempt to increase the resilience threshold while maintaining eciency. We show that the heuristic security arguments given for these modified schemes do not hold, and that they can be completely broken once we allow even a slight extension of the parameters beyond those achieved by the underlying information-theoretic schemes. Our attacks apply to the key predistribution scheme of Zhang et al. (MobiHoc 2007), the access-control schemes of Subramanian et al. (PerCom 2007), and the authentication schemes of Zhang et al. (INFOCOM 2008).
CRYPTOGRAPHIC KEY LENGTH RECOMMENDATION
PUBLISH: http://www.keylength.com/en/3/, 2013.
In most
cryptographic functions, the key length is an important security parameter.
Both academic and private organizations provide recommendations and
mathematical formulas to approximate the minimum key size requirement for
security. Despite the availability of these publications, choosing an
appropriate key size to protect your system from attacks remains a headache as
you need to read and understand all these papers.
This web site implements mathematical formulas
and summarizes reports from well-known organizations allowing you to quickly
evaluate the minimum security requirements for your system. You can also easily
compare all these techniques and find the appropriate key length for your
desired level of protection. The lengths provided here are designed to resist
mathematic attacks; they do not take algorithmic attacks, hardware flaws, etc.
into account.
LIGHTWEIGHT AND COMPROMISE-RESILIENT MESSAGE AUTHENTICATION IN SENSOR NETWORKS
AUTHOR: W. Zhang, N. Subramanian, and G. WangProc.
PUBLISH: IEEE INFOCOM, Apr. 2008.
Numerous authentication schemes have been proposed in the past for protecting communication authenticity and integrity in wireless sensor networks. Most of them however have following limitations: high computation or communication overhead, no resilience to a large number of node compromises, delayed authentication, lack of scalability, etc. To address these issues, we propose in this paper a novel message authentication approach which adopts a perturbed polynomial-based technique to simultaneously accomplish the goals of lightweight, resilience to a large number of node compromises, immediate authentication, scalability, and non-repudiation. Extensive analysis and experiments have also been conducted to evaluate the scheme in terms of security properties and system overhead.
COMPARING SYMMETRIC-KEY AND PUBLIC-KEY BASED SECURITY SCHEMES IN SENSOR NETWORKS: A CASE STUDY OF USER ACCESS CONTROL
AUTHOR: H. Wang, S. Sheng, C. Tan, and Q.
PUBLISH: Li Proc. IEEE 28th Int’l Conf. Distributed Computing Systems (ICDCS), pp. 11-18, 2008.
While symmetric-key schemes are efficient in processing time for sensor networks, they generally require complicated key management, which may introduce large memory and communication overhead. On the contrary, public-key based schemes have simple and clean key management, but cost more computational time. The recent progress of elliptic curve cryptography (ECC) implementation on sensors motivates us to design a public-key scheme and compare its performance with the symmetric-key counterparts. This paper builds the user access control on commercial off-the-shelf sensor devices as a case study to show that the public-key scheme can be more advantageous in terms of the memory usage, message complexity, and security resilience. Meanwhile, our work also provides insights in integrating and designing public-key based security protocols for sensor networks.
CHAPTER 2
EXISTING SYSTEM:
DISADVANTAGES OF EXISTING SYSTEM:
PROPOSED SYSTEM:
ADVANTAGES OF PROPOSED SYSTEM:
HARDWARE REQUIREMENT:
CHAPTER 3
SYSTEM DESIGN:
Data Flow Diagram / Use Case Diagram / Flow Diagram:
External sources or destinations, which may be people or organizations or other entities
Here the data referenced by a process is stored and retrieved.
People, procedures or devices that produce data. The physical component is not identified.
Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.
There are several common modeling rules when creating DFDs:
ARCHITECTURE DIAGRAM:
DATAFLOW DIAGRAM:
UML DIAGRAMS:
USE CASE DIAGRAM:
Client
Server
CLASS DIAGRAM:
SEQUENCE DIAGRAM:
Files Transmitted
ECC Encrypted Data
SAMA Verification
Checking for key
Data Received
ACTIVITY DIAGRAM:
CHAPTER 4
4.0 IMPLEMENTATION:
Privacy is sometimes referred to as anonymity. Communication anonymity in information management has been discussed in a number of previous works in generally refers to the state of being unidentifiable within a set of subjects. This set is called the AS. Sender anonymity means that a particular message is not linkable to any sender, and no message is linkable to a particular sender. We will start with the definition of the unconditionally secure SAMA.
4.1 ALGORITHM:
4.3 MODULES:
SERVER CLIENT MODULE:
KEY MANAGEMENT AND NODE DETECTION
SYMMETRIC-KEY CRYPTOSYSTEM
PUBLIC-KEY CRYPTOSYSTEM
HOP-BY-HOP
AUTHENTICATION
4.4 MODULES DESCRIPTON:
SERVER CLIENT MODULE:
Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.
KEY MANAGEMENT AND NODE DETECTION:
Recently, message sender anonymity based on ring a signature was introduced in this approach enables the message sender to generate a source anonymous message signature with content authenticity assurance. To generate a ring signature, a ring member randomly selects an AS and forges a message signature for all other members. Then he uses his trap-door information to glue the ring together. The original scheme has very limited flexibility and very high complexity.
We focused on the cryptographic
algorithm public-key based approach, each message is transmitted along with the
digital signature of the message generated using the sender’s private key.
Every intermediate forwarder and the final receiver can authenticate the
message using the sender’s public key. The recent progress on ECC shows that
the public-key schemes can be more advantageous in terms of memory usage,
message complexity, and security resilience, since public-key based approaches
have a simple and clean key management.
SYMMETRIC-KEY CRYPTOSYSTEM:
Symmetric key and hash based authentication schemes were proposed for WSNs. In these schemes, each symmetric authentication key is shared by a group of sensor nodes. An intruder can compromise the key by capturing a single sensor node. Therefore, these schemes are not resilient to node compromise attacks. Another type of symmetric-key scheme requires synchronization among nodes. These schemes, including TESLA and its variants, can also provide message sender authentication. However, this scheme requires initial time synchronization, which is not easy to be implemented in large scale WSNs. In addition, they also introduce delay in message authentication, and the delay increases as the network scales up.
PUBLIC-KEY CRYPTOSYSTEM:
A secret polynomial based message authentication scheme was introduced in scheme offers information- theoretic security with ideas similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial. When the number of messages transmitted is below the threshold, the scheme enables the intermediate node to verify the authenticity of the message through polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. To increase the threshold and the complexity for the intruder to reconstruct the secret polynomial, a random noise, also called a perturbation factor, was added to the polynomial in to thwart the adversary from computing the coefficient of the polynomial.
However, the added perturbation factor can be completely removed using error-correcting code techniques for the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. The recent progress on ECC shows that the public-key schemes can be more advantageous in terms of memory usage, message complexity, and security resilience, since public-key based approaches have a simple and clean key management.
HOP-BY-HOP AUTHENTICATION:
Hop-by-hop authentication can be achieved through a public-key encryption system, the public-key based schemes were generally considered as not preferred, mainly due to their high computational overhead. However, our research demonstrates that it is not always true, especially for elliptic curve public-key cryptosystems.
In our scheme, each SAMA contains an AS of n randomly selected nodes that dynamically changes for each message. For n ¼ 1, our scheme can provide at least the same security as the bivariate polynomial-based scheme. For n > 1, we can provide extra source privacy benefits. Even if one message is corrupted, other messages transmitted in the network can still be secure.
Therefore, n can be much smaller than the parameters dx and dy. In fact, even a small n may provide adequate source privacy, while ensuring high system performance. In addition, in the bivariate polynomial-based scheme, there is only one base station that can send messages. All the other nodes can only act as intermediate nodes or receivers. This property makes the base station easy to attack, and severely narrows the applicability of this scheme. In fact, the major traffic inWSNs is packet delivery from the sensor nodes to the sink node.
Our scheme enables every node to transmit the message to the sink node as a message initiator.
The recent progress on ECC has
demonstrated that the public-key based schemes have more advantages in terms of
memory usage, message complexity, and security resilience, since public-key
based approaches have a simple and clean key management.
CHAPTER 5
5.0 SYSTEM STUDY:
5.1 FEASIBILITY STUDY:
The feasibility of the project is analyzed in this phase and business proposal is put forth with a very general plan for the project and some cost estimates. During system analysis the feasibility study of the proposed system is to be carried out. This is to ensure that the proposed system is not a burden to the company. For feasibility analysis, some understanding of the major requirements for the system is essential.
Three key considerations involved in the feasibility analysis are
5.1.1 ECONOMICAL FEASIBILITY:
This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.
This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.
5.1.3 SOCIAL FEASIBILITY:
The aspect of study is to check the level of
acceptance of the system by the user. This includes the process of training the
user to use the system efficiently. The user must not feel threatened by the
system, instead must accept it as a necessity. The level of acceptance by the
users solely depends on the methods that are employed to educate the user about
the system and to make him familiar with it. His level of confidence must be
raised so that he is also able to make some constructive criticism, which is
welcomed, as he is the final user of the system.
5.2 SYSTEM TESTING:
Testing is a process of checking whether the developed system is working according to the original objectives and requirements. It is a set of activities that can be planned in advance and conducted systematically. Testing is vital to the success of the system. System testing makes a logical assumption that if all the parts of the system are correct, the global will be successfully achieved. In adequate testing if not testing leads to errors that may not appear even many months. This creates two problems, the time lag between the cause and the appearance of the problem and the effect of the system errors on the files and records within the system. A small system error can conceivably explode into a much larger Problem. Effective testing early in the purpose translates directly into long term cost savings from a reduced number of errors. Another reason for system testing is its utility, as a user-oriented vehicle before implementation. The best programs are worthless if it produces the correct outputs.
5.2.1 UNIT TESTING:
A program represents the logical elements of a system. For a program to run satisfactorily, it must compile and test data correctly and tie in properly with other programs. Achieving an error free program is the responsibility of the programmer. Program testing checks for two types of errors: syntax and logical. Syntax error is a program statement that violates one or more rules of the language in which it is written. An improperly defined field dimension or omitted keywords are common syntax errors. These errors are shown through error message generated by the computer. For Logic errors the programmer must examine the output carefully.
UNIT TESTING:
| Description | Expected result |
| Test for application window properties. | All the properties of the windows are to be properly aligned and displayed. |
| Test for mouse operations. | All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions. |
5.1.3 FUNCTIONAL TESTING:
Functional testing of an application is used to prove the application delivers correct results, using enough inputs to give an adequate level of confidence that will work correctly for all sets of inputs. The functional testing will need to prove that the application works for each client type and that personalization function work correctly.When a program is tested, the actual output is compared with the expected output. When there is a discrepancy the sequence of instructions must be traced to determine the problem. The process is facilitated by breaking the program into self-contained portions, each of which can be checked at certain key points. The idea is to compare program values against desk-calculated values to isolate the problems.
FUNCTIONAL TESTING:
| Description | Expected result |
| Test for all modules. | All peers should communicate in the group. |
| Test for various peer in a distributed network framework as it display all users available in the group. | The result after execution should give the accurate result. |
5.1. 4 NON-FUNCTIONAL TESTING:
The Non Functional software testing encompasses a rich spectrum of testing strategies, describing the expected results for every test case. It uses symbolic analysis techniques. This testing used to check that an application will work in the operational environment. Non-functional testing includes:
5.1.5 LOAD TESTING:
An important tool for implementing system tests is a Load generator. A Load generator is essential for testing quality requirements such as performance and stress. A load can be a real load, that is, the system can be put under test to real usage by having actual telephone users connected to it. They will generate test input data for system test.
Load Testing
| Description | Expected result |
| It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received. | Should designate another active node as a Server. |
5.1.5 PERFORMANCE TESTING:
Performance tests are utilized in order to determine the widely defined performance of the software system such as execution time associated with various parts of the code, response time and device utilization. The intent of this testing is to identify weak points of the software system and quantify its shortcomings.
PERFORMANCE TESTING:
| Description | Expected result |
| This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management. | Should handle large input values, and produce accurate result in a expected time. |
5.1.6 RELIABILITY TESTING:
The software reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time and it is being ensured in this testing. Reliability can be expressed as the ability of the software to reveal defects under testing conditions, according to the specified requirements. It the portability that a software system will operate without failure under given conditions for a given time interval and it focuses on the behavior of the software element. It forms a part of the software quality control team.
RELIABILITY TESTING:
| Description | Expected result |
| This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application. | In case of failure of the server an alternate server should take over the job. |
5.1.7 SECURITY TESTING:
Security
testing evaluates system characteristics that relate to the availability,
integrity and confidentiality of the system data and services. Users/Clients
should be encouraged to make sure their security needs are very clearly known
at requirements time, so that the security issues can be addressed by the
designers and testers.
SECURITY TESTING:
| Description | Expected result |
| Checking that the user identification is authenticated. | In case failure it should not be connected in the framework. |
| Check whether group keys in a tree are shared by all peers. | The peers should know group key in the same group. |
5.1.7 WHITE BOX TESTING:
White box
testing, sometimes called glass-box
testing is a test case
design method that uses
the control structure
of the procedural design to
derive test cases. Using
white box testing
method, the software engineer
can derive test
cases. The White box testing focuses on the inner structure of the
software structure to be tested.
5.1.8 WHITE BOX TESTING:
| Description | Expected result |
| Exercise all logical decisions on their true and false sides. | All the logical decisions must be valid. |
| Execute all loops at their boundaries and within their operational bounds. | All the loops must be finite. |
| Exercise internal data structures to ensure their validity. | All the data structures must be valid. |
5.1.9 BLACK BOX TESTING:
Black box
testing, also called behavioral testing, focuses on the functional requirements
of the software. That is,
black testing enables
the software engineer to derive
sets of input
conditions that will
fully exercise all
functional requirements for a
program. Black box testing is not
alternative to white box techniques.
Rather it is
a complementary approach
that is likely
to uncover a different
class of errors
than white box methods. Black box testing attempts to find
errors which focuses on inputs, outputs, and principle function of a software
module. The starting point of the black box testing is either a specification
or code. The contents of the box are hidden and the stimulated software should
produce the desired results.
5.1.10 BLACK BOX TESTING:
| Description | Expected result |
| To check for incorrect or missing functions. | All the functions must be valid. |
| To check for interface errors. | The entire interface must function normally. |
| To check for errors in a data structures or external data base access. | The database updation and retrieval must be done. |
| To check for initialization and termination errors. | All the functions and data structures must be initialized properly and terminated normally. |
All
the above system testing strategies are carried out in as the development,
documentation and institutionalization of the proposed goals and related
policies is essential.
CHAPTER 6
6.0 SOFTWARE DESCRIPTION:
Java technology is both a programming language and a platform.
With most programming languages, you either compile or interpret a program so that you can run it on your computer. The Java programming language is unusual in that a program is both compiled and interpreted. With the compiler, first you translate a program into an intermediate language called Java byte codes —the platform-independent codes interpreted by the interpreter on the Java platform. The interpreter parses and runs each Java byte code instruction on the computer. Compilation happens just once; interpretation occurs each time the program is executed. The following figure illustrates how this works.
You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether it’s a development tool or a Web browser that can run applets, is an implementation of the Java VM. Java byte codes help make “write once, run anywhere” possible. You can compile your program into byte codes on any platform that has a Java compiler. The byte codes can then be run on any implementation of the Java VM. That means that as long as a computer has a Java VM, the same program written in the Java programming language can run on Windows 2000, a Solaris workstation, or on an iMac.
A platform is the hardware or software environment in which a program runs. We’ve already mentioned some of the most popular platforms like Windows 2000, Linux, Solaris, and MacOS. Most platforms can be described as a combination of the operating system and hardware. The Java platform differs from most other platforms in that it’s a software-only platform that runs on top of other hardware-based platforms.
The Java platform has two components:
You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.
The Java API is a large collection of ready-made software components that provide many useful capabilities, such as graphical user interface (GUI) widgets. The Java API is grouped into libraries of related classes and interfaces; these libraries are known as packages. The next section, What Can Java Technology Do? Highlights what functionality some of the packages in the Java API provide.
The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.
Native code is code that after you compile it, the compiled code runs on a specific hardware platform. As a platform-independent environment, the Java platform can be a bit slower than native code. However, smart compilers, well-tuned interpreters, and just-in-time byte code compilers can bring performance close to that of native code without threatening portability.
The most common types of programs written in the Java programming language are applets and applications. If you’ve surfed the Web, you’re probably already familiar with applets. An applet is a program that adheres to certain conventions that allow it to run within a Java-enabled browser.
However, the Java programming language is not just for writing cute, entertaining applets for the Web. The general-purpose, high-level Java programming language is also a powerful software platform. Using the generous API, you can write many types of programs.
An application is a standalone program that runs directly on the Java platform. A special kind of application known as a server serves and supports clients on a network. Examples of servers are Web servers, proxy servers, mail servers, and print servers. Another specialized program is a servlet.
A servlet can almost be thought of as an applet that runs on the server side. Java Servlets are a popular choice for building interactive web applications, replacing the use of CGI scripts. Servlets are similar to applets in that they are runtime extensions of applications. Instead of working in browsers, though, servlets run within Java Web servers, configuring or tailoring the server.
How does the API support all these kinds of programs? It does so with packages of software components that provides a wide range of functionality. Every full implementation of the Java platform gives you the following features:
The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.
We can’t promise you fame, fortune, or even a job if you learn the Java programming language. Still, it is likely to make your programs better and requires less effort than other languages. We believe that Java technology will help you do the following:
Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.
Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.
The ODBC system files are not installed on your system by Windows 95. Rather, they are installed when you setup a separate database application, such as SQL Server Client or Visual Basic 4.0. When the ODBC icon is installed in Control Panel, it uses a file called ODBCINST.DLL. It is also possible to administer your ODBC data sources through a stand-alone program called ODBCADM.EXE. There is a 16-bit and a 32-bit version of this program and each maintains a separate list of ODBC data sources.
From a programming perspective, the beauty of ODBC is that the application can be written to use the same set of function calls to interface with any data source, regardless of the database vendor. The source code of the application doesn’t change whether it talks to Oracle or SQL Server. We only mention these two as an example. There are ODBC drivers available for several dozen popular database systems. Even Excel spreadsheets and plain text files can be turned into data sources. The operating system uses the Registry information written by ODBC Administrator to determine which low-level ODBC drivers are needed to talk to the data source (such as the interface to Oracle or SQL Server). The loading of the ODBC drivers is transparent to the ODBC application program. In a client/server environment, the ODBC API even handles many of the network issues for the application programmer.
The advantages of this scheme are so numerous
that you are probably thinking there must be some catch. The only disadvantage
of ODBC is that it isn’t as efficient as talking directly to the native
database interface. ODBC has had many detractors make the charge that it is too
slow. Microsoft has always claimed that the critical factor in performance is
the quality of the driver software that is used. In our humble opinion, this is
true. The availability of good ODBC drivers has improved a great deal recently.
And anyway, the criticism about performance is somewhat analogous to those who
said that compilers would never match the speed of pure assembly language.
Maybe not, but the compiler (or ODBC) gives you the opportunity to write
cleaner programs, which means you finish sooner. Meanwhile, computers get
faster every year.
6.6 JDBC:
In an effort to set an independent database standard API for Java; Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of “plug-in” database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.
To gain a wider acceptance of JDBC, Sun based JDBC’s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.
JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.
The remainder of this section will cover enough information about JDBC for you to know what it is about and how to use it effectively. This is by no means a complete overview of JDBC. That would fill an entire book.
Few software packages are designed without goals in mind. JDBC is one that, because of its many goals, drove the development of the API. These goals, in conjunction with early reviewer feedback, have finalized the JDBC class library into a solid framework for building database applications in Java.
The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:
SQL Level API
The designers felt that their main goal was to define a SQL interface for Java. Although not the lowest database interface level possible, it is at a low enough level for higher-level tools and APIs to be created. Conversely, it is at a high enough level for application programmers to use it confidently. Attaining this goal allows for future tool vendors to “generate” JDBC code and to hide many of JDBC’s complexities from the end user.
SQL Conformance
SQL syntax varies as you move from database vendor to database vendor. In an effort to support a wide variety of vendors, JDBC will allow any query statement to be passed through it to the underlying database driver. This allows the connectivity module to handle non-standard functionality in a manner that is suitable for its users.
JDBC must be implemental on top of common database interfaces
The JDBC SQL API must “sit” on top of other common SQL level APIs. This goal allows JDBC to use existing ODBC level drivers by the use of a software interface. This interface would translate JDBC calls to ODBC and vice versa.
Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.
This goal probably appears in all software design goal listings. JDBC is no exception. Sun felt that the design of JDBC should be very simple, allowing for only one method of completing a task per mechanism. Allowing duplicate functionality only serves to confuse the users of the API.
Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.
Because more often than not, the usual SQL calls
used by the programmer are simple SELECT’s,
INSERT’s,
DELETE’s
and UPDATE’s,
these queries should be simple to perform with JDBC. However, more complex SQL
statements should also be possible.
Finally we decided to precede the implementation using Java Networking.
And for dynamically updating the cache table we go for MS Access database.
Java ha two things: a programming language and a platform.
Java is a high-level programming language that is all of the following
Simple Architecture-neutral
Object-oriented Portable
Distributed High-performance
Interpreted Multithreaded
Robust Dynamic Secure
Java is also unusual in that each Java program is both compiled and interpreted. With a compile you translate a Java program into an intermediate language called Java byte codes the platform-independent code instruction is passed and run on the computer.
Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.
The TCP/IP stack is shorter than the OSI one:
TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.
The IP layer provides a connectionless and unreliable delivery system. It considers each datagram independently of the others. Any association between datagram must be supplied by the higher layers. The IP layer supplies a checksum that includes its own header. The header includes the source and destination addresses. The IP layer handles routing through an Internet. It is also responsible for breaking up large datagram into smaller ones for transmission and reassembling them at the other end.
UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.
TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.
In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.
Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.
Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.
8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.
The 32 bit address is usually written as 4 integers separated by dots.
A service exists on a host, and is identified by its port. This is a 16 bit number. To send a message to a server, you send it to the port for that service of the host that it is running on. This is not location transparency! Certain of these ports are “well known”.
A
socket is a data structure maintained by the system to handle network
connections. A socket is created using the call socket. It returns an integer that is
like a file descriptor. In fact, under Windows, this handle can be used with Read File and Write File functions.
#include <sys/types.h>
#include <sys/socket.h>
int socket(int family, int type, int protocol);
Here
“family” will be AF_INET for IP communications, protocol will be zero,
and type
will depend on whether TCP or UDP is used. Two processes wishing to communicate
over a network create a socket each. These are similar to two ends of a pipe – but
the actual pipe does not yet exist.
6.8 JFREE CHART:
JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:
A consistent and well-documented API, supporting a wide range of chart types;
A flexible design that is easy to extend, and targets both server-side and client-side applications;
Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);
JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.
Charts showing values that relate to geographical areas. Some examples include: (a) population density in each state of the United States, (b) income per capita for each country in Europe, (c) life expectancy in each country of the world. The tasks in this project include: Sourcing freely redistributable vector outlines for the countries of the world, states/provinces in particular countries (USA in particular, but also other areas);
Creating an appropriate dataset interface (plus
default implementation), a rendered, and integrating this with the existing
XYPlot class in JFreeChart; Testing, documenting, testing some more,
documenting some more.
Implement a new (to JFreeChart) feature for interactive time series charts — to display a separate control that shows a small version of ALL the time series data, with a sliding “view” rectangle that allows you to select the subset of the time series data to display in the main chart.
There is currently a lot of interest in dashboard displays. Create a flexible dashboard mechanism that supports a subset of JFreeChart chart types (dials, pies, thermometers, bars, and lines/time series) that can be delivered easily via both Java Web Start and an applet.
The property editor mechanism in JFreeChart only
handles a small subset of the properties that can be set for charts. Extend (or
reimplement) this mechanism to provide greater end-user control over the
appearance of the charts.
CHAPTER 7
APPENDIX
7.1 SAMPLE SOURCE CODE
7.2
SAMPLE OUTPUT
CHAPTER 8
8.1 CONCLUSION:
In this paper, we first proposed a novel and efficient SAMA based on ECC. While ensuring message sender privacy, SAMA can be applied to any message to provide message content authenticity. To provide hop-by-hop message authentication without the weakness of the builtin threshold of the polynomial-based scheme, we then proposed a hop-by-hop message authentication scheme based on the SAMA. When applied to WSNs with fixed sink nodes, we also discussed possible techniques for compromised node identification.
We compared our proposed scheme with the
bivariate polynomial-based scheme through simulations using ns-2 and TelosB.
Both theoretical and simulation results show that, in comparable scenarios, our
proposed scheme is more efficient than the bivariate polynomial-based scheme in
terms of computational overhead, energy consumption, delivery ratio, message
delay, and memory consumption.
CHAPTER 9
REFERENCE:
[1] M. Albrecht, C. Gentry, S. Halevi, and J. Katz, “Attacking Cryptographic Schemes Based on ‘Perturbation Polynomials’,” Report 2009/098, http://eprint.iacr.org/, 2009.
[2] “Cryptographic Key Length Recommendation,” http://www.keylength.com/en/3/, 2013.
[3] W. Zhang, N. Subramanian, and G. Wang, “Lightweight and Compromise-Resilient Message Authentication in Sensor Networks,” Proc. IEEE INFOCOM, Apr. 2008.
[4] H. Wang, S. Sheng, C. Tan, and Q. Li, “Comparing Symmetric-Key and Public-Key Based Security Schemes in Sensor Networks: A Case Study of User Access Control,” Proc. IEEE 28th Int’l Conf. Distributed Computing Systems (ICDCS), pp. 11-18, 2008.
[5] Q. Liu, Y. Ge, Z. Li, H. Xiong, and E. Chen, “Personalized Travel Package Recommendation,” Proc. IEEE 11th Int’l Conf. Data Mining (ICDM ’11), pp. 407-416, 2011.
[6] Q. Liu, E. Chen, H. Xiong, C. Ding, and J. Chen, “Enhancing Collaborative Filtering by User Interests Expansion via Personalized Ranking,” IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 42, no. 1, pp. 218-233, Feb. 2012.