In this paper proposes Searchable Public-Key Ciphertexts with Hidden Structures (SPCHS) for keyword search as fast as possible without sacrificing semantic security of the encrypted keywords. In SPCHS, all keyword-searchable ciphertexts are structured by hidden relations, and with the search trapdoor corresponding to a keyword, the minimum information of the relations is disclosed to a search algorithm as the guidance to find all matching ciphertexts efficiently.
We construct a SPCHS scheme from scratch in which the ciphertexts have a hidden star-like structure. We prove our scheme to be semantically secure in the Random Oracle (RO) model. The search complexity of our scheme is dependent on the actual number of the ciphertexts containing the queried keyword, rather than the number of all ciphertexts.
Finally, we present a generic SPCHS
construction from anonymous identity-based encryption and collision-free
full-identity malleable Identity-Based Key Encapsulation Mechanism (IBKEM) with
anonymity. We illustrate two collision-free full-identity malleable IBKEM
instances, which are semantically secure and anonymous, respectively, in the RO
and standard models. The latter instance enables us to construct an SPCHS
scheme with semantic security in the standard model.
1.2 INTRODUCTION:
We start by formally defining the concept of Searchable Public-key Ciphertexts with Hidden Structures (SPCHS) and its semantic security. In this new concept, keywordsearchable ciphertexts with their hidden structures can be generated in the public key setting; with a keyword search trapdoor, partial relations can be disclosed to guide the discovery of all matching ciphertexts. Semantic security is defined for both the keywords and the hidden structures. It is worth noting that this new concept and its semantic security are suitable for keyword-searchable ciphertexts with any kind of hidden structures. In contrast, the concept of traditional PEKS does not contain any hidden structure among the PEKS ciphertexts; correspondingly, its semantic security is only defined for the keywords. Following the SPCHS definition, we construct a simple SPCHS from scratch in the random oracle (RO) model. The scheme generates keyword-searchable ciphertexts with a hidden star-like structure. The search performance mainly depends on the actual number of the ciphertexts containing the queried keyword. For security, the scheme is proven semantically secure based on the Decisional Bilinear DiffieHellman (DBDH) assumption in the RO model.
We build a generic SPCHS construction
with IdentityBased Encryption (IBE) and collision-free full-identity malleable
IBKEM. The resulting SPCHS can generate keyword-searchable ciphertexts with a
hidden star-like structure. Moreover, if both the underlying IBKEM and IBE have
semantic security and anonymity (i.e. the privacy of receivers’ identities),
the resulting SPCHS is semantically secure. As there are known IBE schemes [4],
[5], [6], [7] in both the RO model and the standard model, an SPCHS
construction is reduced to collision-free full-identity malleable IBKEM with
anonymity. We proposed several IBKEM schemes to construct Verifiable Random
Functions2 (VRF). We show that one of these IBKEM schemes is anonymous and
collision-free fullidentity malleable in the RO model. We transform this IBE
scheme into a collision-free full-identity malleable IBKEM scheme with semantic
security and anonymity in the standard model. Hence, this new IBKEM scheme
allows us to build SPCHS schemes secure in the standard model with the same
search performance as the previous SPCHS construction from scratch in the RO
model.
1.3 LITRATURE SURVEY
TITLE: FUZZY KEYWORD SEARCH OVER ENCRYPTED DATA IN CLOUD COMPUTING
AUTOHR: Li J., Wang Q., Wang C., Cao N., Ren K., Lou W
PUBLISH: IEEE INFOCOM 2010, pp. 1-5. (2010)
EXPLANATION:
As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. That is, there is no tolerance of minor typos and format inconsistencies which, on the other hand, are typical user searching behavior and happen very frequently. This significant drawback makes existing techniques unsuitable in Cloud Computing as it greatly affects system usability, rendering user searching experiences very frustrating and system efficacy very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop an advanced technique on constructing fuzzy keyword sets, which greatly reduces the storage and representation overheads. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search.
TITLE: ANONYMOUS FUZZY IDENTITY-BASED ENCRYPTION FOR SIMILARITY SEARCH
AUTOHR: Cheung D. W., Mamoulis N., Wong W. K., Yiu S. M., Zhang
PUBLISH: ISAAC 2010. LNCS, vol. 6505, pp. 61-72. Springer, Heidelberg (2010)
EXPLANATION:
The predicate that was studied in the very beginning is “exact keyword matching”. That is, whether the value hidden by the token is equal to the attribute value hidden in the ciphertext. Schemes that only provide data item security are basically “Identity-Based Encryption”. Schemes protecting both the data item and the attributes were initiated in the private-key setting public-key setting. Relationship between and “Anonymous Identity-Based Encryption” was revisited in range query as the predicate was also considered. Boneh et al. devised an Augmented Broadcast Encryption which allows checking if the attribute value falls within a range on encrypted data. Their scheme also provides attribute protection. Then, Boneh and Waters extended it to multi-dimensional range query.
However, there is no practical scheme supporting this predicate with attribute protection in public-key settings investigated this problem in the private-key setting and is IND2-CKA secure. His scheme is in a public-key setting. However, the scheme requires the threshold value t to be fixed in the setup time. Our work is using as a framework provided schemes for handling predicates represented as inner products. Their formulation of using inner products with bounded disjunction is powerful. We show how to reduce inner products to hamming distance similarity comparison predicate, and then derive a slightly different encryption scheme for better performance when considering the inequality case. In our work, we consider the problem of attribute protection in public-key setting. In some applications, people may also want to provide protection to predicate (“the token”), which is inherently unachievable in public-key setting. Note that a predicate encryption supporting inner product in private-key setting has been devised in which can provide predicate privacy
TITLE: TRAPDOOR PRIVACY IN ASYMMETRIC SEARCHABLE ENCRYPTION SCHEMES
AUTOHR: Arriaga A., Tang Q., Ryan P
PUBLISH: AFRICACRYPT 2014. LNCS, vol. 8469, pp. 31-50. Springer, Heidelberg (2014)
EXPLANATION:
Asymmetric searchable encryption allows searches to
be carried over ciphertexts, through delegation, and by means of trapdoors
issued by the owner of the data. Public Key Encryption with Keyword Search
(PEKS) is a primitive with such functionality that provides delegation of
exact-match searches. As it is important that ciphertexts preserve data
privacy, it is also important that trapdoors do not expose the user’s search
criteria. The difficulty of formalizing a security model for trapdoor privacy
lies in the verification functionality, which gives the adversary the power of
verifying if a trapdoor encodes a particular keyword. In this paper, we provide
a broader view on what can be achieved regarding trapdoor privacy in asymmetric
searchable encryption schemes, and bridge the gap between previous definitions,
which give limited privacy guarantees in practice against search patterns. We
propose the notion of Strong Search Pattern Privacy for PEKS and construct a
scheme that achieves this security notion.
CHAPTER 2
2.0 SYSTEM ANALYSIS
2.1 EXISTING SYSTEM:
Existing semantically secure PEKS schemes take search time linear with the total number of all ciphertexts. This makes retrieval from large-scale databases prohibitive. Therefore, more efficient search performance is crucial for practically deploying PEKS schemes. One of the prominent works to accelerate the search over encrypted keywords in the public-key setting enabling search over encrypted keywords to be as effi- cient as the search for unencrypted keywords, such that a ciphertext containing a given keyword can be retrieved in time complexity logarithmic in the total number of all ciphertexts.
This is reasonable because the encrypted keywords can form a tree-like structure when stored according to their binary values. However, deterministic encryption has two inherent limitations. First, keyword privacy can be guaranteed only for keywords that are a priori hardto-guess by the adversary (i.e., keywords with high minentropy to the adversary); second, certain information of a message leaks inevitably via the ciphertext of the keywords since the encryption is deterministic. Hence, deterministic encryption is only applicable in special scenarios.
Observe that a keyword space is usually
of no high minentropy in many scenarios. Semantic security is crucial to
guarantee keyword privacy in such applications. Thus the linear search
complexity of existing schemes is the major obstacle to their adoption.
Unfortunately, the linear complexity seems to be inevitable because the server
has to scan and test each ciphertext, due to the fact that these ciphertexts
(corresponding to the same keyword or not) are indistinguishable to the server.
2.1.1 DISADVANTAGES:
Each sender should be able to generate the keyword-searchable ciphertexts with the hidden star-like structure by the receiver’s public-key; the server having a keyword search trapdoor should be able to disclose partial relations, which is related to all matching ciphertexts. Semantic security is preserved 1) if no keyword search trapdoor is known, all ciphertexts are indistinguishable, and no information is leaked about the structure, and 2) given a keyword search trapdoor, only the corresponding relations can be disclosed, and the matching ciphertexts leak no information about the rest of ciphertexts, except the fact that the rest do not contain the queried keyword.
2.2 PROPOSED SYSTEM:
We propose methods of searchable Public-key Ciphertexts with Hidden Structures (SPCHS) and its semantic security. In this new concept, keywordsearchable ciphertexts with their hidden structures can be generated in the public key setting; with a keyword search trapdoor, partial relations can be disclosed to guide the discovery of all matching ciphertexts. Semantic security is defined for both the keywords and the hidden structures. Following the SPCHS definition, we construct a simple SPCHS from scratch in the random oracle (RO) model. The scheme generates keyword-searchable ciphertexts with a hidden star-like structure. The search performance mainly depends on the actual number of the ciphertexts containing the queried keyword.
We are also interested in providing a
generic SPCHS construction to generate keyword-searchable ciphertexts with a
hidden star-like structure. Our generic SPCHS is inspired by several
interesting observations on Identity-Based Key Encapsulation Mechanism (IBKEM).
We build a generic SPCHS construction with IdentityBased Encryption (IBE) and
collision-free full-identity malleable IBKEM. The resulting SPCHS can generate
keyword-searchable ciphertexts with a hidden star-like structure. Moreover, if
both the underlying IBKEM and IBE have semantic security and anonymity (i.e.
the privacy of receivers’ identities), the resulting SPCHS is semantically
secure. As there are known IBE schemes in both the RO model and the standard
model, an SPCHS construction is reduced to collision-free full-identity
malleable IBKEM.
2.2.1 ADVANTAGES:
IBKEM schemes to construct Verifiable Random Functions2 (VRF) [8]. We show that one of these IBKEM schemes is anonymous and collision-free fullidentity malleable in the RO model utilized the “approximation” of multilinear maps to construct a standard-model version of Boneh-and-Franklin (BF) IBE scheme.
We transform this IBE scheme into a collision-free full-identity malleable IBKEM scheme with semantic security and anonymity in the standard model. Hence, this new IBKEM scheme allows us to build SPCHS schemes secure in the standard model with the same search performance as the previous SPCHS construction from scratch in the RO model.
2.3.1 HARDWARE REQUIREMENT:
CHAPTER 3
3.0 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’s in 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.
MODELING RULES:
There are several common modeling rules when creating DFDs:
3.1 ARCHITECTURE DIAGRAM
3.2 DATAFLOW DIAGRAM
LEVEL I:
LEVEL II:
UML DIAGRAMS:
3.2 USE CASE DIAGRAM:
3.3 CLASS DIAGRAM:
3.4 SEQUENCE DIAGRAM:
3.5 ACTIVITY DIAGRAM:
CHAPTER 4
4.0 IMPLEMENTATION:
SPCHS SCHEME:
We first explain intuitions behind SPCHS. We describe a hidden structure formed by ciphertexts as (C, Pri, Pub), where C denotes the set of all ciphertexts, Pri denotes the hidden relations among C, and Pub denotes the public parts. In case there is more than one hidden structure formed by ciphertexts, the description of multiple hidden structures formed by ciphertexts can be
In SPCHS, the encryption algorithm has two functionalities. One is to encrypt a keyword, and the other is to generate a hidden relation, which can associate the generated ciphertext to the hidden structure. Let (Pri, Pub) be the hidden structure. The encryption algorithm must take Pri as input, otherwise the hidden relation cannot be generated since Pub does not contain anything about the hidden relations. At the end of the encryption procedure, the Pri should be updated since a hidden relation is newly generated (but the specific method to update Pri relies on the specific instance of SPCHS). In addition, SPCHS needs an algorithm to initialize (Pri, Pub) by taking the master public key as input, and this algorithm will be run before the first time to generate a ciphertext. With a keyword search trapdoor, the search algorithm of SPCHS can disclose partial relations to guide the discovery of the ciphertexts containing the queried keyword with the hidden structure.
4.1 ALGORITHM
IBKEM ALGORITHM:
In this section, we formalize collision-free full-identity malleable IBKEM and a generic SPCHS construction from IBKEM. Our generic construction also relies on a notion of collision-free full-identity malleable IBKEM. The following IBKEM definition is derived from [47]. A difference only appears in algorithm EncapsIBKEM. In order to highlight that the generator of an IBKEM encapsulation knows the chosen random value used in algorithm EncapsIBKEM, we take the random value as an input of the algorithm.
The collision-free full-identity malleable IBKEM implies the following characteristics: all identities’ decryption keys can decapsulate the same encapsulation; all decapsulated keys are collision-free; the generator of the encapsulation can also compute these decapsulated keys; the decapsulated keys of different encapsulations are also collision-free.
A
collision-free full-identity malleable IBKEM scheme may preserve semantic
security and anonymity. We incorporate the semantic security and anonymity into
AnonSS-ID-CPA secure IBKEM. But this security is different from the traditional
version [47] of the Anon-SS-ID-CPA security due to the full-identity
malleability of IBKEM.
4.2 MODULES:
USER MODULES:
IDENTITY BASED ENCRYPTION:
FAST SEARCHABLE ENCRYPTION:
SEMANTIC
DATA SECURITY:
4.3 MODULE DESCRIPTION:
USER MODULE:
In this module is used to help the server to view details and upload files with the security. Admin upload the data’s to database. Also view the subscriber details and user details. Admin find the redistribute details. Also who send the data and receive the data’s. Data owner store large amount of data to clouds and access data using secure key provided admin after encrypting data’s. Encrypt the data using SECY. User store data after auditor, view and verifying data and also changed data. User again views data at that time admin provided the message to user only changes data.
In this module subscriber choose document and download the data’s from service providers. Subscribers pay the amount to service provider. Service provider provides that data key to subscriber. So subscribers download the data using data key. A cloud computing service provider serves users’ service requests by using a server system, which is constructed and maintained by an infrastructure vendor and rented by the service provider.
In this module, Users are having authentication and security to access the detail which is presented in the ontology system. Before accessing or searching the details user should have the account in that otherwise they should register first user can register their details like user name, password, email, mobile no, and then. We develop this module, where the cloud storage can be made secure.
IDENTITY BASED ENCRYPTION:
Batch identity-based key distribution: A direct application of collision-free full-identity malleable IBKEM is to achieve batch identity-based key distribution. In such an application, a sender would like to distribute different secret session keys to multiple receivers so that each receiver can only know the session key to himself/herself. With collision-free full-identity malleable IBKEM, a sender just needs to broadcast an IBKEM encapsulation in the identitybased cryptography setting, e.g., encapsulating a session key K to a single user ID. According to the collisionfreeness of IBKEM, each receiver ID0 can decapsulate and obtain a different key K0 with his/her secret key in the identity based crypto-system. Due to the full-identity malleability, the sender knows the decapsulated keys of all the receivers.
Anonymous identity-based broadcast
encryption: A slightly more complicated application is anonymous identity-based
broadcast encryption with efficient decryption. An analogous application was
proposed respectively application will work if the IBKEM is collision-free
full-identity malleable. It preserves the anonymity of receivers if the IBKEM
is anonymous. Note that trivial anonymous broadcast encryption suffers
decryption cost linear with the number of the receivers. In contrast, our
anonymous identity-based broadcast encryption enjoys constant decryption cost,
plus logarithmic complexity to search the matching index in a set (K1 1 , …,
KN 1 ) organized by a certain partial order, e.g., a dictionary order according
to their binary representations.
FAST SEARCHABLE ENCRYPTION:
As-fast-as-possible search in PEKS with semantic security. We proposed the concept of SPCHS as a variant of PEKS. The new concept allows keyword-searchable ciphertexts to be generated with a hidden structure. Given a keyword search trapdoor, the search algorithm of SPCHS can disclose part of this hidden structure for guidance on finding out the ciphertexts of the queried keyword. Semantic security of SPCHS captures the privacy of the keywords and the invisibility of the hidden structures. We proposed an SPCHS scheme from scratch with semantic security in the RO model. The scheme generates keyword-searchable ciphertexts with a hidden star-like structure. It has search complexity mainly linear with the exact number of the ciphertexts containing the queried keyword. It outperforms existing PEKS schemes with semantic security, whose search complexity is linear with the number of all ciphertexts.
We identified several interesting properties, i.e., collision-freeness and full-identity malleability in some IBKEM instances, and formalized these properties to build a generic SPCHS construction. We illustrated two collision-free full-identity malleable IBKEM instances, which are respectively secure in the RO and standard models. SPCHS seems a promising tool to solve some challenging problems in public-key searchable encryption. One application may be to achieve retrieval completeness verification which, to the best of our knowledge, has not been achieved in existing PEKS schemes. Specifically, by forming a hidden ring-like structure, i.e., letting the last hidden pointer always point to the head, one can obtain PEKS allowing to check the completeness of the retrieved ciphertexts by checking whether the pointers of the returned ciphertexts form a ring.
SEMANTIC DATA SECURITY:
The SS-CKSA security of the above SPCHS scheme relies on the DBDH assumption in Even in the case that a sender gets his local privacy Pri compromised, SPCHS still offers forward security. This means that the existing hidden structure of ciphertexts stays confidential, since the local privacy only contains the relationship of the new generated ciphertexts. To offer backward security with SPCHS, the sender can initialize a new structure by algorithm Structure Initialization for the new generated ciphertexts. A collision-free full-identity malleable IBKEM scheme may preserve semantic security and anonymity.
We incorporate the semantic security and anonymity into AnonSS-ID-CPA secure IBKEM. But this security is different from the traditional version of the Anon-SS-ID-CPA security due to the full-identity malleability of IBKEM. The difference will be introduced after defining that security. In that security, a PPT adversary is allowed to query the decryption keys for adaptively chosen identities, and adaptively choose two challenge identities. The Anon-SSID-CPA security of IBKEM means that for a challenge key-and-encapsulation pair, the adversary cannot determine the correctness of this pair and the challenge identity of this pair, given that the adversary does not know the two challenging identities’ decryption keys in the Anon-SSID-CPA security of a collision-free full-identity malleable IBKEM scheme.
The SS-sK-CKSA security of the above generic SPCHS construction relies on the AnonSS-sID-CPA security of the underlying IBKEM and the Anon-SS-ID-CPA security of the underlying IBE. In the security proof, we prove that if there is an adversary who can break the SS-sK-CKSA security of the above generic SPCHS construction, then there is another adversary who can break the Anon-SS-sID-CPA security of the underlying IBKEM or the Anon-SS-ID-CPA security of the underlying IBE.
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:
| 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. |
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.
5.1.2 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.
| 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. 3 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:
5.1.4 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.
| 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.
| 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.
| 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.
| 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. |
5.1.8 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.
| 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.
| 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
7.0 APPENDIX
7.1 SAMPLE SCREEN SHOTS:
7.2
SAMPLE SOURCE CODE:
CHAPTER 8
8.1 CONCLUSION
This paper investigated as-fast-as-possible search in PEKS with semantic security. We proposed the concept of SPCHS as a variant of PEKS. The new concept allows keyword-searchable ciphertexts to be generated with a hidden structure. Given a keyword search trapdoor, the search algorithm of SPCHS can disclose part of this hidden structure for guidance on finding out the ciphertexts of the queried keyword. Semantic security of SPCHS captures the privacy of the keywords and the invisibility of the hidden structures. We proposed an SPCHS scheme from scratch with semantic security in the RO model. The scheme generates keyword-searchable ciphertexts with a hidden star-like structure. It has search complexity mainly linear with the exact number of the ciphertexts containing the queried keyword. It outperforms existing PEKS schemes with semantic security, whose search complexity is linear with the number of all ciphertexts.
We identified several interesting
properties, i.e., collision-freeness and full-identity malleability in some
IBKEM instances, and formalized these properties to build a generic SPCHS
construction. We illustrated two collision-free full-identity malleable IBKEM
instances, which are respectively secure in the RO and standard models. SPCHS
seems a promising tool to solve some challenging problems in public-key
searchable encryption. One application may be to achieve retrieval completeness
verification which, to the best of our knowledge, has not been achieved in
existing PEKS schemes. Specifically, by forming a hidden ring-like structure,
i.e., letting the last hidden pointer always point to the head, one can obtain
PEKS allowing to check the completeness of the retrieved ciphertexts by
checking whether the pointers of the returned ciphertexts form a ring.