Data leakage

Çalışan bir sistem dışarıya belli oranlarda radyo dalga emisyonu, ışık, ses veya titreşim gönderir. Bu sinyaller sistemin o anki çalışması ile ilgili bilgi veren anlamlı bir yapıdadır.

Örneğin TEMPEST güvenliği alınmamış bir bilgisayarın veya cihazın o anda hangi veriyi işlediği veya hangi komutu çalıştırdığı hiçbir fiziksel bağlantı kurulmadan uzaktan öğrenilebilir.

Elektrik ile çalışan tüm cihazlar dış ortama elektro manyetik bir alan/girişim yayarlar. (EMI) Bu giriş cihazın o anda elektriksel olarak işlediği verinin birebir anlamlı kopyasıdır.

The parrhesiastic spaces brought about by networked technologies have transformed what counts as truth-telling today. While the notion of truth has been thoroughly scrutinized within organization theory as well in studies on the ethics of whistle-blowing, less attention has been devoted to how new and emerging practices of truth-telling are related to socio-technological imaginaries-that is, the way social structures such as gender, sexuality and race affect and are affected by technological assemblages, especially infrastructures of information. This article argues that networked forms of truth-telling are enmeshed in technological imaginaries where gender and sexuality are symbolically and materially encoded. Prompted by recent cases of information disclosure, the article theorizes how technological infrastructures, gendered imaginaries and economic regimes come together to shape, complicate and ultimately define who counts as a truth-teller within parrhesiastic networked spaces. Drawing on feminist infrastructure and media theories, the article discusses normative distinctions between whistle-blowers, leakers and hackers to explore how their infrastructural imaginaries map onto contemporary communication networks, the gender politics of organizing information, and the conditions of what counts as truth. The article argues that attending to infrastructural imaginaries and their intersections with gendered imaginaries can not only help us to make sense of how the gendering of truth-telling operates in highly networked spaces, but can also aid us in devising improved conditions for truths to be told in organizational spaces. Ultimately, infrastructures matter because they fundamentally determine whose knowledge and labour are socially valued, and whose voices come to count in public life.

The amount of data in world is increasing rapidly. Data is developing as a direct result of utilization of web and increased usage of mobile phones. Big data is an assortment of data sets which is extremely enormous in size. Presently, Big data is one of the most talked theme in IT industry. It will produce significant jobs in future. Big data changes how data is seen and utilized. A portion of the applications are in areas such as healthcare, traffic management, banking, retail, education, etc. organizations are turning out to be more adaptable and more open. As the big data is getting bigger various challenges are arriving infront of it. One of the major challenges infront of big data are information overload. I have discussed an efficient way called DOD (Data on Demand) which helps filter data noice.

Industrial Control Systems (ICS) are used for controlling, operating and monitoring industrial processes. That current ICS infrastructures and elements are not amply secured against cyber threats in context of security. Woefully, due to the specific nature of these systems, the application of common security countermeasures is often not effective. We suggest building tools and mechanisms to improve the security and awareness in ICS. We discuss challenges and opportunities identified during a comprehensive analysis of ICS data system resources. Industrial processes are more exposed to cybersecurity risks through a range of vulnerabilities in software and hardware technologies as well as weaknesses inherited from the legacy design of ICS networks.

Data leakage means sending confidential data to an unauthorized person. Nowadays, identifying confidential data is a big challenge for the organizations. We developed a system by using data mining techniques, which identifies confidential data of an organization. First, we create clusters for the training data set. Next, identify confidential terms and context terms for each cluster. Finally, based on the confidential terms and context terms, the confidentiality level of the detected document calculated in terms of score. If the score of the detected document beyond a predefined threshold, then the document is blocked and marked as a confidential.

Cloud computing environment provides on-demand access to shared resources that can be managed with minimal interaction of cloud service provider and validated service to the user. Cloud storage can be either public or private. Data in the public storage can be viewed by all cloud users. The private data can be viewed by the authorized user only. This paper enhance the security of the cloud data using Advanced Encryption Standard (AES) encryption algorithm. Data owners are motivated to outsource their data in cloud servers for great convenience. Private data should be encrypted before outsourcing by using keys. Encryption is an important concept in cloud computing to maintain the database. Existing system maintained the database by providing password for files and documents. The proposed system provides keys to access the file and keys are maintained as private and keys are provided by the data owner. The paper focused ostrovsky scheme (private information retrieval) that allows a user to retrieve file without any information leakage. Experimental result are presented to test the security of AES algorithm and information leakage.

The Data Distributors organizations outsource their sensitive data to some outside trusted third party. The objective would be to detect when their sensitive data has been leaked by agents, and if possible to identify them. An application where the original sensitive data cannot be perturbed is considered; in some cases it is imperative not to modify the original distributor’s data. For such situations, one cannot modify the data, so one has to go by the method in which data alteration is not required. In this paper we have proposed a solution under such diverse situations. The goal is to estimate the likelihood that the leaked data came from the agents as opposed to other sources. Not only to this system wants to estimate the likelihood the agents leaked data, but it would also like to find out if one of them in particular was more likely to be the leaker. The data allocation strategies facilitate the distributor “intelligently” give data to agents. Fake objects are added to identify the guilty part, to address this problem four instances are specified. Depending on which the data request is provided; the type of data request either Explicit Data Request or Sample Data Request and with or without the fake objects are allowed.

Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, as no single point of attack can leak all a user's information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, to address this problem, we present Store-Sim, an information leakage-aware storage system in multi cloud. Store-Sim aims to store syntactically similar data on the same cloud, thus minimizing the user's information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity-preserving signatures for data chunks based on Min-Hash and Bloom filters, and design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluated our scheme using two real datasets from Wikipedia and GitHub. We show that our scheme can reduce information leakage by up to 60-70 Percent.