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VLSI PROJECTS ABSTRACT 2016-2017 A PERFORMANCE DEGRADATION TOLERABLE CACHE DESIGN BY EXPLOITING MEMORY HIERARCHIES ABSTRACT: Performance degradation tolerance (PDT) has been shown to be able to effectively improve the yield, reliability, and lifetime of an electronic product. The focus of PDT is on the particular performance degrading faults (pdef) that only incur some performance degradation of a system without inducing any computation errors. The basic idea is that as long as the defective chips containing only the pdef can provide acceptable performance for some applications, they may still be marketable. Critical issues of PDT to be addressed include the portion of the pdef in a faulty chip and their induced performance degradation. For a typical cache design, most of the possible faults are not pdef. In this brief, we propose a cache redesign method, called PDT cache, where all functional faults in the data-storage cells of a cache (major part of the cache) can be transformed into pdef. By transforming this large number of faults into pdef, a faulty cache becomes much more likely to be still marketable. The proposed design exploits the existing hardware resources and the inherent error resilience scheme to reduce the incurred hardware overhead. The logic synthesis results show that the incurred hardware overhead is only 6.29% for a 32-kB cache. We also evaluate the induced performance degradation under various fault densities using the CPU2000 and CPU2006 benchmark programs. The results show that for a 32-kB cache design, when the fault density is <1%, only 0.31% performance degradation is incurred. In addition, the scalability of the PDT cache is also evaluated. The results show that a smaller hardware overhead is required for a larger cache, and the performance degradation is independent of the cache associativity and can even be smaller for a
JAVA PROJECTS ABSTRACT 2016-2017 A LOCALITY SENSITIVE LOW-RANK MODEL FOR IMAGE TAG COMPLETION ABSTRACT: Tag-based image retrieval often used to increase performance to retrieving images with the help of search engines. Image retrieval based on user-provided image tags on the photo sharing websites. A requirement for effective searching and retrieval of images in rapid growing online image databases is that each image has accurate and useful annotation. Many visual applications have benefited from the outburst of web images, yet the imprecise and incomplete tags arbitrarily provided by users. In this paper, we propose a novel locality sensitive low-rank model for image tag completion, which approximates the global nonlinear model with a collection of local linear models. To effectively infuse the idea of locality sensitivity, a simple and effective pre-processing module is designed to learn suitable representation for data partition.In thi paper they used for BIRCH algorithm. BIRCH (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large data-sets.An advantage of BIRCH is its ability to incrementally and dynamically cluster incoming, multi-dimensional metric data points in an attempt to produce the best quality clustering for a given set of resources (memory and time constraints). In most cases, BIRCH only requires a single scan of the database. Existing System The user-labeled visual data, such as images which are uploaded and shared in Flickr, are usually associated with imprecise and incomplete tags. This will pose threats to the retrieval or indexing of these images, causing them difficult to be accessed by users. Unfortunately, missing label is inevitable in the manual labeling phase, since it is infeasible for users to label every related word and avoid all possible confusions, due to the existence of synonyms and user preference. Therefore, image tag completion or refinement has emerged as a hot issue in the multimedia community.Many visual applications have benefited from the outburst of web images, yet the imprecise and incomplete tags arbitrarily provided by users, as the thorn of the rose, may hamper the performance of retrieval or indexing systems relying on such data. Proposed System To effectively infuse the idea of locality sensitivity, a simple and effective pre-processing module is designed to learn suitable representation for data partition, and a global consensus regularizer is introduced to mitigate the risk of overfitting. Meanwhile, low-rank matrix factorization is employed as local models, where the local geometry structures are preserved for the low-dimensional representation of both tags and samples. Extensive empirical evaluations conducted on three datasets demonstrate the effectiveness and efficiency of the proposed method, where our method outperforms pervious ones by a large margin. Advantages • We propose a locality sensitive low-rank model for image tag completion, which approximates the global nonlinear model with a collection of local linear models, by which complex correlation structures can be captured. • Several adaptations are introduced to enable the fusion of locality sensitivity and low-rank factorization, including a simple and effective pre-processing module and a global consensus regularizer to mitigate the risk of overfitting. Disadvantages • image tag completion or refinement has emerged as a hot issue in the multimedia community. • The existing completion methods are usually founded on linear assumptions, hence the obtained models are limited due to their incapability to capture complex correlation patterns. System Requirements H/W System Configuration:- Processor - Pentium –III Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA S/W System Configuration  Operating System :Windows95/98/2000/XP  Application Server : Tomcat5.0/6.X  Front End : HTML, Java, Jsp  Scripts : JavaScript.  Server side Script : Java Server Pages.  Database Connectivity : Mysql. Conclusion In this paper we propose a locality sensitive low-rank model for image tag completion. The proposed method can capture complex correlations by approximating a nonlinear model with a collection of local linear models. To effectively integrate locality sensitivity and low-rank factorization, several adaptations are introduced, including the design of a pre-processing module and a global consensus regularizer. Our method achieves superior results on three datasets and outperforms pervious methods by a large margin.
JAVA /DOT NET PROJECTS ABSTRACT 2016-2017 OUTSOURCED ATTRIBUTE BASED ENCRYPTION WITH KEYWORD SEARCH FUNCTION FOR CLOUD STORAGE ABSTRACT: Cloud computing becomes increasingly popular for data owners to outsource their data to public cloud servers while allowing intended data users to retrieve these data stored in cloud. This kind of computing model brings challenges to the security and privacy of data stored in cloud. Attribute-based encryption (ABE) technology has been used to design fine-grained access control system, which provides one good method to solve the security issues in cloud setting. However, the computation cost and cipher text size in most ABE schemes grow with the complexity of the access policy. Outsourced ABE(OABE) with fine-grained access control system can largely reduce the computation cost for users who want to access encrypted data stored in cloud by outsourcing the heavy computation to cloud service provider (CSP). However, as the amount of encrypted files stored in cloud is becoming very huge, which will hinder efficient query processing. To deal with above problem, we present a new cryptographic primitive called attribute-based encryption scheme with outsourcing key-issuing and outsourcing decryption, which can implement keyword search function (KSF-OABE). The proposed KSF-OABE scheme is proved secure against chosen-plaintext attack (CPA). CSP performs partial decryption task delegated by data user without knowing anything about the plaintext. Moreover, the CSP can perform encrypted keyword search without knowing anything about the keywords embedded in trapdoor. Here we used the alogorithm is, EXISTING SYSTEM: Out Sourced Attribute Based Encryption With Keyword Search Function For Cloud Storage, In this case, the File key can be upload based on the attribute functions. The file can be upload if the authorized person give a key to upload a file. If a group is updated, then the group key changes to the shared key of the new group. The drawback of is that the user key size is combinatorial large in the total number of users (if the system is unconditionally secure).Another drawback is that the group key of a given group cannot be changed even if it is leaked unexpectedly (e.g) cryptanalysis of cipher texts bearing this key).The key size problem may be overcome if a computationally secure easy. Further, computationally secure KPS is only known for the two party case and the three-party case KPs with a group size greater than still open. PROPOSED SYSTEM: The out sourced attribute based encryption with keyword search function for cloud storage with an arbitrary connectivity graph, where each user is only aware of his neighbors and has no information about the existence of other users. Further, he has no information about the network topology. Under this setting a user does not need to trust a user who is not his neighbor.Thus, if one is initialized using PKI, then the need not trust or remember public keys of users beyond his neighbours. ADVANTAGES: 1. To update the key more efficiently than just running the protocol again, when user memberships are changing. 2. Two passively secure protocols with contributiveness and proved lower bounds on a round complexity, demonstrating that our protocols are round efficient. H/W System Configuration:- Processor - Pentium –III 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 S/W System Configuration:-  Operating System :Windows95/98/2000/XP  Front End : java, jdk1.6  Database : My sqlserver 2005  Database Connectivity : JDBC.
JAVA /DOT NET PROJECT ABSTRACT 2016-2017 MITIGATING CROSS-SITE SCRIPTING ATTACKS WITH A CONTENT SECURITY POLICY ABSTRACT: A content security policy (CSP) can help Web application developers and server administrators better control website content and avoid vulnerabilities to cross site scripting (XSS). In experiments with a prototype website, the authors’ CSP implementation successfully mitigated all XSS attack types in four popular browsers. Among the many attacks on Web applications, cross site scripting (XSS) is one of the most common. An XSS attack involves injecting malicious script into a trusted website that executes on a visitor’s browser without the visitor’s knowledge and thereby enables the attacker to access sensitive user data, such as session tokens and cookies stored on the browser.1 With this data, attackers can execute several malicious acts, including identity theft, key logging, phishing, user impersonation, and webcam activation. Content Security Policy (CSP) is an added layer of security that helps to detect and mitigate certain types of attacks, including Cross Site Scripting (XSS) and data injection attacks. These attacks are used for everything from data theft to site defacement or distribution of malware. CSP is designed to be fully backward compatible; browsers that don't support it still work with servers that implement it, and vice-versa. Browsers that don't support CSP simply ignore it, functioning as usual, defaulting to the standard same-origin policy for web content. If the site doesn't offer the CSP header, browsers likewise use the standard same-origin policy.Enabling CSP is as easy as configuring your web server to return the Content-Security-Policy HTTP header. (Prior to Firefox 23, the X-Content-Security-Policy header was used). See Using Content Security Policy for details on how to configure and enable CSP. INTRODUCTION A primary goal of CSP is to mitigate and report XSS attacks. XSS attacks exploit the browser's trust of the content received from the server. Malicious scripts are executed by the victim's browser because the browser trusts the source of the content, even when it's not coming from where it seems to be coming from. CSP makes it possible for server administrators to reduce or eliminate the vectors by which XSS can occur by specifying the domains that the browser should consider to be valid sources of executable scripts. A CSP compatible browser will then only execute scripts loaded in source files received from those whitelisted domains, ignoring all other script (including inline scripts and event-handling HTML attributes). PROPOSED SYSTEM: A client-side tool that acts as a Web proxy, disallows requests that do not belong to the website and thus thwarts stored XSS attacks. Browser-enforced embedded policies (BEEPs) let the Web application developer embed a policy in the website by specifying which scripts are allowed to run.With a BEEP, the developer can put genuine source scripts in a white list and disable source scripts in certain website regions. Document Structure Integrity (DSI) is a client-server architecture that restricts the interpretation of untrusted content. DSI uses parser-level isolation to isolate inline untrusted data and separates dynamic content from static content. However, this approach requires both servers and clients to cooperatively upgrade to enable protection. System Configuration H/W System Configuration: Processor - Pentium –III 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 S/W System Configuration:  Operating System :Windows95/98/2000/XP  Application Server : Tomcat5.0/6.X  Front End : HTML, Java, Jsp  Scripts : JavaScript.  Server side Script : Java Server Pages.  Database : Mysql  Database Connectivity : JDBC. CONCLUSION: Although our CSP has many benefits, it is not intended as a primary defense mechanism against XSS attacks. Rather, it would best serve as a defensein- depth mitigation mechanism. A primary defense involves tailored security schemes that validate user inputs and encode user outputs. Cross site scripting has been a major threat for web applications and its users from past few years. Lot of work has been done to handle XSS attacks which include: • Client side approaches • Server side approaches • Testing based approaches • Static and dynamic analysis based approaches
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JAVA/ DOT NET PROJECT ABSTRACT 2016-2017 QUALITY-AWARE SUBGRAPH MATCHING OVER INCONSISTENT PROBABILISTIC GRAPH DATABASES ABSTRACT: The Resource Description Framework (RDF) is a general framework for how to describe any Internet resource such as a Web site and its content. An RDF description (such descriptions are often referred to as metadata, or "data about data") can include the authors of the resource, date of creation or updating, the organization of the pages on a site (the sitemap), information that describes content in terms of audience or content rating, key words for search engine data collection, subject categories, and so forth.Resource Description Framework has been widely used in the Semantic Web to describe resources and their relationships. The RDF graph is one of the most commonly used representations for RDF data. However, in many real applications such as the data extraction/integration, RDF graphs integrated from different data sources may often contain uncertain and inconsistent information (e.g., uncertain labels or that violate facts/rules), due to the unreliability of data sources. In this paper, we formalize the RDF data by inconsistent probabilistic RDF graphs, which contain both inconsistencies and uncertainty. With such a probabilistic graph model, we focus on an important problem, quality-aware subgraph matching over inconsistent probabilistic RDF graphs , which retrieves subgraphs from inconsistent probabilistic RDF graphs that are isomorphic to a given query graph and with high quality scores (considering both consistency and uncertainty). In order to efficiently answer QA-gMatch queries, we provide two effective pruning methods, namely adaptive label pruning and quality score pruning, which can greatly filter out false alarms of subgraphs. We also design an effective index to facilitate our proposed pruning methods, and propose an efficient approach for processing QA-gMatch queries. Finally, we demonstrate the efficiency and effectiveness of our proposed approaches through extensive experiments. EXISTING SYSTEM: Probabilistic graphs are often obtained from real-world applications such as the data extraction/integration in the SemanticWeb. Due to the unreliability of data sources or inaccurate extraction/integration techniques, probabilistic graph data often contain inconsistencies, violating some rules or facts. Here, rules or facts can be specified by knowledge base or inferred by data mining techniques. RDF graphs integrated from different data sources may often contain uncertain and inconsistent information , due to the unreliability of data sources. we formalize the RDF data by inconsistent probabilistic RDF graphs, which contain both inconsistencies and uncertainty. With such a probabilistic graph model, we focus on an important problem, quality-aware subgraph matching over inconsistent probabilistic RDF graphs (QA-gMatch), which retrieves subgraphs from inconsistent probabilistic RDF graphs that are isomorphic to a given query graph and with high quality scores (considering both consistency and uncertainty. PROPOSED SYATEM: In this paper, we propose the quality-aware subgraph matching problem (namely, QA-gMatch) in a novel context of inconsistent probabilistic graphs G with quality guarantees. Specifically, given a query graph q, a QA-gMatch query retrieves subgraphs g of probabilistic graph G that match with q and have high quality scores. The QA-gMatch problem has many practical applications such as the Semantic Web. For example, we can answer standard queries, SPARQL queries, over inconsistent probabilistic RDF graphs by issuing QA-gMatch queries. we will propose effective pruning methods, namely adaptive label pruning (based on a cost model) and quality score pruning, to reduce the QAgMatch search space and improve the query efficiency. Advantages: • We propose the QA-gMatch problem in inconsistent probabilistic graphs, which, to our best knowledge, no prior work has studied. • We carefully design effective pruning methods, adaptive label and quality score pruning, specific for inconsistent and probabilistic features of RDF graphs. • We build a tree index over pre-computed data of inconsistent probabilistic graphs, and illustrate efficient QA-gMatch query procedure by traversing the index. System Requirements: H/W System Configuration:- Processor - Pentium –III Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA S/W System Configuration:-  Operating System :Windows95/98/2000/XP  Application Server : Tomcat5.0/6.X  Front End : HTML, Java, Jsp  Scripts : JavaScript.  Server side Script : Java Server Pages.  Database Connectivity : Mysql.
JAVA/ DOT NET PROJECT ABSTRACT 2016-2017 SECRBAC: SECURE DATA IN CLOUDS ABSTRACT: Most current security solutions are based on perimeter security. However, Cloud computing breaks the organization perimeters. When data resides in the Cloud, they reside outside the organizational bounds. This leads users to a loos of control over their data and raises reasonable security concerns that slow down the adoption of Cloud computing. Is the Cloud service provider accessing the data? Is it legitimately applying the access control policy defined by the user? This paper presents a data-centric access control solution with enriched role-based expressiveness in which security is focused on protecting user data regardless the Cloud service provider that holds it. Novel identity-based and proxy re-encryption techniques are used to protect the authorization model. Data is encrypted and authorization rules are cryptographically protected to preserve user data against the service provider access or misbehavior. The authorization model provides high expressiveness with role hierarchy and resource hierarchy support. The solution takes advantage of the logic formalism provided by Semantic Web technologies, which enables advanced rule management like semantic conflict detection. A proof of concept implementation has been developed and a working prototypical deployment of the proposal has been integrated within Google services. EXISTING SYSTEM: The data centers used by cloud providers may also be subject to compliance requirements. Using a cloud service provider (CSP) can lead to additional security concerns around data jurisdiction since customer or tenant data may not remain on the same system, or in the same data center or even within the same provider's cloud. Searchable Encryption is a cryptographic primitive which offers secure search functions over encrypted data. In order to improve search efficiency, an SE solution generally builds keyword indexes to securely perform user queries. Existing SE schemes can be classified into two categories: SE based on secret-key cryptography and SE based on public-key cryptography. PROPOSED SYSTEM The proposed authorization solution provides a rule-based approach following the RBAC scheme, where roles are used to ease the management of access to the resources. The main contributions of the proposed solution are: • Data-centric solution with data protection for the Cloud Service Provider to be unable to access it . • Rule-based approach for authorization where rules are under control of the data owner. • High expressiveness for authorization rules applying the RBAC scheme with role hierarchy and resource hierarchy (Hierarchical RBAC or hRBAC). • Access control computation delegated to the CSP, but being unable to grant access to unauthorized parties. System Configuration H/W System Configuration: Processor - Pentium –III 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 S/W System Configuration:  Operating System :Windows95/98/2000/XP  Application Server : Tomcat5.0/6.X  Front End : HTML, Java, Jsp  Scripts : JavaScript.  Server side Script : Java Server Pages.  Database : Mysql  Database Connectivity : JDBC. CONCLUSION: A data-centric authorization solution has been proposed for the secure protection of data in the Cloud. SecRBAC allows managing authorization following a rule-based approach and provides enriched role-based expressiveness including role and object hierarchies. Access control computations are delegated to the CSP, being this not only unable to access the data, but also unable to release it to unauthorized parties. Advanced cryptographic techniques have been applied to protect the authorization model. A re-encryption key complement each authorization rule as cryptographic token to protect data against CSP misbehavior. The solution is independent of any PRE scheme or implementation as far as three specific features are supported.
JAVA/DOT NET PROJECTS ABSTRACT 2016-2107 TRUST AGENT-BASED BEHAVIOR INDUCTION IN SOCIAL NETWORKS ABSTRACT: The essence of social networks is that they can influence people's public opinions and group behaviors form quickly. Negative group behavior influences societal stability significantly, but existing behavior-induction approaches are too simple and inefficient. To automatically and efficiently induct behavior in social networks, this article introduces trust agents and designs their features according to group behavior features. In addition, a dynamics control mechanism can be generated to coordinate participant behaviors in social networks to avoid a specific restricted negative group behavior. This article investigates the importance of the endogenous selection of partners for trust and cooperation in market exchange situations, where there is information asymmetry between investors and trustees. We created an experimental-data driven agent-based model where the endogenous link between interaction outcome and social structure formation was examined starting from heterogeneous agent behaviour. By testing various social structure configurations, we showed that dynamic networks lead to more cooperation when agents can create more links and reduce exploitation opportunities by free riders. Furthermore, we found that the endogenous network formation was more important for cooperation than the type of network. Our results cast serious doubt about the static view of network structures on cooperation and can provide new insights into market efficiency. EXISTING SYSTEMS Online behavioral analysis and modeling has aroused considerable interest from closely related research fields such as data mining, machine learning, and information retrieval. This special issue provides a forum for researchers in behavior analysis to review pressing needs, discuss challenging research issues, and showcase state-of-the-art research and development in modern Web platforms. Research on network group behavior tendency generally can be divided into two areas: negative tendencies and hot-issue tendencies. For a negative tendency in group behavior, Yiting Zhang explained why violent behavior exists on the Internet and proposed countermeasure research to avoid it. PROPOSED SYSTEMS In Proposed systems by focusing on short texts published on social networks, one group of researchers proposed a biterm topic model that learns behavior topics by directly modeling the generation of word co-occurrence patterns (that is, biterms) in the corpus. The core problem of behavior induction in this article is as follows: with some restricted behaviors predetermined, how to induct participants in social networks to avoid these behaviors? There are all kinds of interaction relations between participants in social networks, but the most important one is trust. Abstractly, trust is the measure taken by one party about the willingness and ability of another party to act in the interest of the former party in a certain situation. However, there’s still no research on trust related to behavior induction in social networks—in particular, how to design features that make trust agents trusted by participants, maximize the effect of participant behaviors, and enhance the effectiveness of behavior induction. System Configuration: H/W System Configuration: Processor - Pentium –III 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 S/W System Configuration:  Operating System :Windows95/98/2000/XP  Application Server : Tomcat5.0/6.X  Front End : HTML, Java, Jsp  Scripts : JavaScript.  Server side Script : Java Server Pages.  Database : Mysql  Database Connectivity : JDBC. CONCLUSION: Now that we’ve proposed and experimentally validated our trust agent-based social behavior induction approach. In future work we’ll introduce Latent Dirichlet Allocation to abstract the behavior features of users in social networks, such as Twitter. We can construct links in behavior feature-driven social networks using the Pearson similarity of users’ behavior features.The explicit formulation of trust, reputation, and related quantities suggests a straightforward implementation of the model in a multi-agent environment.
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