Pradeep K. Atrey

The University of Winnipeg, Winnipeg, Manitoba, Canada

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Publications (78)45.91 Total impact

  • A. Yakubu, N. C. Maddage, P. K. Atrey
    The 10th Annual Symposium on Information Assurance in conjunction with The 18th New York State Cyber Security Conference; 06/2015
  • Prabhu Natarajan, Pradeep K. Atrey, Mohan Kankanhalli
    ACM Transactions on Multimedia Computing Communications and Applications 06/2015; 11(4):1-30. DOI:10.1145/2710128 · 0.90 Impact Factor
  • Ankita Lathey, Pradeep K. Atrey
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    ABSTRACT: Cloud-based multimedia systems are becoming increasingly common. These systems offer not only storage facility, but also high-end computing infrastructure which can be used to process data for various analysis tasks ranging from low-level data quality enhancement to high-level activity and behavior identification operations. However, cloud data centers, being third party servers, are often prone to information leakage, raising security and privacy concerns. In this article, we present a Shamir's secret sharing based method to enhance the quality of encrypted image data over cloud. Using the proposed method we show that several image enhancement operations such as noise removal, antialiasing, edge and contrast enhancement, and dehazing can be performed in encrypted domain with near-zero loss in accuracy and minimal computation and data overhead. Moreover, the proposed method is proven to be information theoretically secure.
    ACM Transactions on Multimedia Computing Communications and Applications 02/2015; 11(3):1-24. DOI:10.1145/2656205 · 0.90 Impact Factor
  • Source
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    ABSTRACT: Audio Secret Sharing (ASS) is a technique used to protect audio data from tampering and disclosure by dividing it into shares such that qualified shares can reconstruct the original audio data. Existing ASS schemes encrypt binary secret messages and rely on the human auditory system for decryption by simultaneously playing authorized shares. This decryption approach tends to overburden the human auditory system when the number of shares used to reconstruct the secret increases [3]. Furthermore, it does not create room for further analysis or computation to be performed on the reconstructed secret since decryption ends at the human auditory system. Additionally, schemes in [2], [3], [4], [6] do not extend to the general (k, n) threshold. In this paper we propose an ASS scheme based on Shamir’s secret sharing, which is (k, n) threshold, ideal2, and information theoretically secure and it provides computationally efficient decryption.
    MMM 2015, the 21st Anniversary International Conference on MultiMedia Modeling, Sydney, NSW, Australia; 01/2015
  • Manoranjan Mohanty, Wei Tsang Ooi, Pradeep K. Atrey
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    ABSTRACT: With the evolution in cloud computing, cloud-based volume rendering, which outsources data rendering tasks to cloud datacenters, is attracting interest. Although this new rendering technique has many advantages, allowing third-party access to potentially sensitive volume data raises security and privacy concerns. In this paper, we address these concerns for cloud-based pre-classification volume ray-casting by using Shamir’s (k, n) secret sharing and its variant (l, k, n) ramp secret sharing, which are homomorphic to addition and scalar multiplication operations, to hide color information of volume data/images in datacenters. To address the incompatibility issue of the modular prime operation used in secret sharing technique with the floating point operations of ray-casting, we consider excluding modular prime operation from secret sharing or converting the floating number operations of ray-casting to fixed point operations - the earlier technique degrades security and the later degrades image quality. Both these techniques, however, result in significant data overhead. To lessen the overhead at the cost of high security, we propose a modified ramp secret sharing scheme that uses the three color components in one secret sharing polynomial and replaces the shares in floating point with smaller integers.
    Multimedia Tools and Applications 01/2015; DOI:10.1007/s11042-015-2567-8 · 1.06 Impact Factor
  • Hazem Al-Najjar, Saeed Alharthi, Pradeep K. Atrey
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    ABSTRACT: Image sharing has become a prominent field in large and small networks. However, in order to deliver the shares to their respective shareholders, we need a secure channel to protect the shares from potential attacks by other users on the network. These users can locate the shares and retrieve the image using the Lagrange interpolation method if they are able to locate the minimum required number of shares. This paper proposes a method to protect the privacy and security of the shares when sending them through unsecured channels. The proposed method is divided into three phases. In the first phase, image pixels are changed using the column and row indices, then the shares are created using Shamir’s secret sharing (SSS) method. Then a relationship is created between the shares using a linear independence function. In the second phase, the first part of the image is encrypted to hide the solver data. Finally, in the third phase, the data is shared using the SSS method. Participants can retrieve the whole image by applying the reverse order of the proposed method using only the information from the sender through the same channel. The simulation results show that the proposed method is efficient and robust against different types of attacks and can be used to send the shares over unsecured channels.
    Multimedia Tools and Applications 12/2014; DOI:10.1007/s11042-014-2404-5 · 1.06 Impact Factor
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    ABSTRACT: Automated multimedia surveillance systems capture, process and analyze multimedia data coming from heterogeneous sensors. These systems are often designed to support (semi-) automatic decision making, such as generating an alarm in response to a surveillance event, as well as providing useful information to human decision makers to ensure public safety. Various tools and techniques from different fields such as Computer Vision, Pattern Recognition, and Multimedia Computing have contributed to the success of such systems.Although there has been significant progress in the field of multimedia surveillance research, we still face situations when the system is unable to detect critical events, wrongly identifies individuals or generates false alarms leading to undesired consequences. Hence, the goal of this special issue is to bring forward recent advancements in automated multimedia surveillance for improved public safety. More specifically, it reports the state-of-the-art techniques, met
    Multimedia Tools and Applications 11/2014; 73(1). DOI:10.1007/s11042-012-1342-3 · 1.06 Impact Factor
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    ABSTRACT: Design and implementation of an effective surveillance system is a challenging task. In practice, a large number of CCTV cameras are installed to prevent illegal and unacceptable activities where a human operator observes different camera views and identifies various alarming cases. But reliance on the human operator for real-time response can be expensive as he may be unable to pay full attention to all camera views at the same time. Moreover, the complexity of a situation may not be easily perceivable by the operator for which he might require additional support in response to an adverse situation. In this paper, we present a Decision Support Engine (DSE) to select and schedule most appropriate camera views that can help the operator to take an informed decision. For this purpose, we devise a utility based approach where the utility value changes based on automatically detected events in different surveillance zones, event co-relation, and operator’s feedback. In addition to the selected camera views, we propose to synthetically embed extra information around the camera views such as event summary and suggested action plan to globally perceive the current situation. The experimental results show the usefulness of the proposed decision support system.
    Multimedia Tools and Applications 11/2014; 73(1). DOI:10.1007/s11042-012-1294-7 · 1.06 Impact Factor
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    ABSTRACT: This paper presents an analysis of the multiresolution form of singular value decomposition SVD (MR-SVD) and generalizes the analysis into a random multiresolution form of singular value decomposition (R-MR-SVD) with an intrinsic randomness. The core idea behind the proposed transform is to introduce randomness in the computing process based on parameters without which one can neither decompose nor reconstruct the data correctly. The proposed transform inherits the excellent properties of MR-SVD along with its own unique features, which can be useful in many research areas. Image encryption, lossy image compression, and face recognition are the primary applications used to illustrate the practical usage of the proposed transform.
    Information Sciences 09/2014; 277(1):247-262. DOI:10.1016/j.ins.2014.02.018 · 3.89 Impact Factor
  • Gaurav Bhatnagar, Q.M. Jonathan Wu, Pradeep K. Atrey
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    ABSTRACT: In this paper, a novel logo watermarking technique with key concept is proposed using fractional wavelet packet transform (FrWPT), non-linear chaotic map and singular value decomposition (SVD). The core idea is to use biometrically generated keys in the embedding process of gray-scale watermark. Therefore, this paper first proposes a method for generating keys from biometrics efficiently. Then the host image is first randomized with the help of non-linear chaotic map followed by the embedding in the FrWPT domain by modifying the singular values of the randomized image. Further, in order to enhance the security, an authentication key is formed to authenticate the watermarked image. Finally, a reliable extraction process is proposed to extracted watermark from the possibly attacked authenticate watermarked image. The security, attack and comparative analysis confirm high security, efficiency and robustness of the proposed watermarking technique. Further, an efficient solution is also proposed to deal with the ambiguous situations created by SVD in watermarking.
    Expert Systems with Applications 08/2014; 41(10):4563–4578. DOI:10.1016/j.eswa.2014.01.023 · 1.97 Impact Factor
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    ABSTRACT: Huge amounts of video are being recorded every day by surveillance systems. Since video is capable of recording and preserving an enormous amount of information which can be used in many applications, it is worth examining the degree of privacy loss that might occur due to public access to the recorded video. A fundamental requirement of privacy solutions is an understanding and analysis of the inference channels than can lead to a breach of privacy. Though inference channels and privacy risks are well studied in traditional data sharing applications (e.g., hospitals sharing patient records for data analysis), privacy assessments of video data have been limited to the direct identifiers such as people’s faces in the video. Other important inference channels such as location (Where), time (When), and activities (What) are generally overlooked. In this paper we propose a privacy loss model that highlights and incorporates identity leakage through multiple inference channels that exist in a video due to what, when, and where information. We model the identity leakage and the sensitive information separately and combine them to calculate the privacy loss. The proposed identity leakage model is able to consolidate the identity leakage through multiple events and multiple cameras. The experimental results are provided to demonstrate the proposed privacy analysis framework.
    Multimedia Tools and Applications 01/2014; 68(1). DOI:10.1007/s11042-012-1207-9 · 1.06 Impact Factor
  • Multimedia Tools and Applications 01/2014; DOI:10.1007/s11042-014-2212-y · 1.06 Impact Factor
  • International Journal of Distributed Sensor Networks 01/2014; 2014:1-10. DOI:10.1155/2014/757845 · 0.92 Impact Factor
  • Manoranjan Mohanty, Wei Tsang Ooi, Pradeep K. Atrey
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    ABSTRACT: Advances in cloud computing have allowed volume rendering tasks, typically done by volume ray-casting, to be outsourced to cloud data centers. The availability of volume data and rendered images (which can contain important information such as the disease information of a patient) to a third-party cloud provider, however, presents security and privacy challenges. This paper addresses these challenges by proposing a secure cloud-based volume ray-casting framework that distributes the rendering tasks among the data centers and hides the information that is exchanged between the server and a data center, between two data centers, and between a data center and the client by using Shamir's secret sharing, such that none of the data centers has enough information to know the secret data and/or rendered image. Experiments and analyses show that our framework is highly secure and requires low computation cost.
    Proceedings of the 2013 IEEE International Conference on Cloud Computing Technology and Science - Volume 01; 12/2013
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    ABSTRACT: Today digital video is used extensively in many applications. Sometimes a video could be treated as a top secret for an organization, for example military secrets, surveillance footage and corporate product designs, and may need to be shared among a group of people in a secure manner. Traditional data security methods such as encryption techniques are prone to single-point attack, i.e. the secret can be revealed by obtaining the decryption key from any single person. Alternatively, the secret sharing scheme provides collective control over the secrecy of information and is considered information theoretically secure. In this paper, we propose to adopt a secret sharing based approach to provide collective control over a given sensitive video. We present three methods that utilize the spatial and temporal redundancy in videos in different ways. We analyze the security of these methods and compare them for efficiency in terms of computation time and space using extensive experimentation.
    Multimedia Tools and Applications 12/2013; 73(3):1459-1486. DOI:10.1007/s11042-013-1644-0 · 1.06 Impact Factor
  • Gaurav Bhatnagar, Q. M. Jonathan Wu, Pradeep K. Atrey
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    ABSTRACT: In this article, a novel logo watermarking scheme is proposed based on wavelet frame transform, singular value decomposition and automatic thresholding. The proposed scheme essentially rectifies the ambiguity problem in the SVD-based watermarking. The core idea is to randomly upscale the size of host image using reversible random extension transform followed by the embedding of logo watermark in the wavelet frame domain. After embedding, a verification phase is casted with the help of a binary watermark and toral automorphism. At the extraction end, the binary watermark is first extracted followed by the verification of watermarked image. The logo watermark is extracted if and only if the watermarked image is verified. The security, attack and comparative analysis confirm high security, efficiency and robustness of the proposed watermarking system.
    ACM Transactions on Multimedia Computing Communications and Applications 12/2013; 10(1). DOI:10.1145/2542205.2542207 · 0.90 Impact Factor
  • Shreelatha bs, Pradeep K. Atrey, Majid Khabbazian
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    ABSTRACT: In this work, we analyze some of the existing secret image sharing methods and show that they do not possess semantic security, a property of many secure systems. We propose a new method based on the threshold secret sharing scheme for images in the compressed and uncompressed domains. Our method generates minimal share sizes with similar computational cost to previous methods, yet it is computationally secure and satisfies the semantic security property.
    IEEE International Conference on Semantic Computing; 09/2013
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    ABSTRACT: Despite the fact that performance improvements have been reported in the last years, semantic concept detection in video remains a challenging problem. Existing concept detection techniques, with ontology rules, exploit the static correlations among primitive concepts but not the dynamic spatiotemporal correlations. The proposed method rewards (or punishes) detected primitive concepts using dynamic spatiotemporal correlations of the given ontology rules and updates these ontology rules based on the accuracy of detection. Adaptively learned ontology rules significantly help in improving the overall accuracy of concept detection as shown in the experimental result.
    ACM Transactions on Multimedia Computing Communications and Applications 05/2013; 9(2). DOI:10.1145/2457450.2457452 · 0.90 Impact Factor
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    ABSTRACT: This paper attempts to solve the integrity issues of a compromised face biometric system using two watermarking schemes. Two new blind watermarking schemes, namely S1 and S2, are proposed to ensure the integrity of the training face database and of the test images, respectively. Scheme S1 is fragile spatial-domain based and scheme S2 works in the discrete cosine transformation (DCT) domain and is robust to channel noise. The novelty of S1 lies in the fact that it is lossless and the ratio of watermark bits to the size of the host image is 2.67, while S2 has better robustness than existing blind watermarking schemes. The performance of both schemes is evaluated on a subset of the Indian face database and the results show that both schemes verify the integrity with very high accuracy without affecting the performance of the biometric system.
    Signal and Image Processing Applications (ICSIPA), 2013 IEEE International Conference on; 01/2013
  • Ankita Lathey, Pradeep K. Atrey, Nishant Joshi
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    ABSTRACT: Outsourcing the storage and processing of multimedia data to cloud data centers (CDCs) is becoming increasingly common. However, the use of third party CDCsraises security and privacy concerns. In this paper, we present a Shamir's Secret Sharing (SSS) based method to obtain enhanced digital images by performing low pass filtering (LPF)on the obfuscated (or encrypted) images over cloud. The proposed scheme is novel in performing averaging (division)operations involved in the spatial convolution of a mask overan image in the encrypted domain (ED) to get the same filtered resultant image as when the filtering operation is performed in the plain text domain (PD). Security and performance analyses corroborate that our scheme is information theoretically secure and transmission efficient (as compared to other schemes), respectively.
    Semantic Computing (ICSC), 2013 IEEE Seventh International Conference on; 01/2013

Publication Stats

494 Citations
45.91 Total Impact Points

Institutions

  • 2008–2015
    • The University of Winnipeg
      • Department of Applied Computer Science
      Winnipeg, Manitoba, Canada
  • 2014
    • University at Albany, The State University of New York
      New York, New York, United States
  • 2010
    • University of Ottawa
      • Faculty of Medicine
      Ottawa, Ontario, Canada
  • 2006
    • IIT Kharagpur
      Khargpur, West Bengal, India
  • 2004–2006
    • National University of Singapore
      • Department of Computer Science
      Tumasik, Singapore