scholarly journals Data Anonymization for Hiding Personal Tendency in Set-Valued Database Publication

2019 ◽  
Vol 11 (6) ◽  
pp. 138
Author(s):  
Dedi Gunawan ◽  
Masahiro Mambo
Keyword(s):  
The Other ◽  
Item Information ◽  
Sensitive Information ◽  
Random Data ◽  
Single Item ◽  
Data Anonymization ◽  
Individual Privacy ◽  
Privacy Breach ◽  
Marketing Analysis ◽  
Database Content

Set-valued database publication has been increasing its importance recently due to its benefit for various applications such as marketing analysis and advertising. However, publishing a raw set-valued database may cause individual privacy breach such as the leakage of sensitive information like personal tendencies when data recipients perform data analysis. Even though imposing data anonymization methods such as suppression-based methods and random data swapping methods to such a database can successfully hide personal tendency, it induces item loss from records and causes significant distortion in record structure that degrades database utility. To avoid the problems, we proposed a method based on swapping technique where an individual’s items in a record are swapped to items of the other record. Our swapping technique is distinct from existing one called random data swapping which yields much structure distortion. Even though the technique results in inaccuracy at a record level, it can preserve every single item in a database from loss. Thus, data recipients may obtain all the item information in an anonymized database. In addition, by carefully selecting a pair of records for item swapping, we can avoid excessive record structure distortion that leads to alter database content immensely. More importantly, such a strategy allows one to successfully hide personal tendency without sacrificing a lot of database utility.

Anonymizing Prescription Data Against Individual Privacy Breach in Healthcare Database

2021 ◽  
Author(s):  
Dedi Gunawan ◽  
Yusuf Sulistyo Nugroho ◽  
Maryam ◽  
Fatah Yasin Al Irsyadi
Keyword(s):  
Prescription Data ◽  
Healthcare Database ◽  
Individual Privacy ◽  
Privacy Breach

scholarly journals Ciphertext-Policy Attribute-based Encryption with Hidden Sensitive Policy for Recruitment in Smart City

2020 ◽  
Author(s):  
Fei Meng ◽  
Leixiao Cheng ◽  
Mingqiang Wang
Keyword(s):  
Smart City ◽  
End Users ◽  
The Other ◽  
Sensitive Information ◽  
Security Model ◽  
Access Policy ◽  
Computational Overhead ◽  
Attribute Based Encryption ◽  
Ciphertext Policy ◽  
Access Policies

Abstract Smart city, as a promising technical tendency, greatly facilitates citizens and generates innumerable data, some of which is very private and sensitive. To protect data from unauthorized users, ciphertext-policy attribute-based encryption (CP-ABE) enables data owner to specify an access policy on encrypted data. However, There are two drawbacks in traditional CP-ABE schemes. On the one hand, the access policy is revealed in the ciphertext so that sensitive information contained in the policy is exposed to anyone who obtains the ciphertext. For example, both the plaintext and access policy of an encrypted recruitment may reveal the company's future development plan. On the other hand, the decryption time scales linearly with the complexity of the access, which makes it unsuitable for resource-limited end users. In this paper, we propose a CP-ABE scheme with hidden sensitive policy for recruitment in smart city. Specifically, we introduce a new security model chosen sensitive policy security: two access policies embedded in the ciphertext, one is public and the other is sensitive and fully hidden, only if user's attributes satisfy the public policy, it's possible for him/her to learn about the hidden policy, otherwise he/she cannot get any information (attribute name and its values) of it. When the user satisfies both access policies, he/she can obtain and decrypt the ciphertext. Compared with other CP-ABE schemes, our scheme supports a more expressive access policy, since the access policy of their schemes only work on the ``AND-gate'' structure. In addition, intelligent devices spread all over the smart city, so partial computational overhead of encryption of our scheme can be outsourced to these devices as fog nodes, while most part overhead in the decryption process is outsourced to the cloud. Therefore, our scheme is more applicable to end users with resource-constrained mobile devices. We prove our scheme to be selective secure under the decisional bilinear Diffie-Hellman (DBDH) assumption.

Toward a Deeper Understanding of Personnel Anomaly Detection

2011 ◽  
pp. 206-215
Author(s):  
Shuyuan Mary Ho
Keyword(s):  
Anomaly Detection ◽  
Behavioral Outcomes ◽  
Sensitive Information ◽  
Potential Threat ◽  
Insider Threats ◽  
Internal Resources ◽  
Corporate Security ◽  
Systems Perspective ◽  
Individual Privacy ◽  
Over Time

Recent threats to prominent organizations have greatly increased social awareness of the need for information security. Many measures have been designed and developed to guard against threats from outsider attacks. Technologies are commonly implemented to actively prohibit unauthorized connection and/or limit access to corporate internal resources; however, threats from insiders are even more subtle and complex. Personnel whom are inherently trusted have valuable internal corporate knowledge that could impact profits or organizational integrity. They are often a source of potential threat within the corporation, through leaking or damaging confidential and sensitive information—whether intentionally or unintentionally. Identifying and detecting anomalous personnel behavior and potential threats are concomitantly important. It can be done by observation and evaluation of communicated intentions and behavioral outcomes of the employee over time. While human observations are subject to fallibility and systems statistics are subject to false positives, personnel anomaly detection correlates observations on the change of personnel trustworthiness to provide for both corporate security and individual privacy. In this paper, insider threats are identified as one of the significant problems to corporate security. Some insightful discussions of personnel anomaly detection are provided, from both a social and a systems perspective.

An examination of the information disclosure behavior of infertility bloggers

2014 ◽  
Vol 66 (2) ◽  
pp. 175-201 ◽  
Author(s):  
Maria Knoll ◽  
Jenny Bronstein
Keyword(s):  
Information Disclosure ◽  
Design Methodology ◽  
The Other ◽  
High Rate ◽  
Sensitive Information ◽  
Self Disclosure ◽  
Content Type ◽  
Alternate Explanation ◽  
Infertility Treatments ◽  
Disclosure Patterns

Purpose – The study aimed to investigate the information disclosure behavior of women bloggers who suffer from infertility by examining their self-disclosure as it relates to the anonymity patterns they adopted. Design/methodology/approach – A survey was distributed to approximately 300 authors of infertility blogs, 135 bloggers answered the request to take part in the study. The survey gathered basic demographic and blogging practice data, and measured different elements of the bloggers' discursive and visual anonymity as well as their patters of self-disclosure. Findings – Findings reveal that the majority of respondents identify themselves on their blogs and only a small percentage decided to be totally anonymous, and about half of the bloggers post actual photos of themselves and their lives. The participants reported a high rate of self-disclosure, revealing sensitive information, letting their defenses down, disclosing highly intimate details about their lives, writing openly about their infertility treatments on their blog. No significant correlation was observed between visual and discursive anonymity and the perceived self-disclosure of participants. Results show that the more anonymous the bloggers are, the more afraid they become that their blog may be read by people they know offline. On the other hand, the more identifiable the bloggers are, the more willingness they show to share the content of their journal with people they know offline. The majority of participants expressed concerns that blogging could negatively impact their lives. Originality/value – This study explores an alternate explanation through the examination of the bloggers' self-disclosure patterns as they relate to the degree of anonymity adopted.

A Secure Protocol for High-Dimensional Big Data Providing Data Privacy

2021 ◽  
pp. 327-343
Author(s):  
Anitha J. ◽  
Prasad S. P.
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Privacy ◽  
Personal Information ◽  
Technological Development ◽  
High Dimensional ◽  
Sensitive Information ◽  
Data Anonymization ◽  
Secure Protocol ◽  
Data Owner

Due to recent technological development, a huge amount of data generated by social networking, sensor networks, internet, etc., adds more challenges when performing data storage and processing tasks. During PPDP, the collected data may contain sensitive information about the data owner. Directly releasing this for further processing may violate the privacy of the data owner, hence data modification is needed so that it does not disclose any personal information. The existing techniques of data anonymization have a fixed scheme with a small number of dimensions. There are various types of attacks on the privacy of data like linkage attack, homogeneity attack, and background knowledge attack. To provide an effective technique in big data to maintain data privacy and prevent linkage attacks, this paper proposes a privacy preserving protocol, UNION, for a multi-party data provider. Experiments show that this technique provides a better data utility to handle high dimensional data, and scalability with respect to the data size compared with existing anonymization techniques.

scholarly journals Essay on Kolmogorov Law of Minus 5 over 3 Viewed with Golden Ratio

2013 ◽  
Vol 2013 ◽  
pp. 1-3 ◽  
Author(s):  
Ming Li ◽  
Wei Zhao
Keyword(s):  
Fractal Dimension ◽  
Energy Transfer ◽  
High Energy Physics ◽  
Golden Ratio ◽  
High Energy ◽  
Point Of View ◽  
The Other ◽  
Random Data ◽  
Random Functions ◽  
Energy Physics

The golden ratio is an astonishing number in high-energy physics, neutrino physics, and cosmology. The Kolmogorov −5/3 law plays a role in describing energy transfer of random data or random functions. The contributions of this essay are in twofold. One is to express the Kolmogorov −5/3 law by using the golden ratio. The other is to represent the fractal dimension of random data following the Kolmogorov −5/3 law with the golden ratio. It is our hope that this essay may be helpful to provide a new outlook of the Kolmogorov −5/3 law from the point of view of the golden ratio.

A Self-Relocation Based Method for Malware Detection

2012 ◽  
Vol 220-223 ◽  
pp. 2688-2693
Author(s):  
Yu Zhang ◽  
Feng Xia
Keyword(s):  
Computer System ◽  
Malware Detection ◽  
The Self ◽  
The Other ◽  
The Internet ◽  
Sensitive Information ◽  
Malicious Software ◽  
Unauthorized Access ◽  
Base Address ◽  
Computer Operation

Malware (malicious software) is software designed to disrupt computer operation, gather sensitive information, or gain unauthorized access to a computer system. Most malwares propagate themselves throughout the Internet by self-relocation. Self-relocation is a built-in module in most malwares that gets the base address of the code to correctly infect the other programs. Since most legitimate computer programs do not need the self-relocate module, the detection of malware with self-relocation module can be viewed as a promising approach for malware detection. This paper presents a self-relocation based method for both known and previously unknown malwares. The experiments indicate that the proposed approach has better ability to detect known and unknown malwares than other methods.

scholarly journals Predictive privacy: towards an applied ethics of data analytics

2021 ◽  
Author(s):  
Rainer Mühlhoff
Keyword(s):  
Machine Learning ◽  
Data Protection ◽  
Data Analytics ◽  
Predictive Analytics ◽  
Applied Ethics ◽  
Big Data Analytics ◽  
Training Data ◽  
Sensitive Information ◽  
Ethical Implications ◽  
Individual Privacy

AbstractData analytics and data-driven approaches in Machine Learning are now among the most hailed computing technologies in many industrial domains. One major application is predictive analytics, which is used to predict sensitive attributes, future behavior, or cost, risk and utility functions associated with target groups or individuals based on large sets of behavioral and usage data. This paper stresses the severe ethical and data protection implications of predictive analytics if it is used to predict sensitive information about single individuals or treat individuals differently based on the data many unrelated individuals provided. To tackle these concerns in an applied ethics, first, the paper introduces the concept of “predictive privacy” to formulate an ethical principle protecting individuals and groups against differential treatment based on Machine Learning and Big Data analytics. Secondly, it analyses the typical data processing cycle of predictive systems to provide a step-by-step discussion of ethical implications, locating occurrences of predictive privacy violations. Thirdly, the paper sheds light on what is qualitatively new in the way predictive analytics challenges ethical principles such as human dignity and the (liberal) notion of individual privacy. These new challenges arise when predictive systems transform statistical inferences, which provide knowledge about the cohort of training data donors, into individual predictions, thereby crossing what I call the “prediction gap”. Finally, the paper summarizes that data protection in the age of predictive analytics is a collective matter as we face situations where an individual’s (or group’s) privacy is violated using data other individuals provide about themselves, possibly even anonymously.

scholarly journals Ciphertext-Policy Attribute-based Encryption with Hidden Sensitive Policy from Keyword Search Techniques in Smarty City

2020 ◽  
Author(s):  
Fei Meng ◽  
Leixiao Cheng ◽  
Mingqiang Wang
Keyword(s):  
Smart City ◽  
Keyword Search ◽  
End Users ◽  
The Other ◽  
Sensitive Information ◽  
Security Model ◽  
Access Policy ◽  
Attribute Based Encryption ◽  
Ciphertext Policy ◽  
Access Policies

Abstract Smart city greatly facilitates citizens and generates innumerable data, some of which is very private and sensitive. To protect data from unauthorized users, ciphertext-policy attribute-based encryption (CP-ABE) enables data owner to specify an access policy on encrypted data. However, There are two drawbacks in traditional CP-ABE schemes. On the one hand, the access policy is revealed in the ciphertext so that sensitive information contained in the policy is exposed to anyone who obtains the ciphertext. For example, both the plaintext and access policy of an encrypted recruitment may reveal the company’s future development plan. On the other hand, the decryption time scales linearly with the complexity of the access, which makes it unsuitable for resource-limited end users. In this paper, we propose a CP-ABE scheme with hidden sensitive policy from keyword search (KS) techniques in smart city. Specifically, we introduce a new security model chosen sensitive policy security : two access policies embedded in the ciphertext, one is public and the other is sensitive and fully hidden, only if user’s attributes satisfy the public policy, it’s possible for him/her to learn about the hidden policy, otherwise he/she cannot get any information (attribute name and its values) of it. When the user satisfies both access policies, he/she can obtain and decrypt the ciphertext. Compared with other CP-ABE schemes, our scheme exploits KS techniques to achieve more expressive and efficient, while the access policy of their schemes only work on the “AND-gate” structure or their ciphertext size or decryption time maybe super-polynomial. In addition, intelligent devices spread all over the smart city, so partial computational overhead of encryption of our scheme can be outsourced to these devices as fog nodes, while most part overhead in the decryption process is outsourced to the cloud.Therefore, our scheme is more applicable to end users with resource-constrained mobile devices. We prove our scheme to be selective secure under the decisional bilinear Diffie-Hellman (DBDH) assumption.

scholarly journals A Survey of Different Steganography Technique using Cryptographic Algorithm

2018 ◽  
Vol 7 (2) ◽  
pp. 40-43
Author(s):  
Prakhar Agrawal ◽  
Arvind Upadhyay
Keyword(s):  
Data Security ◽  
Image Steganography ◽  
The Other ◽  
Sensitive Information ◽  
Hidden Information ◽  
Cipher Text ◽  
Other Hand ◽  
Cryptographic Algorithm ◽  
Secure Data ◽  
Hide Data

Steganography and cryptography are two major aspects of data security . In this paper we are going to provide the survey of different techniques of LSB based Steganography that used cryptography algorithms to secure sensitive information. Steganography is used to hide data and Cryptography is used to encrypt the data. Although cryptography and steganography individually can provide data security, every of them has a drawback. Drawback associated with Cryptography is that, the cipher text looks meaningless, so the unintended user can interrupt the transmission or make more careful checks on the information from the sender to the receiver. Drawback associated with Steganography is that when the presence of hidden information is revealed or even suspected, the message is become known[1].By combining these two methods we can solve both of the above problem. First we encrypt the data using any cryptography technique and then embed the encrypted text into the image. Steganography is the process which hides the presence of secure data during communication. On the other hand cryptography is encrypting and decrypting of secure data and information with a secrete key so that no one can be understand the message directly.

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