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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 ConfigurationH/W System Configuration:Processor - Pentium –IIISpeed - 1.1 GhzRAM - 256 MB(min)Hard Disk - 20 GBFloppy Drive - 1.44 MBKey Board - Standard Windows KeyboardMouse - Two or Three Button MouseMonitor - SVGAS/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 –IIISpeed - 1.1 GhzRAM - 256 MB(min)Hard Disk - 20 GBKey Board - Standard Windows KeyboardMouse - Two or Three Button MouseMonitor - 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.
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IEEE 2016 - 2017 Matlab Image Processing TitlesS.No Project Titles 1. Data-driven Soft Decoding of Compressed Images in Dual Transform-Pixel Domain 2. Double-Tip Arte fact Removal from Atomic Force Microscopy Images 3. Quaternion Collaborative and Sparse Representation With Application to Color Face Recognition 4. Multi-Level Canonical Correlation Analysis for Standard-Dose PET Image Estimation 5. Weakly Supervised Fine-Grained Categorization with Part-Based Image Representation 6. Robust Visual Tracking via Convolutional Networks without Training 7. Context-based prediction filtering of impulse noise images 8. Predicting the Forest Fire Using Image Processing 9. A Review Paper on detection of Glaucoma using Retinal Fundus Images 10. Performance Analysis of Filters on Complex Images for Text Extraction through Binarization 11. Automated Malaria Detection from Blood Samples Using Image Processing 12. Learning Invariant Color Features for Person Re-Identification 13. A Diffusion and Clustering-based Approach for Finding Coherent Motions and Understanding Crowd Scenes 14. Automatic Design of Color Filter Arrays in The Frequency Domain 15. Learning Iteration-wise Generalized Shrinkage-Thresholding Operators for Blind Deconvolution 16. Image Segmentation Using Parametric Contours With Free Endpoints 17. CASAIR: Content and Shape-Aware Image Retargeting and Its Applications 18. Texture classification using Dense Micro-block Difference 19. Statistical performance analysis of a fast super-resolution technique using noisy translations 20. Trees Leaves Extraction In Natural Images Based On Image segmentation and generating Its plant details
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IEEE 2016 -2017 BIG DATA ANDROID DOTNET JAVA TITLESBIG DATA1. FiDoop: Parallel Mining of Frequent Itemsets Using MapReduce.ss2. Self-Healing in Mobile Networks with Big Data.ANDROID1. An Exploration of Geographic Authentication Schemes.2. Intelligent Hands Free Speech based SMS System on Android.3. PassBYOP: Bring Your Own Picture for Securing Graphical Passwords.4. Privacy-Preserving Location Sharing Services for Social Networks.5. SBVLC: Secure Barcode-based Visible Light Communication for Smartphones.6. A Shoulder Surfing Resistant Graphical Authentication System.7. A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies.8. STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users.9. Understanding Smartphone Sensor and App Data for Enhancing the Security of Secret Questions..NET1. Attribute-based Access Control with Constant-size Ciphertext in Cloud Computing.2. Attribute-Based Data Sharing Scheme Revisited in Cloud Computing3. Catch You if You Misbehave: Ranked Keyword Search Results Verification in Cloud Computing4. CDStore: Toward Reliable, Secure, and Cost-Efficient Cloud Storage via Convergent Dispersal5. Cloud workflow scheduling with deadlines and time slot availability6. Dynamic and Public Auditing with Fair Arbitration for Cloud Data7. Dynamic Proofs of Retrievability for Coded Cloud Storage Systems8. Enabling Cloud Storage Auditing with Verifiable Outsourcing of Key Updates9. Identity-Based Encryption with Cloud Revocation Authority and Its Applications10. Identity-Based Proxy-Oriented Data Uploading and Remote Data Integrity Checking in Public Cloud11. MMBcloud-tree: Authenticated Index for Verifiable Cloud Service Selection12. Prioritization of Overflow Tasks to Improve Performance of Mobile Cloud13. Providing User Security Guarantees in Public Infrastructure Clouds14. Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys15. Reversible Data Hiding in Encrypted Images by Reversible Image Transformation16. Searchable Attribute-Based Mechanism with Efficient Data Sharing for Secure Cloud Storage17. Secure Data Sharing in Cloud Computing Using Revocable-Storage Identity-Based Encryption18. Service Usage Classification with Encrypted Internet Traffic in Mobile Messaging Apps19. Shadow Attacks based on Password Reuses: A Quantitative Empirical Analysis20. A Performance Evaluation of Machine Learning-Based Streaming Spam Tweets DetectionJAVA1. A Locality Sensitive Low-Rank Model for Image Tag Completion2. A Shoulder Surfing Resistant Graphical Authentication System3. DeyPoS: Deduplicatable Dynamic Proof of Storage for Multi-User Environments4. Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search5. KSF-OABE: Outsourced Attribute-Based Encryption with Keyword Search Function for Cloud Storage6. Mining User-Aware Rare Sequential Topic Patterns in Document Streams7. Mitigating Cross-Site Scripting Attacks with a Content Security Policy8. Practical Approximate k Nearest Neighbor Queries with Location and Query Privacy9. Quality-Aware Subgraph Matching Over Inconsistent Probabilistic Graph Databases10. SecRBAC: Secure data in the Clouds11. Tag Based Image Search by Social Re-rankingCLOUD COMPUTING1. Cost Minimization for Rule Caching in Software Defined Networking.2. Performance Enhancement of High-Availability Seamless Redundancy (HSR) Networks Using OpenFlow.3. Data Plane and Control Architectures for 5G Transport Networks.4. HBD: Towards Efficient Reactive Rule Dispatching in Software-Defined Networks.5. SDN-based Application Framework for Wireless Sensor and Actor Networks.6. Geo-Social Distance-based Data Dissemination for Socially Aware Networking.7. An Open-Source Wireless Mesh Networking Module for Environmental Monitoring.8. Hybrid IP/SDN networking: open implementation and experiment management tools.9. Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges.10. Cloud Computing-Based Forensic Analysis for Collaborative Network Security Management System.NETWORK SECUIRTY1. Collaborative Network Security in Multi-Tenant Data Center for Cloud Computing.DATA MINING1. Systematic Determination of Discrepancies Across Transient Stability Software Packages.2. Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.3. Teaching Network Security With IP Darkspace Data.4. A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection.5. Mining High Utility Patterns in One Phase without Generating Candidates.6. An Improved String-Searching Algorithm and Its Application in Component Security Testing.
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CLOUD COMPUTING PROJECT ABSTRACT 2016-2017 COST MINIMIZATION FOR RULE CACHING IN SOFTWARE DEFINED NETWORKING ABSTRACT:Software-Defined Networking (SDN) is an emerging network paradigm that simplifies network management by decoupling the control plane and data plane, such that switches become simple data forwarding devices and network management is controlled by logically centralized servers. In SDN-enabled networks, network flow is managed by a set of associated rules that are maintained by switches in their local Ternary Content Addressable Memories (TCAMs) which support high-speed parallel lookup on wildcard patterns. Since TCAM is an expensive hardware and extremely power-hungry, each switch has only limited TCAM space and it is inefficient and even infeasible to maintain all rules at local switches. On the other hand, if we eliminate TCAM occupation by forwarding all packets to the centralized controller for processing, it results in a long delay and heavy processing burden on the controller. In this paper, we strive for the fine balance between rule caching and remote packet processing by formulating a minimum weighted flow provisioning (MWFP) problem with an objective of minimizing the total cost of TCAM occupation and remote packet processing. We propose an efficient offline algorithm if the network traffic is given, otherwise, we propose two online algorithms with guaranteed competitive ratios. Finally, we conduct extensive experiments by simulations using real network traffic traces. The simulation results demonstrate that our proposed algorithms can significantly reduce the total cost of remote controller processing and TCAM occupation, and the solutions obtained are nearly optimal.
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JAVA PROJECTS ABSTRACT 2016-2017 COST MINIMIZATION FOR RULE CACHING IN SOFTWARE DEFINED NETWORKING ABSTRACT: Software-defined networking (SDN) is an emerging network paradigm that simplifies network management by decoupling the control plane and data plane, such that switches become simple data forwarding devices and network management is controlled by logically centralized servers. In SDN-enabled networks, network flow is managed by a set of associated rules that are maintained by switches in their local Ternary Content Addressable Memories (TCAMs) which support high-speed parallel lookup on wildcard patterns. Since TCAM is an expensive hardware and extremely power-hungry, each switch has only limited TCAM space and it is inefficient andeven infeasible to maintain all rules at local switches. On the other hand, if we eliminate TCAM occupation by forwarding all packets to the centralized controller for processing, it results in a long delay and heavy processing burden on the controller. In this paper, we strive for the fine balance between rule caching and remote packet processing by formulating a minimum weighted flow provisioning (MWFP) problem with an objective of minimizing the total cost of TCAM occupation and remote packet processing. We propose an efficient offline algorithm if the network traffic is given, otherwise, we propose two online algorithms with guaranteed competitive ratios. Finally, we conduct extensive experiments by simulations using real network traffic traces. The simulation results demonstrate that our proposed algorithms can significantly reduce the total cost of remote controller processing and TCAM occupation, and the solutionsobtained are nearly optimal.Existing System: That switches usually set an expiration time for rules, which defines the maximum rule maintenance time when no packet of associated flow arrives. the first packet experiences the delay of remote processing at the controller, and the rest will be processed by local rules at switches. However, for burst transmission, the corresponding rules cached in switches will be removed between two batches of packets if their interval is greater than the rule expiration time. As a result, remote packet processing would be incurred by the first packet of each batch, leading to a long delay and high processing burden on the controller. A simple method to reduce the overhead of remote processing is to cache rules at switches within the lifetime of network flow, ignoring the rule expiration time. we conduct extensive simulations using real network traffic traces to evaluate the performance of our proposals. The simulation results demonstrate that our proposed algorithms can significantly reduce the total cost of remote controller processing and TCAM occupation, and the solutions obtained are nearly optimal.Disadvantage: In that case, rules can be cached in forwarding table as many as possible. This abstraction saves TCAMs space, but the packet processing speed in switch is a bottleneck. The endpoints rules are pre-computed and cached in authority switches. Once the first packet of a new microflow arrives the switch, the desired rules are reactively installed, from authority switches rather than the controller. In this way, the flow setup time can be significantly reduced.
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