How To Create A Privacy Preserving And Dynamic Load Balancing System In A Distributed System

Transcription

1 Enforcing Secure and Privacy-Preserving Information Brokering with Dynamic Load Balancing in Distributed Information Sharing. 1 M.E. Computer Engineering Department GHRCEM, Wagholi, Pune. [email protected] 2 Department of Computer, GHRCEM, Wagholi, Pune, India University Of Pune Abstract This paper describes concept of privacy preserving and dynamic load balancing. To preserve sensitive information Privacy Preserving is used. Information sharing through on-demand access has been increased in organizations (e.g. libraries, enterprise). Information sharing among large scale loosely unified data sources are connected via peer-to-peer overlay network by Information Brokering System (IBS). Information Brokering System (IBS) is distributed system providing data access through set of brokers. The set of brokers are used to make decisions to locate data sources for client queries. A solution in Information Brokering process of multiple stakeholders is Privacy Preserving Information Brokering (PPIB) to preserve privacy. To integrate security with query routing has been achieved by automaton segmentation and query segment encryption. The attacker could infer the privacy by two attacks named as correlation attack and inference attack. I also focus on concept of Load Balancing. Load balancing has important impact on performance. In distributed system, load balancing is applied among nodes for redistributing the workload. Load balancing improves resource utilization and response time for implementing this concept; I focus on Dynamic Load Balancing Algorithm. Keywords Privacy, PPIB, Automaton segmentation, query segment encryption, Load Balancing, distributed system. 1. Introduction There is increasing need for information sharing in recent years, in different organization. In designing distributed information sharing system, there is need for peer autonomy. The existing system work on 1) Query Answering model, 2) Distributed database system [2]. In Query Answering model, peers are fully autonomous but no system-wide communication. In Distributed database system, all participates don t have autonomy and they are managed by centralized DBMs.Both of the spectrum are not suitable for newly application. The centralized DBMs is not suitable for sensitive and autonomous data provider. For this problem, the solution is Data Centric overlay. The 207

2 system consisting of data sources and brokers. Brokers are helping to make routing decision for queries. In earlier study, distributed system providing data access through set of brokers.ibs system providing scalability, on-demand data access with transparency and server autonomy. The problem with IBS infrastructure is brokers are not fully trusted Figure 1. Overview of the IBS infrastructure. To overcome this problem, Privacy Preserving Information Brokering (PPIB) introduced. In this paper, it introduced the implementation of Dynamic Load Balancing concept. Dynamic load balancing improves system performance. Load Balancing means redistribute workload among the nodes of distribute system to improve resource utilization and response time [6]. 2. Background In order to provide privacy and security Privacy Preserving Information Brokering (PPIB) introduced. PPIB has two types of brokering component 1) Brokers and 2) Co-ordinator [1][2]. The user authentication and query forwarding is done by brokers. Access control and query routing is done by co-ordinator. In this paper, two attacks have been discussed and also provide solution to overcome those attacks for security purpose. In this paper, it introduced concept of dynamic load balancing. For improving system performance dynamic load balancing is implemented. 3. The Problem In the Information brokering system, there are mainly three types of stakeholder data owner, data provider and data requester. The information is may be different from one another. The main problem has been created by attacker. Attacker could infer privacy of data owner, data provider and data requester. Also introduce problem of system performance. There are two types of attacks as follows 1).Inference attack 2).Attributecorrelation attack[1][2]. Inference attack This attack is totally based on the guessing the query. If the guess is matches, the query will be inferred. Attribute-correlation attack This attack is depends on predicates. Attacker prevents query, which contain 208

3 predicates. To infer sensitive information, the attacker correlate attributes Need for improving Performance Solution: PPIB has been provided for overcome these attacks. In this way, privacy is preserved. And also Dynamic load balancing algorithm is implemented for improving performance of system. 4. Privacy Preserving Information Brokering (PPIB) 4.1 Architecture of PPIB: Brokers: Brokers are attached through coordinators. The main function of brokers is for user authentication and query forwarding. Coordinator: Coordinator is responsible for access control and content based query routing. Central Authority: Central Authority is responsible for metadata maintenance and key management. 4.2 Two Novel Schemes: A. Automata Segmentation The data is share between multiple organizations. Organizations have their own ideas and goals. Global components are divided locally and forwarded to the coordinators. The query must be partitioned into multiple parts and parts are forwarded to the local coordinators. Automata Segmentation includes deployment, segmentation and replication [1][2]. B. Query Segment Encryption Figure 1. Architecture of PPIB. PPIB has mainly three types of brokering components: (a) Brokers (b) Coordinators and (c) Central authority (CA) [2]. In Query Segment Encryption phase, segmented query is encrypted by the coordinator. It consists of post-encryption and pre-encryption modules. Coordinator uses the key to encrypt the query segment. The encrypted query has been send to the next coordinator. Until it reaches its data server, query must be prevented. Query has been forwarded to destination [1][2] Phases of PPIB 209

4 5. Conclusion Fig 3. 4-Phases of PPIB. Phase 1: To join the system user needs to authenticate to local broker. The user submits encrypted segment with XML query by unique session key Ks and public level keys, data servers encrypted with the public key, to return data. Phase 2: The task of metadata preparation is done by broker. 1. It extracts the role of the user authenticated and attaches it to the encrypted XML query; 2. For each query it makes a unique ID, and attaches QID with its own address to the query. Data server can directly return the data. Phase 3: The query receives by the root of the coordinator tree and its metadata from a local the query within the coordinator tree, until it reaches a leaf coordinator, which broker, it follows schemes i.e. the automata segmentation scheme for segment the XML query and to perform access control the query segment encryption scheme and to route sends the query to related data servers. Phase 4: In this phase, the data server gets a safe query in an encrypted form. The data server evaluates the query and after decryption returns the data, encrypted by Ks, to the broker of the query [2]. This system gives different ways for privacy and security issues. We studied how the privacy and security is maintained. Attacker could infer privacy of data owner, data provider and data requester. Also introduce problem of system performance. There are two types of attacks: inference attack and Attribute-correlation attack are studied. In this paper, we studied PPIB architecture, two novel scheme, and phases of PPIB. This system proposes a new approach for Dynamic load Balancing concept. 6. References [1] Enforcing Secure and Privacy- Preserving Information Brokering in Distributed Information Sharing, by Bo Luo, Chao-Hsien Chu, Peng Liu Dongwon Lee, Fengjun Li, IEEE TRANSCATIONS ON INFORMATION FORENSICS AND SECURITY, [2] Ms. Pradnya Kamble, Mr. Mukesh Kawatghare, Review on Enforcing Secure And Privacy Preserving Information Brokering In Distributed Information Sharing. [3] In-broker access control: Towards efficient end-to-end performance of information brokerage systems, by F. Li, P. Liu, D. Lee, B. Luo, W. Lee, and P. Mitra, C. Chu, in Proc. IEEE SUTC, [4] A. Banu Prabha Security Enforcement with query routing Information Brokering in Distributed Information Sharing IOSR-JCE,Issue 2, Vol 16,Ver.XI Mar-Apr

5 [5] Noe Elisa, K. Suresh Babu SURVEY ON PROTECTING PRIVACY ANDSECURITY IN XML INFORMATION BROKERING IJCSMC, Vol.3, Issue.4 April [6] EXECUTION ANALYSIS OF LOAD BALANCING ALGORITHMS IN CLOUD COMPUTING ENVIRONMENT Ajanta De Sarkar,Soumya Ray. IJCCSA, Vol.2, No.5, October [7] S.S.Apte,Abhijit A. Rajguru,, A Comparative Performance Analysis of Load Balancing Algorithms in Distributed System using Qualitative Parameters Volume-1,Issue-3,August [8] Rima Lingawar,Milind Srode,Mangesh Ghonge, Survey on Load-Balancing Techniques in Cloud Computing IJARCE,Vol.1,No.3,May AUTHORS First Author Ms. Jyoti M.More, ME (Computer Engineering), GHRCEM, Wagholi Pune. [email protected] Second Author Ms. Urmila Biradar, ME(CE),GHRCEM,Wagholi pune. 211