The Distributed m-healthcare cloud computing system considerably facilitates secure and efficient patient treatment for medical consultation by sharing personal health information among the healthcare providers. This system should bring about the challenge of keeping both the data confidentiality and patients’ identity privacy simultaneously. Many existing access control and anonymous authentication schemes cannot be straightforwardly exploited. To solve the problem proposed a novel authorized accessible privacy model (AAPM) is established. Patients can authorize physicians by setting an access tree supporting flexible threshold predicates.

Our new technique of attribute based designated verifier signature, a patient self-controllable multi-level privacy preserving cooperative authentication scheme (PSMPA) realizing three levels of security and privacy requirement in distributed m-healthcare cloud computing system is proposed. The directly authorized physicians, the indirectly authorized physicians and the unauthorized persons in medical consultation can respectively decipher the personal health information and/or verify patients’ identities by satisfying the access tree with their own attribute sets.

1.2 INTRODUCTION:

Distributed m-healthcare cloud computing systems have been increasingly adopted worldwide including the European Commission activities, the US Health Insurance Portability and Accountability Act (HIPAA) and many other governments for efficient and high-quality medical treatment. In m-healthcare social networks, the personal health information is always shared among the patients located in respective social communities suffering from the same disease for mutual support, and across distributed healthcare providers (HPs) equipped with their own cloud servers for medical consultant. However, it also brings about a series of challenges, especially how to ensure the security and privacy of the patients’ personal health information from various attacks in the wireless communication channel such as eavesdropping and tampering As to the security facet, one of the main issues is access control of patients’ personal health information, namely it is only the authorized physicians or institutions that can recover the patients’ personal health information during the data sharing in the distributed m-healthcare cloud computing system. In practice, most patients are concerned about the confidentiality of their personal health information since it is likely to make them in trouble for each kind of unauthorized collection and disclosure.

Therefore, in distributed m-healthcare cloud computing systems, which part of the patients’ personal health information should be shared and which physicians their personal health information should be shared with have become two intractable problems demanding urgent solutions. There has emerged various research results focusing on them. A fine-grained distributed data access control scheme is proposed using the technique of attribute based encryption (ABE). A rendezvous-based access control method provides access privilege if and only if the patient and the physician meet in the physical world. Recently, a patient-centric and fine-grained data access control in multi-owner settings is constructed for securing personal health records in cloud computing. However, it mainly focuses on the central cloud computing system which is not sufficient for efficiently processing the increasing volume of personal health information in m-healthcare cloud computing system.

Moreover, it is not enough for to only guarantee the data confidentiality of the patient’s personal health information in the honest-but-curious cloud server model since the frequent communication between a patient and a professional physician can lead the adversary to conclude that the patient is suffering from a specific disease with a high probability. Unfortunately, the problem of how to protect both the patients’ data confidentiality and identity privacy in the distributed m-healthcare cloud computing scenario under the malicious model was left untouched.

In this paper, we consider simultaneously achieving data confidentiality and identity privacy with high efficiency. As is described in Fig. 1, in distributed m-healthcare cloud computing systems, all the members can be classified into three categories: the directly authorized physicians with green labels in the local healthcare provider who are authorized by the patients and can both access the patient’s personal health information and verify the patient’s identity and the indirectly authorized physicians with yellow labels in the remote healthcare providers who are authorized by the directly authorized physicians for medical consultant or some research purposes (i.e., since they are not authorized by the patients, we use the term ‘indirectly authorized’ instead). They can only access the personal health information, but not the patient’s identity. For the unauthorized persons with red labels, nothing could be obtained. By extending the techniques of attribute based access control and designated verifier signatures (DVS) on de-identified health information

1.3 LITRATURE SURVEY

SECURING PERSONAL HEALTH RECORDS IN CLOUD COMPUTING: PATIENT-CENTRIC AND FINE-GRAINED DATA ACCESS CONTROL IN MULTI-OWNER SETTINGS

AUTHOR: M. Li, S. Yu, K. Ren, and W. Lou

PUBLISH: Proc. 6th Int. ICST Conf. Security Privacy Comm. Netw., 2010, pp. 89–106.

EXPLANATION:

Online personal health record (PHR) enables patients to manage their own medical records in a centralized way, which greatly facilitates the storage, access and sharing of personal health data. With the emergence of cloud computing, it is attractive for the PHR service providers to shift their PHR applications and storage into the cloud, in order to enjoy the elastic resources and reduce the operational cost. However, by storing PHRs in the cloud, the patients lose physical control to their personal health data, which makes it necessary for each patient to encrypt her PHR data before uploading to the cloud servers. Under encryption, it is challenging to achieve fine-grained access control to PHR data in a scalable and efficient way. For each patient, the PHR data should be encrypted so that it is scalable with the number of users having access. Also, since there are multiple owners (patients) in a PHR system and every owner would encrypt her PHR files using a different set of cryptographic keys, it is important to reduce the key distribution complexity in such multi-owner settings. Existing cryptographic enforced access control schemes are mostly designed for the single-owner scenarios. In this paper, we propose a novel framework for access control to PHRs within cloud computing environment. To enable fine-grained and scalable access control for PHRs, we leverage attribute based encryption (ABE) techniques to encrypt each patients’ PHR data. To reduce the key distribution complexity, we divide the system into multiple security domains, where each domain manages only a subset of the users. In this way, each patient has full control over her own privacy, and the key management complexity is reduced dramatically.

PRIVACY AND EMERGENCY RESPONSE IN E-HEALTHCARE LEVERAGING WIRELESS BODY SENSOR NETWORKS

AUTHOR: J. Sun, Y. Fang, and X. Zhu

PUBLISH: IEEE Wireless Commun., vol. 17, no. 1, pp. 66–73, Feb. 2010.

EXPLANATION:

Electronic healthcare is becoming a vital part of our living environment and exhibits advantages over paper-based legacy systems. Privacy is the foremost concern of patients and the biggest impediment to e-healthcare deployment. In addressing privacy issues, conflicts from the functional requirements must be taken into account. One such requirement is efficient and effective response to medical emergencies. In this article, we provide detailed discussions on the privacy and security issues in e-healthcare systems and viable techniques for these issues. Furthermore, we demonstrate the design challenge in the fulfillment of conflicting goals through an exemplary scenario, where the wireless body sensor network is leveraged, and a sound solution is proposed to overcome the conflict.

HCPP: CRYPTOGRAPHY BASED SECURE EHR SYSTEM FOR PATIENT PRIVACY AND EMERGENCY HEALTHCARE

AUTHOR: J. Sun, X. Zhu, C. Zhang, and Y. Fang

PUBLISH: Proc. 31st Int. Conf. Distrib. Comput. Syst., 2011, pp. 373–382.

EXPLANATION:

Privacy concern is arguably the major barrier that hinders the deployment of electronic health record (EHR) systems which are considered more efficient, less error-prone, and of higher availability compared to traditional paper record systems. Patients are unwilling to accept the EHR system unless their protected health information (PHI) containing highly confidential data is guaranteed proper use and disclosure, which cannot be easily achieved without patients’ control over their own PHI. However, cautions must be taken to handle emergencies in which the patient may be physically incompetent to retrieve the controlled PHI for emergency treatment. In this paper, we propose a secure EHR system, HCPP (Healthcaresystem for Patient Privacy), based on cryptographic constructions and existing wireless network infrastructures, to provide privacy protection to patients under any circumstances while enabling timelyPHI retrieval for life-saving treatment in emergency situations. Furthermore, our HCPP system restricts PHI access to authorized (not arbitrary) physicians, who can be traced and held accountable if the accessed PHI is found improperly disclosed. Last but not least, HCPP leverages wireless network access to support efficient and private storage/retrieval of PHI, which underlies a secure and feasible EHR system.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Existing system data confidentiality is much important but in existing system framework it is not enough for to only guarantee the data confidentiality of the patient’s personal health information in the honest-but-curious cloud server model since the frequent communication between a patient and a professional physician can lead the adversary to conclude that the patient is suffering from a specific disease with a high probability. Unfortunately, the problem of how to protect both the patients’ data confidentiality and identity privacy in the distributed m-healthcare cloud computing scenario under the malicious model was left untouched.

Patients are unwilling to accept the EHR system unless their protected health information (PHI) containing highly confidential data is guaranteed proper use and disclosure, which cannot be easily achieved without patients’ control over their own PHI. However, cautions must be taken to handle emergencies in which the patient may be physically incompetent to retrieve the controlled PHI for emergency treatment a secure EHR system, HCPP (Health care system for Patient Privacy), based on cryptographic constructions and existing wireless network infrastructures, to provide privacy protection to patients under any circumstances while enabling timelyPHI retrieval for life-saving treatment in emergency situations.

2.1.1 DISADVANTAGES:

Existing applications in e-healthcare scenario can be realized through real-time, continuous vital monitoring to give immediate alerts of changes in patient status. Also, the WBAN operates in environments with open access by various people such as hospital or medical organization, which also accommodates attackers. The open wireless channel makes the data prone to be eavesdropped, modified, and injected. Many kinds of security threats have been existed, such as unauthenticated or unauthorized access, message disclosure, message modification, denial-of-service, node capture and compromised node, and routing attacks, etc. Among which two kinds of threats play the leading role, the threats from device compromise and the threats from network dynamics.

Existing problem of security is rising nowadays. Especially, the privacy of communication through Internet may be at risk of attacking in a number of ways. On-line collecting, transmitting, and processing of personal data cause a severe threat to privacy. Once the utilization of Internet-based services is concerned on-line, the lack of privacy in network communication is the main conversation in the public. This problem is far more significant in modern medical environment, as e-healthcare networks are implemented and developed. According to common standards, the network linked with general practitioners, hospitals, and social centers at a national or international scale. While suffering the risk of leaking the privacy data, such networks’ privacy information is facing great danger.

Data confidentiality is low.
Data redundancy is high.
There is a violation in data security.

2.2 PROPOSED SYSTEM:

We presented a new architecture of pseudonymiaztion for protecting privacy in E-health (PIPE) integrated pseudonymization of medical data, identity management, obfuscation of metadata with anonymous authentication to prevent disclosure attacks and statistical analysis in and suggested a secure mechanism guaranteeing anonymity and privacy in both the personal health information transferring and storage at a central m-healthcare cloud server.

We proposed an anonymous authentication of membership in dynamic groups. However, since the anonymous authentication mentioned above are established based on public key infrastructure (PKI), the need of an online certificate authority (CA) and one unique public key encryption for each symmetric key k for data encryption at the portal of authorized physicians made the overhead of the construction grow linearly with size of the group. Furthermore, the anonymity level depends on the size of the anonymity set making the anonymous authentication impractical in specific surroundings where the patients are sparsely distributed.

In this paper, the security and anonymity level of our proposed construction is significantly enhanced by associating it to the underlying Gap Bilinear Diffie-Hellman (GBDH) problem and the number of patients’ attributes to deal with the privacy leakage in patient sparsely distributed scenarios significantly, without the knowledge of which physician in the healthcare provider is professional in treating his illness, the best way for the patient is to encrypt his own PHI under a specified access policy rather than assign each physician a secret key. As a result, the authorized physicians whose attribute set satisfy the access policy can recover the PHI and the access control management also becomes more efficient.

2.2.1 ADVANTAGES:

Our advantages a patient-centric and fine-grained data access control using ABE to secure personal health records in cloud computing without privacy-preserving authentication. For comparison, to achieve the same functions of PSMPA, it could be considered as the combination of ABE and DVS that the computational complexity of PSMPA remains constant regardless of the number of directly authorized physicians and nearly half of the combination construction of ABE and DVS supporting flexible predicate.

The communication cost of PSMPA also remains constant; almost half of the combination construction and independent of the number of attributes d in that though the storage overhead of PSMPA is slightly more than the combination construction, it is independent of the number of directly authorized physicians and performs significantly better than traditional DVS, all of whose computational, communication and storage overhead increase linearly to the number of directly authorized physicians.

M-healthcare system is fully controlled and secured with encryption standards.
There is no data loss and data redundancy.
System provides full protection for patient’s data and their attributes.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : Microsoft Visual Studio .NET 2008
Script : C# Script
Back End : MS-SQL Server 2005
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data’s in the physical component is not identified.

DATA FLOW:

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:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 ARCHITECTURE DIAGRAM

3.2 DATAFLOW DIAGRAM:

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

In our implementation, we choose MIRACLE Library for simulating cryptographic operations using Microsoft C/C++ compilers. To achieve a comparable security of 1,024-bit RSA, According to the standards of Paring-based Crypto Librarya patient-centric and fine-grained data access control using ABE to secure personal health records in cloud computing [30] without privacy-preserving authentication. For comparison, to achieve the same functions of PSMPA, it could be considered as the combination of ABE and DVS that the computational complexity of PSMPA remains constant regardless of the number of directly authorized physicians and nearly half of the combination construction of ABE and DVS supporting flexible predicate. Fig. 5 illustrates the communication cost of PSMPA also remains constant, almost half of the combination construction and independent of the number of attributes d in vD. Fig. 6 shows that though the storage overhead of PSMPA is slightly more than the combination construction, it is independent of the number of directly authorized physicians and performs significantly better than traditional DVS, all of whose computational, communication and storage overhead increase linearly to the number of directly authorized physicians. that the computational and communication overhead of the combination construction decrease slightly faster than PSMPA as the threshold k increases, however, even when k reaches the maximum value equaling to d, the overheads are still much more than PSMPA. The comparison between our scheme and the anonymous authentication based on PKI the storage, communication and computational overhead towards N and k is identical to DVS, since to realize the same identity privacy, in all the constructions a pair of public key and private key would be assigned to each directly authorized physician and the number of signature operations is also linear to the number of physicians, independent of the threshold k. The simulation results show our PSMPA better adapts to the distributed m-healthcare cloud computing system than previous schemes, especially for enhancing the energy constrained mobile devices (the data sink’s) efficiency.

4.1 ALGORITHM

Attribute Based Designated Verifier Signature Scheme We propose a patient self-controllable and multi-level privacy-preserving cooperative authentication scheme based on ADVS to realize three levels of security and privacy requirement in distributed m-healthcare cloud computing system which mainly consists of the following five algorithms: Setup, Key Extraction, Sign, Verify and Transcript Simulation Generation. Denote the universe of attributes as U.

4.2 MODULES:

E-HEALTHCARE SYSTEM FRAMEWORK:

AUTHORIZED ACCESSIBLE PRIVACY MODEL:

SECURITY VERIFICATION:

PERFORMANCE EVALUATION:

4.3 MODULE DESCRIPTION:

E-healthcare System Framework:

E-healthcare System consists of three components: body area networks (BANs), wireless transmission networks and the healthcare providers equipped with their own cloud servers. The patient’s personal health information is securely transmitted to the healthcare provider for the authorized physicians to access and perform medical treatment. Illustrate the unique characteristics of distributed m-healthcare cloud computing systems where all the personal health information can be shared among patients suffering from the same disease for mutual support or among the authorized physicians in distributed healthcare providers and medical research institutions for medical consultation.

Authorized accessible privacy model:

Multi-level privacy-preserving cooperative authentication is established to allow the patients to authorize corresponding privileges to different kinds of physicians located in distributed healthcare providers by setting an access tree supporting flexible threshold predicates. Propose a novel authorized accessible privacy model for distributed m-healthcare cloud computing systems which consists of the following two components: an attribute based designated verifier signature scheme (ADVS) and the corresponding adversary model.

Security Verification:

The security and anonymity level of our proposed construction is significantly enhanced by associating it to the underlying Gap Bilinear Diffie-Hellman (GBDH) problem and the number of patients’ attributes to deal with the privacy leakage in patient sparsely distributed scenarios. More significantly, without the knowledge of which physician in the healthcare provider is professional in treating his illness, the best way for the patient is to encrypt his own PHI under a specified access policy rather than assign each physician a secret key. As a result, the authorized physicians whose attribute set satisfy the access policy can recover the PHI and the access control management also becomes more efficient.

Performance Evaluation:

The efficiency of PSMPA in terms of storage overhead, computational complexity and communication cost. a patient-centric and fine-grained data access control using ABE to secure personal health records in cloud computing without privacy-preserving authentication. To achieve the same security, our construction performs more efficiently than the traditional designated verifier signature for all the directly authorized physicians, where the overheads are linear to the number of directly authorized physicians.

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

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

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.

5.1.2 TECHNICAL FEASIBILITY:

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:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

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 7

7.0 SOFTWARE SPECIFICATION:

7.1 FEATURES OF .NET:

Microsoft .NET is a set of Microsoft software technologies for rapidly building and integrating XML Web services, Microsoft Windows-based applications, and Web solutions. The .NET Framework is a language-neutral platform for writing programs that can easily and securely interoperate. There’s no language barrier with .NET: there are numerous languages available to the developer including Managed C++, C#, Visual Basic and Java Script.

The .NET framework provides the foundation for components to interact seamlessly, whether locally or remotely on different platforms. It standardizes common data types and communications protocols so that components created in different languages can easily interoperate.

“.NET” is also the collective name given to various software components built upon the .NET platform. These will be both products (Visual Studio.NET and Windows.NET Server, for instance) and services (like Passport, .NET My Services, and so on).

7.2 THE .NET FRAMEWORK

The .NET Framework has two main parts:

1. The Common Language Runtime (CLR).

2. A hierarchical set of class libraries.

The CLR is described as the “execution engine” of .NET. It provides the environment within which programs run. The most important features are

Conversion from a low-level assembler-style language, called Intermediate Language (IL), into code native to the platform being executed on.
Memory management, notably including garbage collection.
Checking and enforcing security restrictions on the running code.
Loading and executing programs, with version control and other such features.
The following features of the .NET framework are also worth description:

Managed Code

The code that targets .NET, and which contains certain extra Information – “metadata” – to describe itself. Whilst both managed and unmanaged code can run in the runtime, only managed code contains the information that allows the CLR to guarantee, for instance, safe execution and interoperability.

Managed Data

With Managed Code comes Managed Data. CLR provides memory allocation and Deal location facilities, and garbage collection. Some .NET languages use Managed Data by default, such as C#, Visual Basic.NET and JScript.NET, whereas others, namely C++, do not. Targeting CLR can, depending on the language you’re using, impose certain constraints on the features available. As with managed and unmanaged code, one can have both managed and unmanaged data in .NET applications – data that doesn’t get garbage collected but instead is looked after by unmanaged code.

Common Type System

The CLR uses something called the Common Type System (CTS) to strictly enforce type-safety. This ensures that all classes are compatible with each other, by describing types in a common way. CTS define how types work within the runtime, which enables types in one language to interoperate with types in another language, including cross-language exception handling. As well as ensuring that types are only used in appropriate ways, the runtime also ensures that code doesn’t attempt to access memory that hasn’t been allocated to it.

Common Language Specification

The CLR provides built-in support for language interoperability. To ensure that you can develop managed code that can be fully used by developers using any programming language, a set of language features and rules for using them called the Common Language Specification (CLS) has been defined. Components that follow these rules and expose only CLS features are considered CLS-compliant.

7.3 THE CLASS LIBRARY

.NET provides a single-rooted hierarchy of classes, containing over 7000 types. The root of the namespace is called System; this contains basic types like Byte, Double, Boolean, and String, as well as Object. All objects derive from System. Object. As well as objects, there are value types. Value types can be allocated on the stack, which can provide useful flexibility. There are also efficient means of converting value types to object types if and when necessary.

The set of classes is pretty comprehensive, providing collections, file, screen, and network I/O, threading, and so on, as well as XML and database connectivity.

The class library is subdivided into a number of sets (or namespaces), each providing distinct areas of functionality, with dependencies between the namespaces kept to a minimum.

7.4 LANGUAGES SUPPORTED BY .NET

The multi-language capability of the .NET Framework and Visual Studio .NET enables developers to use their existing programming skills to build all types of applications and XML Web services. The .NET framework supports new versions of Microsoft’s old favorites Visual Basic and C++ (as VB.NET and Managed C++), but there are also a number of new additions to the family.

Visual Basic .NET has been updated to include many new and improved language features that make it a powerful object-oriented programming language. These features include inheritance, interfaces, and overloading, among others. Visual Basic also now supports structured exception handling, custom attributes and also supports multi-threading.

Visual Basic .NET is also CLS compliant, which means that any CLS-compliant language can use the classes, objects, and components you create in Visual Basic .NET.

Managed Extensions for C++ and attributed programming are just some of the enhancements made to the C++ language. Managed Extensions simplify the task of migrating existing C++ applications to the new .NET Framework.

C# is Microsoft’s new language. It’s a C-style language that is essentially “C++ for Rapid Application Development”. Unlike other languages, its specification is just the grammar of the language. It has no standard library of its own, and instead has been designed with the intention of using the .NET libraries as its own.

Microsoft Visual J# .NET provides the easiest transition for Java-language developers into the world of XML Web Services and dramatically improves the interoperability of Java-language programs with existing software written in a variety of other programming languages.

Active State has created Visual Perl and Visual Python, which enable .NET-aware applications to be built in either Perl or Python. Both products can be integrated into the Visual Studio .NET environment. Visual Perl includes support for Active State’s Perl Dev Kit.

Other languages for which .NET compilers are available include

FORTRAN
COBOL
Eiffel

ASP.NET XML WEB SERVICES	Windows Forms
Base Class Libraries
Common Language Runtime
Operating System

Fig1 .Net Framework

C#.NET is also compliant with CLS (Common Language Specification) and supports structured exception handling. CLS is set of rules and constructs that are supported by the CLR (Common Language Runtime). CLR is the runtime environment provided by the .NET Framework; it manages the execution of the code and also makes the development process easier by providing services.

C#.NET is a CLS-compliant language. Any objects, classes, or components that created in C#.NET can be used in any other CLS-compliant language. In addition, we can use objects, classes, and components created in other CLS-compliant languages in C#.NET .The use of CLS ensures complete interoperability among applications, regardless of the languages used to create the application.

CONSTRUCTORS AND DESTRUCTORS:

Constructors are used to initialize objects, whereas destructors are used to destroy them. In other words, destructors are used to release the resources allocated to the object. In C#.NET the sub finalize procedure is available. The sub finalize procedure is used to complete the tasks that must be performed when an object is destroyed. The sub finalize procedure is called automatically when an object is destroyed. In addition, the sub finalize procedure can be called only from the class it belongs to or from derived classes.

GARBAGE COLLECTION

Garbage Collection is another new feature in C#.NET. The .NET Framework monitors allocated resources, such as objects and variables. In addition, the .NET Framework automatically releases memory for reuse by destroying objects that are no longer in use.

In C#.NET, the garbage collector checks for the objects that are not currently in use by applications. When the garbage collector comes across an object that is marked for garbage collection, it releases the memory occupied by the object.

OVERLOADING

Overloading is another feature in C#. Overloading enables us to define multiple procedures with the same name, where each procedure has a different set of arguments. Besides using overloading for procedures, we can use it for constructors and properties in a class.

MULTITHREADING:

C#.NET also supports multithreading. An application that supports multithreading can handle multiple tasks simultaneously, we can use multithreading to decrease the time taken by an application to respond to user interaction.

STRUCTURED EXCEPTION HANDLING

C#.NET supports structured handling, which enables us to detect and remove errors at runtime. In C#.NET, we need to use Try…Catch…Finally statements to create exception handlers. Using Try…Catch…Finally statements, we can create robust and effective exception handlers to improve the performance of our application.

7.5 THE .NET FRAMEWORK

The .NET Framework is a new computing platform that simplifies application development in the highly distributed environment of the Internet.

OBJECTIVES OF .NET FRAMEWORK

1. To provide a consistent object-oriented programming environment whether object codes is stored and executed locally on Internet-distributed, or executed remotely.

2. To provide a code-execution environment to minimizes software deployment and guarantees safe execution of code.

3. Eliminates the performance problems.

There are different types of application, such as Windows-based applications and Web-based applications.

7.6 FEATURES OF SQL-SERVER

The OLAP Services feature available in SQL Server version 7.0 is now called SQL Server 2000 Analysis Services. The term OLAP Services has been replaced with the term Analysis Services. Analysis Services also includes a new data mining component. The Repository component available in SQL Server version 7.0 is now called Microsoft SQL Server 2000 Meta Data Services. References to the component now use the term Meta Data Services. The term repository is used only in reference to the repository engine within Meta Data Services

SQL-SERVER database consist of six type of objects,

They are,

1. TABLE

2. QUERY

3. FORM

4. REPORT

5. MACRO

7.7 TABLE:

A database is a collection of data about a specific topic.

VIEWS OF TABLE:

We can work with a table in two types,

1. Design View

2. Datasheet View

Design View

To build or modify the structure of a table we work in the table design view. We can specify what kind of data will be hold.

Datasheet View

To add, edit or analyses the data itself we work in tables datasheet view mode.

QUERY:

A query is a question that has to be asked the data. Access gathers data that answers the question from one or more table. The data that make up the answer is either dynaset (if you edit it) or a snapshot (it cannot be edited).Each time we run query, we get latest information in the dynaset. Access either displays the dynaset or snapshot for us to view or perform an action on it, such as deleting or updating.

CHAPTER 7

7.0 APPENDIX

7.1 SAMPLE SCREEN SHOTS:

7.2 SAMPLE SOURCE CODE:

CHAPTER 8

8.1 CONCLUSION AND FUTURE ENHANCEMENT:

In this paper, a novel authorized accessible privacy model and a patient self-controllable multi-level privacy preserving cooperative authentication scheme realizing three different levels of security and privacy requirement in the distributed m-healthcare cloud computing system are proposed, followed by the formal security proof and efficiency evaluations which illustrate our PSMPA can resist various kinds of malicious attacks and far outperforms previous schemes in terms of storage, computational and communication overhead.