Review on Seuring Data by Using Data Leakage Prevention and Detection

Today?s life everything including digital economy, data enter and leaves cyberspace at record rates. A typical enterprise sends and receives millions of email messages and downloads, saves, and transfers thousands of files via various channels on a daily basis. Enterprises also hold sensitive data that customers, business partners, regulators, and shareholders expect them to protect. While doing business we need to maintain the sensitive and confidential data. If the confidential data is leaked from the organization then it may influence on the organization heath. So preventing the data many vendors currently offer data leak prevention and detection products; surprisingly, however, there is one technique which is data leak prevention and detection, in this paper review on that Data Leak Prevention and Detection method. Here first term is data leak. Data leaks involve the release of sensitive information to an third party which is unauthorized user intentionally. Data leakage is the unauthorized transmission of data or information within an organization or from an organization to the external destination. The data stored in any device can be leaked in two ways; if the system is hacked or if the internal resources intentionally or unintentionally make the data public. Therefore, organizations should take measures to understand the sensitive data they hold, how it?s controlled, and how to prevent it from being leaked or compromised. So that purpose in this review data is preventing by using different technique of data leak prevention and detection

Data Leak Detection As a Service: Challenges and Solutions

We describe a network-based data-leak detection (DLD) technique, the main feature of which is that the detection does not require the data owner to reveal the content of the sensitive data. Instead, only a small amount of specialized digests are needed. Our technique – referred to as the fuzzy fingerprint – can be used to detect accidental data leaks due to human errors or application flaws. The privacy-preserving feature of our algorithms minimizes the exposure of sensitive data and enables the data owner to safely delegate the detection to others.We describe how cloud providers can offer their customers data-leak detection as an add-on service with strong privacy guarantees. We perform extensive experimental evaluation on the privacy, efficiency, accuracy and noise tolerance of our techniques. Our evaluation results under various data-leak scenarios and setups show that our method can support accurate detection with very small number of false alarms, even when the presentation of the data has been transformed. It also indicates that the detection accuracy does not degrade when partial digests are used. We further provide a quantifiable method to measure the privacy guarantee offered by our fuzzy fingerprint framework

Policy-agnostic programming on the client-side

Browser security has become a major concern especially due to web pages becoming more complex. These web applications handle a lot of information, including sensitive data that may be vulnerable to attacks like data exfiltration, cross-site scripting (XSS), etc. Most modern browsers have security mechanisms in place to prevent such attacks but they still fall short in preventing more advanced attacks like evolved variants of data exfiltration. Moreover, there is no standard that is followed to implement security into the browser. A lot of research has been done in the field of information flow security that could prove to be helpful in solving the problem of securing the client-side. Policy- agnostic programming is a programming paradigm that aims to make implementation of information flow security in real world systems more flexible. In this paper, we explore the use of policy-agnostic programming on the client-side and how it will help prevent common client-side attacks. We verify our results through a client-side salary management application. We show a possible attack and how our solution would prevent such an attack

Characterizing Location-based Mobile Tracking in Mobile Ad Networks

Mobile apps nowadays are often packaged with third-party ad libraries to monetize user data

Constraining application behaviour by generating languages

Writing a platform for reactive applications which enforces operational constraints is difficult, and has been approached in various ways. In this experience report, we detail an approach using an embedded DSL which can be used to specify the structure and permissions of a program in a given application domain. Once the developer has specified which components an application will consist of, and which permissions each one needs, the specification itself evaluates to a new, tailored, language. The final implementation of the application is then written in this specialised environment where precisely the API calls associated with the permissions which have been granted, are made available. Our prototype platform targets the domain of mobile computing, and is implemented using Racket. It demonstrates resource access control (e.g., camera, address book, etc.) and tries to prevent leaking of private data. Racket is shown to be an extremely effective platform for designing new programming languages and their run-time libraries. We demonstrate that this approach allows reuse of an inter-component communication layer, is convenient for the application developer because it provides high-level building blocks to structure the application, and provides increased control to the platform owner, preventing certain classes of errors by the developer.Comment: 8 pages, 8th European Lisp Symposiu