Relevant bibliographies by topics / Security of private data

Academic literature on the topic 'Security of private data'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Security of private data.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Security of private data"

1

Kapil, Gayatri, Alka Agrawal, and R. A. Khan. "Big Data Security and Privacy Issues." Asian Journal of Computer Science and Technology 7, no. 2 (August 5, 2018): 128–32. http://dx.doi.org/10.51983/ajcst-2018.7.2.1861.

Full text
Abstract:
Big data gradually become a hot topic of research and business and has been growing at exponential rate. It is a combination of structured, semi-structured & unstructured data which is generated constantly through various sources from different platforms like web servers, mobile devices, social network, private and public cloud etc. Big data is used in many organisations and enterprises, big data security and privacy have been increasingly concerned. However, there is a clear contradiction between the large data security and privacy and the widespread use of big data. In this paper, we have indicated challenges of security and privacy in big data. Then, we have presented some possible methods and techniques to ensure big data security and privacy.
APA, Harvard, Vancouver, ISO, and other styles
2

Alqadi, Ziad, and Mohammad S. Khrisat. "DATA STEGANOGRAPHY USING EMBEDDED PRIVATE KEY." International Journal of Engineering Technologies and Management Research 7, no. 9 (September 21, 2020): 31–38. http://dx.doi.org/10.29121/ijetmr.v7.i9.2020.782.

Full text
Abstract:
LSB2 method of data steganography is one of the most popular methods used to hide secret messages in digital color image. This method keeps the quality of the holding image high but it is not secure and it can be easily hacked. In this paper a method of improving the security of LSB2 method will be proposed, tested and implemented. The added security issues are simple and do require extra memory and time for execution. An embedded key will be extracted from the holding image to encrypt the message, this key will be variable and depends on the selected covering image, selected message length and selected position in the image where to extract the embedded key; the selected position and message length will form a private key to enhance LSB2 security.
APA, Harvard, Vancouver, ISO, and other styles
3

Hussain, Md Equebal, and Mohammad Rashid Hussain. "Securing Cloud Data using RSA Algorithm." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 6, no. 4 (December 19, 2018): 96. http://dx.doi.org/10.3991/ijes.v6i4.9910.

Full text
Abstract:
security is one of the most important concern on cloud computing therefore institutions are hesitating to host their data over cloud. Not all data can be afforded to move on the cloud (example accounts data). The main purpose of moving data over cloud is to reduce cost (infrastructure and maintenance), faster performance, easy upgrade, storage capacity but at the same time security is major concern because cloud is not private but maintained by third party over the internet, security issues like privacy, confidentiality, authorization (what you are allowed to do), authentication (who you are) and accounting (what you actually do) will be encountered. Variety of encryption algorithms required for higher level of security. In this paper we try to provide solution for better security by proposing a combined method of key exchange algorithm with encryption technique. Data stored in cloud can be protected from hackers using proposed solution because even if transmitted key is hacked of no use without user’s private key.
APA, Harvard, Vancouver, ISO, and other styles
4

Srinivasu, N., Masood Sahil, Jeevan Francis, and Sure Pravallika. "Security enhanced using honey encryption for private data sharing in cloud." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 675. http://dx.doi.org/10.14419/ijet.v7i1.1.10826.

Full text
Abstract:
In today’s modern age technology as there is a production of vast amount of data, it is getting very difficult to store such a vast amount of information. The best way to store this huge data is on cloud. As nowadays business organisations are moving towards cloud to store their data, security remains the primary concern. Is the data securing enough on the cloud or not? One of the ways to secure data on cloud is by providing security on cloud through Honey Encryption. Juels&Ristenrpart introduced honey encryption and showed how to achieve message recovery security even in the face of attacks that can exhaustively try all likely keys. Honey Encryption is a new encryption scheme that ensures the messages decrypted with invalid keys yield a valid looking message. In this paper, we present our implementation of Honey Encryption and apply it to useful real-world scenarios such as providing security to files which are been saved in cloud. The files contain variety of information in it. We also provide assurance against brute force attacks.
APA, Harvard, Vancouver, ISO, and other styles
5

Gatkal, Suyog, Vinayak Dhage, Dhanashree Kalekar, and Sanket Ghadge. "Survey on Medical Data Storage Systems." International Journal of Soft Computing and Engineering 11, no. 1 (September 30, 2021): 44–48. http://dx.doi.org/10.35940/ijsce.a3528.0911121.

Full text
Abstract:
Nowadays digital data storage and digital communication are widely used in the healthcare sector. Since data in the digital form significantly easier to store, retrieve, manipulate, analyses, and manage. Also, digital data eliminate the threat of data loss considerably. These advantages pushing many hospitals to store their data digitally. But, as the patients reveal their private and important information to the doctor, it is very crucial to maintain the privacy, security, and reliability of the healthcare data. In this process of handling the data securely, several technologies are being used like cloud storage, data warehousing, blockchain, etc. The main aim of this survey is to study the different models and technologies in the healthcare sector and analyses them on different parameters like security, privacy, performance, etc. This study will help the new developing healthcare systems to choose appropriate technology and approach to build a more efficient, robust, secure, and reliable system.
APA, Harvard, Vancouver, ISO, and other styles
6

Deb, Nabamita, Mohamed A. Elashiri, T. Veeramakali, Abdul Wahab Rahmani, and Sheshang Degadwala. "A Metaheuristic Approach for Encrypting Blockchain Data Attributes Using Ciphertext Policy Technique." Mathematical Problems in Engineering 2022 (February 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/7579961.

Full text
Abstract:
Unlike public chains, the Alliance Blockchain Hyperledger Fabric has a member management service mechanism that may provide data isolation security at the channel level. However, because this data isolation security technique synchronizes plaintext data inside the channel, data leakage is still a possibility. Furthermore, in some fine-grained privacy protection circumstances, channel-based data access restriction is ineffective. In order to solve the data privacy security problems in the above-mentioned consortium chain superledger, a blockchain data attribute encryption scheme based on ciphertext policy is proposed. Combining the original Fabric Certificate Authority module in the Hyperledger, the proposed scheme can realize the user-level fine-grained security access to control blockchain data while also realizing the secure distribution of user attribute keys in the blockchain data attribute encryption scheme based on the ciphertext policy scheme. The security analysis of the scheme shows that the scheme achieves the security goals of attribute-based encryption user attribute private key secure distribution and data privacy protection. The scope of this research is that this study confirms that the solution’s architecture achieves fine-grained access control of private data on the Hyperledger Blockchain network and also the security objectives of secure transmission of user characteristic secret keys and data privacy protection. The performance analysis part also shows that the proposed scheme has good usability.
APA, Harvard, Vancouver, ISO, and other styles
7

Avant, Deborah, and Kara Kingma Neu. "The Private Security Events Database." Journal of Conflict Resolution 63, no. 8 (January 30, 2019): 1986–2006. http://dx.doi.org/10.1177/0022002718824394.

Full text
Abstract:
Since the 1990s, the private provision of military and security services has become a common feature of local, national, and transnational politics. The prevalence of private security has generated important questions about its consequences, but data to answer these questions are sparse. In this article, we introduce the Private Security Events Database (PSED) that traces the involvement of private military and security companies (PMSCs) in events in Africa, Latin America, and Southeast Asia from 1990 to 2012. We describe the PSED project, highlight its descriptive findings, conduct a replication and reanalysis of Akcinaroglu and Radziszewski’s contract data in Africa, and compare the two databases’ coverage of Sierra Leone from 1991 to 1997. Our analysis demonstrates new insights into the relationship between PMSCs and civil war duration, confirming a correlation between PMSC presence and shorter conflicts, but questioning the logic Akcinaroglu and Radziszewski propose. It also points to a number of productive paths for future research.
APA, Harvard, Vancouver, ISO, and other styles
8

Coutu, Sylvain, Inbal Becker-Reshef, Alyssa K. Whitcraft, and Chris Justice. "Food security: underpin with public and private data sharing." Nature 578, no. 7796 (February 2020): 515. http://dx.doi.org/10.1038/d41586-020-00241-y.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Hennessy, S. D., G. D. Lauer, N. Zunic, B. Gerber, and A. C. Nelson. "Data-centric security: Integrating data privacy and data security." IBM Journal of Research and Development 53, no. 2 (March 2009): 2:1–2:12. http://dx.doi.org/10.1147/jrd.2009.5429044.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Park, Young-Hoon, Yejin Kim, and Junho Shim. "Blockchain-Based Privacy-Preserving System for Genomic Data Management Using Local Differential Privacy." Electronics 10, no. 23 (December 3, 2021): 3019. http://dx.doi.org/10.3390/electronics10233019.

Full text
Abstract:
The advances made in genome technology have resulted in significant amounts of genomic data being generated at an increasing speed. As genomic data contain various privacy-sensitive information, security schemes that protect confidentiality and control access are essential. Many security techniques have been proposed to safeguard healthcare data. However, these techniques are inadequate for genomic data management because of their large size. Additionally, privacy problems due to the sharing of gene data are yet to be addressed. In this study, we propose a secure genomic data management system using blockchain and local differential privacy (LDP). The proposed system employs two types of storage: private storage for internal staff and semi-private storage for external users. In private storage, because encrypted gene data are stored, only internal employees can access the data. Meanwhile, in semi-private storage, gene data are irreversibly modified by LDP. Through LDP, different noises are added to each section of the genomic data. Therefore, even though the third party uses or exposes the shared data, the owner’s privacy is guaranteed. Furthermore, the access control for each storage is ensured by the blockchain, and the gene owner can trace the usage and sharing status using a decentralized application in a mobile device.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Security of private data"

1

Basciftci, Yuksel O. Basciftci. "Private and Secure Data Communication: Information Theoretic Approach." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1469137249.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Lai, Ka-ying. "Solving multiparty private matching problems using Bloom-filters." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37854847.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Lai, Ka-ying, and 黎家盈. "Solving multiparty private matching problems using Bloom-filters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37854847.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

DeYoung, Mark E. "Privacy Preserving Network Security Data Analytics." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82909.

Full text
Abstract:
The problem of revealing accurate statistics about a population while maintaining privacy of individuals is extensively studied in several related disciplines. Statisticians, information security experts, and computational theory researchers, to name a few, have produced extensive bodies of work regarding privacy preservation. Still the need to improve our ability to control the dissemination of potentially private information is driven home by an incessant rhythm of data breaches, data leaks, and privacy exposure. History has shown that both public and private sector organizations are not immune to loss of control over data due to lax handling, incidental leakage, or adversarial breaches. Prudent organizations should consider the sensitive nature of network security data and network operations performance data recorded as logged events. These logged events often contain data elements that are directly correlated with sensitive information about people and their activities -- often at the same level of detail as sensor data. Privacy preserving data publication has the potential to support reproducibility and exploration of new analytic techniques for network security. Providing sanitized data sets de-couples privacy protection efforts from analytic research. De-coupling privacy protections from analytical capabilities enables specialists to tease out the information and knowledge hidden in high dimensional data, while, at the same time, providing some degree of assurance that people's private information is not exposed unnecessarily. In this research we propose methods that support a risk based approach to privacy preserving data publication for network security data. Our main research objective is the design and implementation of technical methods to support the appropriate release of network security data so it can be utilized to develop new analytic methods in an ethical manner. Our intent is to produce a database which holds network security data representative of a contextualized network and people's interaction with the network mid-points and end-points without the problems of identifiability.
Ph. D.
APA, Harvard, Vancouver, ISO, and other styles
5

Huang, Xueli. "Achieving Data Privacy and Security in Cloud." Diss., Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/372805.

Full text
Abstract:
Computer and Information Science
Ph.D.
The growing concerns in term of the privacy of data stored in public cloud have restrained the widespread adoption of cloud computing. The traditional method to protect the data privacy is to encrypt data before they are sent to public cloud, but heavy computation is always introduced by this approach, especially for the image and video data, which has much more amount of data than text data. Another way is to take advantage of hybrid cloud by separating the sensitive data from non-sensitive data and storing them in trusted private cloud and un-trusted public cloud respectively. But if we adopt the method directly, all the images and videos containing sensitive data have to be stored in private cloud, which makes this method meaningless. Moreover, the emergence of the Software-Defined Networking (SDN) paradigm, which decouples the control logic from the closed and proprietary implementations of traditional network devices, enables researchers and practitioners to design new innovative network functions and protocols in a much easier, flexible, and more powerful way. The data plane will ask the control plane to update flow rules when the data plane gets new network packets with which it does not know how to deal with, and the control plane will then dynamically deploy and configure flow rules according to the data plane's requests, which makes the whole network could be managed and controlled efficiently. However, this kind of reactive control model could be used by hackers launching Distributed Denial-of-Service (DDoS) attacks by sending large amount of new requests from the data plane to the control plane. For image data, we divide the image is into pieces with equal size to speed up the encryption process, and propose two kinds of method to cut the relationship between the edges. One is to add random noise in each piece, the other is to design a one-to-one mapping function for each piece to map different pixel value into different another one, which cuts off the relationship between pixels as well the edges. Our mapping function is given with a random parameter as inputs to make each piece could randomly choose different mapping. Finally, we shuffle the pieces with another random parameter, which makes the problems recovering the shuffled image to be NP-complete. For video data, we propose two different methods separately for intra frame, I-frame, and inter frame, P-frame, based on their different characteristic. A hybrid selective video encryption scheme for H.264/AVC based on Advanced Encryption Standard (AES) and video data themselves is proposed for I-frame. For each P-slice of P-frame, we only abstract small part of them in private cloud based on the characteristic of intra prediction mode, which efficiently prevents P-frame being decoded. For cloud running with SDN, we propose a framework to keep the controller away from DDoS attack. We first predict the amount of new requests for each switch periodically based on its previous information, and the new requests will be sent to controller if the predicted total amount of new requests is less than the threshold. Otherwise these requests will be directed to the security gate way to check if there is a attack among them. The requests that caused the dramatic decrease of entropy will be filter out by our algorithm, and the rules of these request will be made and sent to controller. The controller will send the rules to each switch to make them direct the flows matching with the rules to honey pot.
Temple University--Theses
APA, Harvard, Vancouver, ISO, and other styles
6

Ma, Jianjie. "Learning from perturbed data for privacy-preserving data mining." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/Summer2006/j%5Fma%5F080406.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Lincoln, Laura Beth. "Symmetric private information retrieval via additive homomorphic probabilistic encryption /." Online version of thesis, 2006. https://ritdml.rit.edu/dspace/handle/1850/2792.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Molema, Karabo Omphile. "The conflict of interest between data sharing and data privacy : a middleware approach." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2415.

Full text
Abstract:
Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2016.
People who are referred to as data owners in this study, use the Internet for various purposes and one of those is using online services like Gmail, Facebook, Twitter and so on. These online services are offered by organizations which are referred to as data controllers. When data owners use these service provided by data controllers they usually have to agree to the terms and conditions which gives data controllers indemnity against any privacy issues that may be raised by the data owner. Data controllers are then free to share that data with any other organizations, referred to as third parties. Though data controllers are protected from lawsuits it does not necessarily mean they are free of any act that may be considered a privacy violation by the data owner. This thesis aims to arrive at a design proposition using the design science research paradigm for a middleware extension, specifically focused on the Tomcat server which is a servlet engine running on the JVM. The design proposition proposes a client side annotation based API to be used by developers to specify classes which will carry data outside the scope of the data controller's system to a third party system, the specified classes will then have code weaved in that will communicate with a Privacy Engine component that will determine based on data owner's preferences if their data should be shared or not. The output of this study is a privacy enhancing platform that comprises of three components the client side annotation based API used by developers, an extension to Tomcat and finally a Privacy Engine.
APA, Harvard, Vancouver, ISO, and other styles
9

Wernberg, Max. "Security and Privacy of Controller Pilot Data Link Communication." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-156337.

Full text
Abstract:
Newly implemented technologies within the aviation lack, according to recent studies, built in security measures to protect them against outside interference. In this thesis we study the security and privacy status of the digital wireless Controller Pilot Data Link Communication (CPDLC) used in air traffic management alongside other systems to increase the safety and traffic capacity of controlled airspaces. The findings show that CPDCL is currently insecure and exposed to attacks. Any solutions to remedy this must adhere to its low levels of performance. Elliptical Curve Cryptography, Protected ACARS and Host Identity Protocol have been identified as valid solutions to the system’s security drawbacks and all three are possible to implement in the present state of CPDLC.
APA, Harvard, Vancouver, ISO, and other styles
10

Gholami, Ali. "Security and Privacy of Sensitive Data in Cloud Computing." Doctoral thesis, KTH, Parallelldatorcentrum, PDC, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186141.

Full text
Abstract:
Cloud computing offers the prospect of on-demand, elastic computing, provided as a utility service, and it is revolutionizing many domains of computing. Compared with earlier methods of processing data, cloud computing environments provide significant benefits, such as the availability of automated tools to assemble, connect, configure and reconfigure virtualized resources on demand. These make it much easier to meet organizational goals as organizations can easily deploy cloud services. However, the shift in paradigm that accompanies the adoption of cloud computing is increasingly giving rise to security and privacy considerations relating to facets of cloud computing such as multi-tenancy, trust, loss of control and accountability. Consequently, cloud platforms that handle sensitive information are required to deploy technical measures and organizational safeguards to avoid data protection breakdowns that might result in enormous and costly damages. Sensitive information in the context of cloud computing encompasses data from a wide range of different areas and domains. Data concerning health is a typical example of the type of sensitive information handled in cloud computing environments, and it is obvious that most individuals will want information related to their health to be secure. Hence, with the growth of cloud computing in recent times, privacy and data protection requirements have been evolving to protect individuals against surveillance and data disclosure. Some examples of such protective legislation are the EU Data Protection Directive (DPD) and the US Health Insurance Portability and Accountability Act (HIPAA), both of which demand privacy preservation for handling personally identifiable information. There have been great efforts to employ a wide range of mechanisms to enhance the privacy of data and to make cloud platforms more secure. Techniques that have been used include: encryption, trusted platform module, secure multi-party computing, homomorphic encryption, anonymization, container and sandboxing technologies. However, it is still an open problem about how to correctly build usable privacy-preserving cloud systems to handle sensitive data securely due to two research challenges. First, existing privacy and data protection legislation demand strong security, transparency and audibility of data usage. Second, lack of familiarity with a broad range of emerging or existing security solutions to build efficient cloud systems. This dissertation focuses on the design and development of several systems and methodologies for handling sensitive data appropriately in cloud computing environments. The key idea behind the proposed solutions is enforcing the privacy requirements mandated by existing legislation that aims to protect the privacy of individuals in cloud-computing platforms. We begin with an overview of the main concepts from cloud computing, followed by identifying the problems that need to be solved for secure data management in cloud environments. It then continues with a description of background material in addition to reviewing existing security and privacy solutions that are being used in the area of cloud computing. Our first main contribution is a new method for modeling threats to privacy in cloud environments which can be used to identify privacy requirements in accordance with data protection legislation. This method is then used to propose a framework that meets the privacy requirements for handling data in the area of genomics. That is, health data concerning the genome (DNA) of individuals. Our second contribution is a system for preserving privacy when publishing sample availability data. This system is noteworthy because it is capable of cross-linking over multiple datasets. The thesis continues by proposing a system called ScaBIA for privacy-preserving brain image analysis in the cloud. The final section of the dissertation describes a new approach for quantifying and minimizing the risk of operating system kernel exploitation, in addition to the development of a system call interposition reference monitor for Lind - a dual sandbox.
“Cloud computing”, eller “molntjänster” som blivit den vanligaste svenska översättningen, har stor potential. Molntjänster kan tillhandahålla exaktden datakraft som efterfrågas, nästan oavsett hur stor den är; dvs. molntjäns-ter möjliggör vad som brukar kallas för “elastic computing”. Effekterna avmolntjänster är revolutionerande inom många områden av datoranvändning.Jämfört med tidigare metoder för databehandling ger molntjänster mångafördelar; exempelvis tillgänglighet av automatiserade verktyg för att monte-ra, ansluta, konfigurera och re-konfigurera virtuella resurser “allt efter behov”(“on-demand”). Molntjänster gör det med andra ord mycket lättare för or-ganisationer att uppfylla sina målsättningar. Men det paradigmskifte, sominförandet av molntjänster innebär, skapar även säkerhetsproblem och förutsätter noggranna integritetsbedömningar. Hur bevaras det ömsesidiga förtro-endet, hur hanteras ansvarsutkrävandet, vid minskade kontrollmöjligheter tillföljd av delad information? Följaktligen behövs molnplattformar som är såkonstruerade att de kan hantera känslig information. Det krävs tekniska ochorganisatoriska hinder för att minimera risken för dataintrång, dataintrångsom kan resultera i enormt kostsamma skador såväl ekonomiskt som policymässigt. Molntjänster kan innehålla känslig information från många olikaområden och domäner. Hälsodata är ett typiskt exempel på sådan information. Det är uppenbart att de flesta människor vill att data relaterade tillderas hälsa ska vara skyddad. Så den ökade användningen av molntjänster påsenare år har medfört att kraven på integritets- och dataskydd har skärptsför att skydda individer mot övervakning och dataintrång. Exempel på skyd-dande lagstiftning är “EU Data Protection Directive” (DPD) och “US HealthInsurance Portability and Accountability Act” (HIPAA), vilka båda kräverskydd av privatlivet och bevarandet av integritet vid hantering av informa-tion som kan identifiera individer. Det har gjorts stora insatser för att utvecklafler mekanismer för att öka dataintegriteten och därmed göra molntjänsternasäkrare. Exempel på detta är; kryptering, “trusted platform modules”, säker“multi-party computing”, homomorfisk kryptering, anonymisering, container-och “sandlåde”-tekniker.Men hur man korrekt ska skapa användbara, integritetsbevarande moln-tjänster för helt säker behandling av känsliga data är fortfarande i väsentligaavseenden ett olöst problem på grund av två stora forskningsutmaningar. Fördet första: Existerande integritets- och dataskydds-lagar kräver transparensoch noggrann granskning av dataanvändningen. För det andra: Bristande kän-nedom om en rad kommande och redan existerande säkerhetslösningar för att skapa effektiva molntjänster.Denna avhandling fokuserar på utformning och utveckling av system ochmetoder för att hantera känsliga data i molntjänster på lämpligaste sätt.Målet med de framlagda lösningarna är att svara de integritetskrav som ställsi redan gällande lagstiftning, som har som uttalad målsättning att skyddaindividers integritet vid användning av molntjänster.Vi börjar med att ge en överblick av de viktigaste begreppen i molntjäns-ter, för att därefter identifiera problem som behöver lösas för säker databe-handling vid användning av molntjänster. Avhandlingen fortsätter sedan med en beskrivning av bakgrundsmaterial och en sammanfattning av befintligasäkerhets- och integritets-lösningar inom molntjänster.Vårt främsta bidrag är en ny metod för att simulera integritetshot vidanvändning av molntjänster, en metod som kan användas till att identifierade integritetskrav som överensstämmer med gällande dataskyddslagar. Vårmetod används sedan för att föreslå ett ramverk som möter de integritetskravsom ställs för att hantera data inom området “genomik”. Genomik handlari korthet om hälsodata avseende arvsmassan (DNA) hos enskilda individer.Vårt andra större bidrag är ett system för att bevara integriteten vid publice-ring av biologiska provdata. Systemet har fördelen att kunna sammankopplaflera olika uppsättningar med data. Avhandlingen fortsätter med att före-slå och beskriva ett system kallat ScaBIA, ett integritetsbevarande systemför hjärnbildsanalyser processade via molntjänster. Avhandlingens avslutan-de kapitel beskriver ett nytt sätt för kvantifiering och minimering av risk vid“kernel exploitation” (“utnyttjande av kärnan”). Denna nya ansats är ävenett bidrag till utvecklingen av ett nytt system för (Call interposition referencemonitor for Lind - the dual layer sandbox).

QC 20160516

APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Security of private data"

1

Salomon, David. Data Privacy and Security. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21707-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Rao, Udai Pratap, Sankita J. Patel, Pethuru Raj, and Andrea Visconti, eds. Security, Privacy and Data Analytics. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9089-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Privacy and data security law deskbook. [Frederick, MD]: Aspen Publishers, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Livraga, Giovanni, Vicenç Torra, Alessandro Aldini, Fabio Martinelli, and Neeraj Suri, eds. Data Privacy Management and Security Assurance. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47072-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Garcia-Alfaro, Joaquin, Guillermo Navarro-Arribas, Alessandro Aldini, Fabio Martinelli, and Neeraj Suri, eds. Data Privacy Management, and Security Assurance. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29883-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Garcia-Alfaro, Joaquin, Jordi Herrera-Joancomartí, Emil Lupu, Joachim Posegga, Alessandro Aldini, Fabio Martinelli, and Neeraj Suri, eds. Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17016-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Cavanagh, Thomas E. Preparedness in the private sector. [New York?]: The Conference Board, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

service), SpringerLink (Online, ed. Quantum private communication. Beijing: Higher Education Press, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Institute, Pennsylvania Bar. Privacy and security. [Mechanicsburg, Pa.] (5080 Ritter Rd., Mechanicsburg 17055-6903): Pennsylvania Bar Institute, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kaufman, Charlie. Network security: Private communication in a public world. Englewood Cliffs, New Jersey: PTR Prentice Hall, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Security of private data"

1

Zhu, Tianqing, Gang Li, Wanlei Zhou, and Philip S. Yu. "Differentially Private Data Analysis." In Advances in Information Security, 49–65. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62004-6_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Kursawe, Klaus, Gregory Neven, and Pim Tuyls. "Private Policy Negotiation." In Financial Cryptography and Data Security, 81–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11889663_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Alderman, James, Benjamin R. Curtis, Oriol Farràs, Keith M. Martin, and Jordi Ribes-González. "Private Outsourced Kriging Interpolation." In Financial Cryptography and Data Security, 75–90. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70278-0_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Goh, Eu-Jin, and Philippe Golle. "Event Driven Private Counters." In Financial Cryptography and Data Security, 313–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11507840_27.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Barth, Adam, Dan Boneh, and Brent Waters. "Privacy in Encrypted Content Distribution Using Private Broadcast Encryption." In Financial Cryptography and Data Security, 52–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11889663_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Abadi, Aydin, Sotirios Terzis, and Changyu Dong. "VD-PSI: Verifiable Delegated Private Set Intersection on Outsourced Private Datasets." In Financial Cryptography and Data Security, 149–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54970-4_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Ching Wa, Daniel. "Software and Data Segregation Security." In Security in the Private Cloud, 73–86. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315372211-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Resende, Amanda C. Davi, and Diego F. Aranha. "Faster Unbalanced Private Set Intersection." In Financial Cryptography and Data Security, 203–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58387-6_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Golle, Philippe. "A Private Stable Matching Algorithm." In Financial Cryptography and Data Security, 65–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11889663_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Camenisch, Jan, and Gregory M. Zaverucha. "Private Intersection of Certified Sets." In Financial Cryptography and Data Security, 108–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03549-4_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Security of private data"

1

MINCĂ, Ioana-Cătălina. "Private Data Security in Social Networks." In International Conference on Cybersecurity and Cybercrime. Romanian Association for Information Security Assurance, 2014. http://dx.doi.org/10.19107/cybercon.2014.06.

Full text
Abstract:
A role more and more important in our lives is occupied by social networks. In addition to the benefits we get, that is the ability to communicate, to make contact with others and in particular to socialize. They expose us to certain risks, however, if we consider the safety of our private data, in particular their system to ensure data security. This article aims to reveal the risks to which we are exposed, but also the solutions that exist to protect us.
APA, Harvard, Vancouver, ISO, and other styles
2

Hossain, Md Tamjid, Shahriar Badsha, and Haoting Shen. "Privacy, Security, and Utility Analysis of Differentially Private CPES Data." In 2021 IEEE Conference on Communications and Network Security (CNS). IEEE, 2021. http://dx.doi.org/10.1109/cns53000.2021.9705022.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Campbell, Zachary, Andrew Bray, Anna Ritz, and Adam Groce. "Differentially Private ANOVA Testing." In 2018 1st International Conference on Data Intelligence and Security (ICDIS). IEEE, 2018. http://dx.doi.org/10.1109/icdis.2018.00052.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bakas, Alexandros, Antonis Michalas, and Tassos Dimitriou. "Private Lives Matter." In CODASPY '22: Twelveth ACM Conference on Data and Application Security and Privacy. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3508398.3511514.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Eigner, Fabienne, Matteo Maffei, Ivan Pryvalov, Francesca Pampaloni, and Aniket Kate. "Differentially private data aggregation with optimal utility." In the 30th Annual Computer Security Applications Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2664243.2664263.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Mishra, Menaka, and A. K. Upadhyay. "Need of Private and Public Sector Information Security." In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, 2019. http://dx.doi.org/10.1109/confluence.2019.8776945.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Perrier, Victor, Hassan Jameel Asghar, and Dali Kaafar. "Private Continual Release of Real-Valued Data Streams." In Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2019. http://dx.doi.org/10.14722/ndss.2019.23535.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Lipps, Christoph, Sachinkumar Bavikatti Mallikarjun, Matthias Strufe, Christopher Heinz, Christoph Grimm, and Hans Dieter Schotten. "Keep Private Networks Private: Secure Channel-PUFs, and Physical Layer Security by Linear Regression Enhanced Channel Profiles." In 2020 3rd International Conference on Data Intelligence and Security (ICDIS). IEEE, 2020. http://dx.doi.org/10.1109/icdis50059.2020.00019.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Su, Dong, Jianneng Cao, Ninghui Li, Elisa Bertino, and Hongxia Jin. "Differentially Private K-Means Clustering." In CODASPY'16: Sixth ACM Conference on Data and Application Security and Privacy. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2857705.2857708.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Anandan, Balamurugan, and Chris Clifton. "Differentially Private Feature Selection for Data Mining." In CODASPY '18: Eighth ACM Conference on Data and Application Security and Privacy. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3180445.3180452.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Security of private data"

1

Warren, David R., Michael A. Bianco, Waheed Nasser, Richard R. Kusman, James Shafer, Jason Venner, Lovell Q. Walls, and Samson J. Wright. Agencies Need Improved Financial Data Reporting for Private Security Contractors. Fort Belvoir, VA: Defense Technical Information Center, October 2008. http://dx.doi.org/10.21236/ada489769.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Vonk, Jaynie. Going Digital: Privacy and data security under GDPR for quantitative impact evaluation. Oxfam, October 2019. http://dx.doi.org/10.21201/2019.5211.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Flagg, Melissa, and Zachary Arnold. A New Institutional Approach to Research Security in the United States: Defending a Diverse R&D Ecosystem. Center for Security and Emerging Technology, January 2021. http://dx.doi.org/10.51593/20200051.

Full text
Abstract:
U.S. research security requires trust and collaboration between those conducting R&D and the federal government. Most R&D takes place in the private sector, outside of government authority and control, and researchers are wary of federal government or law enforcement involvement in their work. Despite these challenges, as adversaries work to extract science, technology, data and know-how from the United States, the U.S. government is pursuing an ambitious research security initiative. In order to secure the 78 percent of U.S. R&D funded outside the government, authors Melissa Flagg and Zachary Arnold propose a new, public-private research security clearinghouse, with leadership from academia, business, philanthropy, and government and a presence in the most active R&D hubs across the United States.
APA, Harvard, Vancouver, ISO, and other styles
4

Mutis, Santiago. Privately Held AI Companies by Sector. Center for Security and Emerging Technology, October 2020. http://dx.doi.org/10.51593/20200019.

Full text
Abstract:
Understanding AI activity in the private sector is crucial both to grasping its economic and security implications and developing appropriate policy frameworks. This data brief shows particularly robust AI activity in software publishing and manufacturing, along with a high concentration of companies in California, Massachusetts and New York.
APA, Harvard, Vancouver, ISO, and other styles
5

Towery, Bobby A. Phasing Out Private Security Contractors in Iraq. Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada449415.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Dukarski, Jennifer. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles. SAE International, September 2021. http://dx.doi.org/10.4271/epr2021019.

Full text
Abstract:
Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used? What are the regulatory regimes that impact vehicular data use? Is the US close to harmonizing with other nations in the automotive data privacy? And will the risks of hackers lead to the “zombie car apocalypse” or to another avenue for ransomware? This report explores a number of these legal challenges and the unsettled aspects that arise in the world of automotive data
APA, Harvard, Vancouver, ISO, and other styles
7

Fang, L., ed. Security Framework for Provider-Provisioned Virtual Private Networks (PPVPNs). RFC Editor, July 2005. http://dx.doi.org/10.17487/rfc4111.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Efflandt, Scott L. Under Siege: How Private Security Companies Threaten the Military Profession. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada589194.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Brown, Charles W. Control of Private Security Contractors by the Joint Force Commander. Fort Belvoir, VA: Defense Technical Information Center, April 2008. http://dx.doi.org/10.21236/ada483966.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Mayle, Ashley. Blockchain based Communication Architectures with Applications to Private Security Networks. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1720211.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Security of private data' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography