The Experts below are selected from a list of 348 Experts worldwide ranked by ideXlab platform
A Gupta - One of the best experts on this subject based on the ideXlab platform.
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Privacy Violation in limited disclosure of database having functional dependency
International Conference on Computer Control and Communication, 2009Co-Authors: A Gupta, Arnab Mondal, Ashish Singal, Atul MittalAbstract:Upholding the Privacy of data has gathered increased interest in the current industrial scenario. The databases that hold personal information and the individuals' choices of Privacy are often subjected to attacks from mischievous sources which try to access undisclosed data. The means used to achieve such ends may be in the form of complex queries that combine sensitive data with the non-sensitive ones. Access Control mechanisms are already in place to prevent such malicious accesses. But the problem is highly compounded when there is a functional dependency among some of the attributes of the data. In such cases often the disclosed data of one person allows the user to infer the undisclosed data of another person. In this paper we propose a model to prevent the breach of Privacy through such inference channels of functional dependency. Then we describe the architecture of our model and the corresponding implementation. Finally we carry out a performance analysis to evaluate the cost overheads of time and space and look out topics for future research.
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context honeypot a framework for anticipatory Privacy Violation
International Conference on Emerging Trends in Engineering and Technology, 2008Co-Authors: Shruti Gupta, V Goyal, A Gupta, R G S Damor, Sangeeta SabharwalAbstract:Honeypots have been studied in the network domain for detection and information collection against external threats in the past few years. They lure a potential attacker by simulating resources having vulnerabilities and observing the behavior of a potential attacker to identify him before a damaging attack takes place. A lot of work has been done in the area of Privacy and security in databases. Though the number of attacks and complexity for database attacks are increasing day by day, there has been no attempt to design honeypots for Privacy enforcing databases. The use of honeypots for databases would help in confirming the suspicion (malafide intention) of a suspicious user without leaking the target information (information which would fulfill the malafide intention) to the attacker. We propose a framework for database honeypots for certain types of attacks in Privacy context. The proposed honeypots for databases are termed as context honeypots.
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a system to test malafide intension based on Privacy Violation detection
International Conference on Digital Information Management, 2007Co-Authors: S K Gupta, S Dubey, V Goyal, A GuptaAbstract:As a response to serious Privacy concerns, various approaches have been proposed on Privacy policy driven databases. However it is very difficult to provide robust Privacy implementation. Privacy Violation can still take place with some masquerading. In such a scenario, it is important to detect the Violation. A solution for Privacy Violation detection based on malafide intension has been proposed recently. In this paper, we propose an architecture and implementation of a system to test the robustness of malafide intension based Privacy Violation detection.
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malafide intension based detection of Privacy Violation in information system
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, V Goyal, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems. This has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. After a Privacy Violation has taken place, the post-event diagnostics should make use of any post-event information which might be available. This information (malafide intention) might play a decisive role in determining Violations. In this paper we propose one such framework which makes use of malafide intentions. The framework is based on the hypothesis that any intrusion/unauthorized access has a malafide intention always associated with it and is available in a post-event scenario. We hereby propose that by analyzing the Privacy policies and the available malafide intention, it is possible to detect probable Privacy Violations.
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design and development of malafide intension based Privacy Violation detection system an ongoing research report
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, S Dubey, V Goyal, Bholi Patra, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems which has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. We propose one such framework which uses malafide intensions (post-event information) and Privacy policy to detect probable Privacy Violations. The framework is based on the hypothesis that every Privacy Violation has a malafide intension associated with it which is available in a post-event scenario.
S K Gupta - One of the best experts on this subject based on the ideXlab platform.
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a system to test malafide intension based on Privacy Violation detection
International Conference on Digital Information Management, 2007Co-Authors: S K Gupta, S Dubey, V Goyal, A GuptaAbstract:As a response to serious Privacy concerns, various approaches have been proposed on Privacy policy driven databases. However it is very difficult to provide robust Privacy implementation. Privacy Violation can still take place with some masquerading. In such a scenario, it is important to detect the Violation. A solution for Privacy Violation detection based on malafide intension has been proposed recently. In this paper, we propose an architecture and implementation of a system to test the robustness of malafide intension based Privacy Violation detection.
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utilizing network features for Privacy Violation detection
COMmunication System softWAre and MiddlewaRE, 2006Co-Authors: Jaijit Bhattacharya, R Dass, V P Kapoor, S K GuptaAbstract:Privacy, its Violations and techniques to circumvent Privacy Violation have grabbed the centre-stage of both academia and industry in recent months. Corporations worldwide have become conscious of the implications of Privacy Violation and its impact on them and to other stakeholders. Moreover, nations across the world are coming out with Privacy protecting legislations to prevent data Privacy Violations. Such legislations however expose organizations to the issues of intentional or unintentional Violation of Privacy data. A Violation by either malicious external hackers or by internal employees can expose the organizations to costly litigations. In this paper, we propose PRIVDAM; a data mining based intelligent architecture of a Privacy Violation Detection and Monitoring system whose purpose is to detect possible Privacy Violations and to prevent them in the future. This paper elaborates on the use of network characteristics for differentiating between normal network traffic and potential malicious attacks. These attacks are usually hidden in common network services like http, ftp, udp etc. Experimental evaluations illustrate that our approach is scalable as well as robust and accurate in detecting Privacy Violations.
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malafide intension based detection of Privacy Violation in information system
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, V Goyal, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems. This has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. After a Privacy Violation has taken place, the post-event diagnostics should make use of any post-event information which might be available. This information (malafide intention) might play a decisive role in determining Violations. In this paper we propose one such framework which makes use of malafide intentions. The framework is based on the hypothesis that any intrusion/unauthorized access has a malafide intention always associated with it and is available in a post-event scenario. We hereby propose that by analyzing the Privacy policies and the available malafide intention, it is possible to detect probable Privacy Violations.
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design and development of malafide intension based Privacy Violation detection system an ongoing research report
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, S Dubey, V Goyal, Bholi Patra, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems which has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. We propose one such framework which uses malafide intensions (post-event information) and Privacy policy to detect probable Privacy Violations. The framework is based on the hypothesis that every Privacy Violation has a malafide intension associated with it which is available in a post-event scenario.
V Goyal - One of the best experts on this subject based on the ideXlab platform.
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context honeypot a framework for anticipatory Privacy Violation
International Conference on Emerging Trends in Engineering and Technology, 2008Co-Authors: Shruti Gupta, V Goyal, A Gupta, R G S Damor, Sangeeta SabharwalAbstract:Honeypots have been studied in the network domain for detection and information collection against external threats in the past few years. They lure a potential attacker by simulating resources having vulnerabilities and observing the behavior of a potential attacker to identify him before a damaging attack takes place. A lot of work has been done in the area of Privacy and security in databases. Though the number of attacks and complexity for database attacks are increasing day by day, there has been no attempt to design honeypots for Privacy enforcing databases. The use of honeypots for databases would help in confirming the suspicion (malafide intention) of a suspicious user without leaking the target information (information which would fulfill the malafide intention) to the attacker. We propose a framework for database honeypots for certain types of attacks in Privacy context. The proposed honeypots for databases are termed as context honeypots.
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a system to test malafide intension based on Privacy Violation detection
International Conference on Digital Information Management, 2007Co-Authors: S K Gupta, S Dubey, V Goyal, A GuptaAbstract:As a response to serious Privacy concerns, various approaches have been proposed on Privacy policy driven databases. However it is very difficult to provide robust Privacy implementation. Privacy Violation can still take place with some masquerading. In such a scenario, it is important to detect the Violation. A solution for Privacy Violation detection based on malafide intension has been proposed recently. In this paper, we propose an architecture and implementation of a system to test the robustness of malafide intension based Privacy Violation detection.
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query rewriting for detection of Privacy Violation through inferencing
Conference on Privacy Security and Trust, 2006Co-Authors: V Goyal, Shruti Gupta, Shobhit SaxenaAbstract:When a Privacy Violation is detected the intension behind the Violation is revealed. We refer to this as a malafide intension and the information revealed as the target. The target can be expressed using an SQL-like syntax. In sophisticated Privacy attacks the target of the attack may not have been directly accessed but inferred from other pieces of information by exploiting functional dependencies present in the application domain. In this paper we present an efficient algorithm to rewrite the malafide intension query attributes which will return the minimal set of attribute from which the target can be derived. The attribute sets returned by algorithm can derive the target using functional dependencies (algorithm is sound) and furthermore if any minimal set can derive the target using functional dependencies then it will be returned by the algorithm (algorithm is complete).
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malafide intension based detection of Privacy Violation in information system
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, V Goyal, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems. This has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. After a Privacy Violation has taken place, the post-event diagnostics should make use of any post-event information which might be available. This information (malafide intention) might play a decisive role in determining Violations. In this paper we propose one such framework which makes use of malafide intentions. The framework is based on the hypothesis that any intrusion/unauthorized access has a malafide intention always associated with it and is available in a post-event scenario. We hereby propose that by analyzing the Privacy policies and the available malafide intention, it is possible to detect probable Privacy Violations.
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design and development of malafide intension based Privacy Violation detection system an ongoing research report
Lecture Notes in Computer Science, 2006Co-Authors: S K Gupta, S Dubey, V Goyal, Bholi Patra, A GuptaAbstract:In the past few years there has been an increased focus on Privacy issues for Information Systems which has resulted in concerted systematic work focused on regulations, tools and enforcement. Despite this, Privacy Violations still do take place. Therefore there is an increased need to develop efficient methods to detect Privacy Violations. We propose one such framework which uses malafide intensions (post-event information) and Privacy policy to detect probable Privacy Violations. The framework is based on the hypothesis that every Privacy Violation has a malafide intension associated with it which is available in a post-event scenario.
Bruno Skrinjaric - One of the best experts on this subject based on the ideXlab platform.
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theoretical concepts of consumer resilience to online Privacy Violation
Interdisciplinary Description of Complex Systems, 2021Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:Resilience is a multifaceted concept used to explain both system and individual behavior across disciplines. Although definitions and research concepts of resilience vary significantly, resilience has become a boundary object in diverse academic fields calling for a holistic approach. This work aims to elaborate the theoretical concepts that might be applied in the research of consumer resilience to online Privacy Violation, a new and unexplored aspect of consumer behavior in the digital environment. The purpose of the research is to develop the future research frontiers in investigating consumer resilience to online Privacy Violation. It contributes to the Privacy resilience debate and lays the groundwork for developing a conceptual model of online consumer resilience that would explore how individual behavior is affected after online Privacy Violation occurrence. Developing a conceptual model of consumer resilience to online Privacy Violation that would include a set of individual and environmental variables, will contribute to the existing understanding of resilience at the intersection of psychology, economics, and Privacy studies. Furthermore, it will also contribute to the understanding of adaptive responses of resilient individuals to Privacy breaches in an online environment, as well as to the understanding of processes by which resilience affects adaptive responses of consumers in the specific context of online Privacy breaches.
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conceptual research framework of consumer resilience to Privacy Violation online
Sustainability, 2021Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:This is a conceptual paper that aims to identify relevant approaches for assessing consumer resilience with regard to online Privacy Violation and to develop a research model suitable for subsequent empirical testing. Based on the relevant literature, we made a synthesis of theoretical approaches to individual resilience from diverse disciplines and in the next step we proposed a set of variables in the model to serve as determinants and behavioral consequences of consumer resilience with regard to online Privacy Violation. Finally, we offer the developed conceptual model for further scholarly debate and for future empirical verification from the research community.
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theoretical concepts of consumer resilience to online Privacy Violation
Research Papers in Economics, 2020Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:Resilience is a multifaceted concept used to explain both system and individual behavior across disciplines. Although definitions and research concepts of resilience vary significantly, resilience has become a boundary object in diverse academic fields calling for a holistic approach. This work aims to elaborate the theoretical concepts that might be applied in the research of consumer resilience to online Privacy Violation, a new and unexplored aspect of consumer behavior in the digital environment. It contributes to the Privacy resilience debate and lays the groundwork for developing a conceptual model of online consumer resilience that would explore how individual behavior is affected after online Privacy Violation occurrence.
Jelena Budak - One of the best experts on this subject based on the ideXlab platform.
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theoretical concepts of consumer resilience to online Privacy Violation
Interdisciplinary Description of Complex Systems, 2021Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:Resilience is a multifaceted concept used to explain both system and individual behavior across disciplines. Although definitions and research concepts of resilience vary significantly, resilience has become a boundary object in diverse academic fields calling for a holistic approach. This work aims to elaborate the theoretical concepts that might be applied in the research of consumer resilience to online Privacy Violation, a new and unexplored aspect of consumer behavior in the digital environment. The purpose of the research is to develop the future research frontiers in investigating consumer resilience to online Privacy Violation. It contributes to the Privacy resilience debate and lays the groundwork for developing a conceptual model of online consumer resilience that would explore how individual behavior is affected after online Privacy Violation occurrence. Developing a conceptual model of consumer resilience to online Privacy Violation that would include a set of individual and environmental variables, will contribute to the existing understanding of resilience at the intersection of psychology, economics, and Privacy studies. Furthermore, it will also contribute to the understanding of adaptive responses of resilient individuals to Privacy breaches in an online environment, as well as to the understanding of processes by which resilience affects adaptive responses of consumers in the specific context of online Privacy breaches.
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conceptual research framework of consumer resilience to Privacy Violation online
Sustainability, 2021Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:This is a conceptual paper that aims to identify relevant approaches for assessing consumer resilience with regard to online Privacy Violation and to develop a research model suitable for subsequent empirical testing. Based on the relevant literature, we made a synthesis of theoretical approaches to individual resilience from diverse disciplines and in the next step we proposed a set of variables in the model to serve as determinants and behavioral consequences of consumer resilience with regard to online Privacy Violation. Finally, we offer the developed conceptual model for further scholarly debate and for future empirical verification from the research community.
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theoretical concepts of consumer resilience to online Privacy Violation
Research Papers in Economics, 2020Co-Authors: Jelena Budak, Edo Rajh, Suncana Slijepcevic, Bruno SkrinjaricAbstract:Resilience is a multifaceted concept used to explain both system and individual behavior across disciplines. Although definitions and research concepts of resilience vary significantly, resilience has become a boundary object in diverse academic fields calling for a holistic approach. This work aims to elaborate the theoretical concepts that might be applied in the research of consumer resilience to online Privacy Violation, a new and unexplored aspect of consumer behavior in the digital environment. It contributes to the Privacy resilience debate and lays the groundwork for developing a conceptual model of online consumer resilience that would explore how individual behavior is affected after online Privacy Violation occurrence.
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behavioural consequences of Privacy Violation online in a post communist society resilience explained
Surveillance Resilience & Privacy conference, 2018Co-Authors: Jelena BudakAbstract:The exploratory study provides insights how past negative Privacy Violation experience of internet user is related to Privacy concern and what actions could be foreseen in the case of individuals that have been exposed to the Privacy breach and those who have not experienced Privacy Violation. This study contributes to the Privacy resilience debate by exploring how individual behaviour relates to the Privacy restored after stress.