Catherine Durnell Cramton (\"The Mutual Knowledge Prob- conditions, the impact of organizational change on subsequent lem and Its Consequences for Dispersed Collaboration\") is Asso- performance and survival, and the consequences of organizational ciate Professor in the School of Management at George Mason structures and dynamics for employees\' careers and the compo- University. She recieved her Ph.D. in organizational behavior from sition of organizations\' work forces. She serves on the editorial Yale University. Her research explores the contemporary chal- boards of Organization Science, Administrative Science Quar- lenges of collaboration and leadership, including distributed work, terly, and the American Sociological Review. Address: Columbia interorganizational collaboration, project team leadership, and the University, Graduate School of Business, 706 Uris Hall, New impact of technology on collaboration. Address: School of Man- York, NY 10027-6902; telephone: (212) 854-4424; e-mail: agement, Mail Stop 5F5, George Mason University, Fairfax, VA hah15@columbia.edu . 22030-4444; telephone: (703) 993-1814; fax: (202) 318-4319; John C. Henderson (\"Understanding `Strategic Learning\': e-mail: ccramton@som.gmu.edu . Linking Organizational Learning, Knowledge Management, and Sue R. Faerman (\"Understanding Interorganizational Cooper- Sensemaking\") is the Richard C. Shipley Professor of Manage- ation: Private-Public Collaboration in Regulating Financial Market ment, Chairperson of the Information Systems Department, and Innovation\") is Professor of Public Administration and Organiza- Director of the Institute for Leading in a Dynamic Economy at tional Studies and Dean of Undergraduate Studies at the University Boston University\'s School of Management. He is a noted at Albany, State University of New York. Her research focuses on researcher, consultant, and executive educator with papers appear- the paradoxical nature of leadership and organizational perfor- ing in many refereed journals. His coauthored book, Knowledge mance. She received her Ph.D. in public administration from the Engine, examines leveraging a firm\'s knowledge assets. His University at Albany, State University of New York. Address: research interests include: managing strategic partnerships, impact Office of Undergraduate Studies-LC30, University at Albany, of the mobile Internet on markets and organizations, and knowl- State University of New York, 1400 Washington Avenue, Albany, edge management. Address: Boston University School of Man- NY 12222; telephone: (518) 442-3950; fax: (518) 442-4959; e-mail: agement, 595 Commonwealth Avenue, Room 546H, Boston, MA sfaerman@uamail.albany.edu . 02215; telephone: (617) 353-6142; fax: (617) 353-1695; e-mail: James F. Fairbank (\"Emulation in Academia: Balancing Struc- jchender@bu.edu . ture and Identity\") received his Ph.D. in management and organi- Giuseppe (Joe) Labianca (\"Emulation in Academia: Balancing zation, The Pennsylvania State University and is an assistant pro- Structure and Identity\") received his Ph.D. in management and or- fessor of management in the College of Business and Economics ganization, The Pennsylvania State University, and is an assistant at West Virginia University in Morgantown, WV. His current re- professor of organization and management at Emory University\'s search interests are strategic decision making and the management Goizueta Business School in Atlanta, GA. His primary interests are of information technology. Address: College of Business and Eco- in network and cognition research at the intra- and interorganiza- nomics, P.O. Box 6025, Morgantown, WV 26506-6025; telephone: tional levels. Recent projects have investigated the antecedents and (304) 293-7937; fax: (304) 293-5652; e-mail: ifairban@wvu.edu . consequences of disliking others in one\'s social networks at work, Dennis A. Gioia (\"Emulation in Academia: Balancing Structure as well as investigating the process of emulation between organ- and Identity\") is Professor of Organizational Behavior, Department zations. He conducts both quantitative and qualitative research, and of Management and Organization, Smeal College of Business Ad- has published in the Academy of Management Journal and Orga- ministration at The Pennsylvania State University. His current nization Science. He is currently serving on the editorial review research and writing interests focus primarily on the cognitive board of the Academy of Management Journal. Address: Goizueta processes of organization members, especially the ways in which Business School, 1300 Clifton Road, Emory University, Atlanta, identity, image, and reputation are involved in organizational GA 30322; telephone: (404) 727-7662; fax: (404) 727-6663; e-mail: sensemaking, sensegiving, and change. His work has appeared joe_labianca@bus.emory.edu . in many of the top journals in the field and he has coedited two David P. McCaffrey (\"Understanding Interorganizational Co- volumes of original contributions: The Thinking Organization operation: Private-Public Collaboration in Regulating Financial and Creative Action in Organizations. Address: Smeal College of Market Innovation\") is Professor of Public Administration, Public Business, Penn State University, 403 Beam BAB, University Park, Policy, and Organizational Studies at the University at Albany, PA 16802; telephone: (814) 865-6370; fax: (814) 863-7261; e-mail: State University of New York. His research focuses on the orga- dag4@psu.edu . nizational dynamics of regulatory systems. He received his Ph.D. Heather A. Haveman (\"Organizational Environments in Flux: in sociology from the State University of New York at Stony The Impact of Regulatory Punctuations on Organizational Do- Brook. Address: Department of Public Administration and Policy, mains, CEO Succession, and Performance\") is Professor of Man- University at Albany, State University of New York, 135 Western agement at the Graduate School of Business, Columbia University. Avenue, Albany, NY 12222; e-mail: d.mccaffrey@albany.edu . She received her Ph.D. in organizational behavior and industrial Alan D. Meyer (\"Organizational Environments in Flux: The relations from the Haas School of Business Administration at the Impact of Regulatory Punctuations on Organizational Domains, University of California at Berkeley in 1990. Her research inves- CEO Succession, and Performance\") is the Charles H. Lundquist tigates organizations\' responses to shifting internal and external Professor of Entrepreneurial Management at the University of

About Authors

Information hiding scheme for digital images using difference expansion and modulus function

Essential secret image sharing scheme with the same size of shadows

This paper is focused on proposal of image steganographic method that is able to embedding of encoded secret message using Quick Response Code (QR) code into image data Discrete Wavelet Transformation (DWT) domain is used for the embedding of QR code, while embedding process is additionally protected by Advanced Encryption Standard (AES) cipher algorithm In addition, typical characteristics of QR code was broken using the encryption, therefore it makes the method more secure The aim of this paper is design of image steganographic method with high secure level and high non-perceptibility level The relation between security and capacity of the method was improved by special compression of QR code before the embedding process Efficiency of the proposed method was measured by Peak Signal-to-Noise Ratio (PSNR) and achieved results were compared with other steganographic tools

Image steganography with using QR code and cryptography

The exponential rise in the development of cloud computing environments in the healthcare field, the protection and confidentiality of the medical records become a primary concern for healthcare services applications. Today, health data stored in the cloud is highly confidential information concealed to avoid unauthorized access to protect the patient’s information. As cloud-based medical data transmission becomes more common, it receives growing attention from researchers and academics. Despite the potential for misuse, medical data transmitted through unreliable networks can be manipulated or compromised. The current cryptosystems alone are not sufficient to deal with these issues, and hence this paper introduces a new hybridization of data encryption model to shelter the diagnosis data in medical images. The proposed model is developed by combining either 2D Discrete Wavelet Transform 1 Level (2D-DWT-1 L) or 2D Discrete Wavelet Transform 2 Level (2D-DWT-2 L) steganography with the proposed hybrid encryption scheme. The hybrid encryption scheme is built by strategically applying Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA) algorithms to secure diagnosis data to be embedded with the RGB channels of medical cover image. One of the key novelties is the use of an Adaptive Genetic Algorithm for Optimal Pixel Adjustment Process (AGA-OPAP) that enriches data hiding ability as well as imperceptibility features. To evaluate the efficiency of the proposed model, numerical tests are performed. The results show that the proposed algorithm is capable of safely transmitting medical data. Comparison of results is carried out concerning the datasets with the state-of-the-art algorithm. In terms of various statistical measures, the results showed the superiority of the proposed algorithm, such as peak signal to noise ratio (PSNR), correlation, structural content (SC), structure similarity (SSIM), entropy, histogram, NPCR, UACI and embedding capacity. The proposed model can also prevent attacks, such as steganalysis or RS attacks.

Hybrid data encryption model integrating multi-objective adaptive genetic algorithm for secure medical data communication over cloud-based healthcare systems

Steganography is the science of hiding secret information in another unsuspicious data. Generally, a steganographic secret message could be a widely useful multimedia: as a picture, an audio file, a video file or a message in clear text - the covertext. The most recent steganography techniques tend to hide a secret message in digital images. We propose and analyze experimentally a blind steganography method based on specific attributes of two dimensional discrete wavelet transform set by Haar mother wavelet. The blind steganography methods do not require an original image in the process of extraction what helps to keep a secret communication undetected to third party user or steganalysis tools. The secret message is encoded by Huffman code in order to achieve a better imperceptibility result. Moreover, this modification also increases the security of the hidden communication.

Data hiding in still images based on blind algorithm of steganography

Steganography is the process of implanting secret message in a cover data without causing degradation neither to the cover information nor to the secret message implanted in the cover data. Most of the steganographic techniques are applied on images, texts, and protocols. In this paper a novel algorithm of image steganography is proposed to implant a secret text message into a cover image using YC b C r color space model and 2D Haar Discrete Wavelet Transform. In this proposed technique, input text in ASCII code is encrypted by AES what ensures, that the relative letter frequency of a plain text secret message will be disturbed. Proposed technique also solves conversion between color space models RGB and YC b C r in spite of modification in component C b by the secret message. This step allows extracting of secret message without errors what is a very important characteristic, because change of only one bit causes extracting of different character. Performance of the proposed algorithm has been gauged by the peak signal to noise ratio (PSNR) and mean square error (MSE) for the stego image.

Image steganography based on combination of YC b C r color model and DWT

The objective of this paper is performance testing of Feature-based Steganalysis methods for detection of steganography tools that are used for hiding a secret message in still images. Many of those tools, which can be used publicly, cause statistical changes in original images during embedding process. The features represent those statistically calculated changes, where feature extraction in this paper was applied in spatial domain and also directly in transformation domain of DCT in JPEG files what helps to obtained relevant statistical data. The results of this paper identify the selection of statistical feature vector that is used during training phase of classifier in order to distinguish between cover and stego image. The reliable detection of selected steganography methods were presented in relation to length of feature vector. Moreover, contribution to design of blind steganalysis system was proposed for the purpose of unveiling a secret communication via completely new steganography methods.

Performance evaluation of feature-based steganalysis in steganography

In the paper we introduce a new universal steg- analytic method in JPEG file format that is detecting well- known and also newly developed steganographic methods. The steganalytic model is trained by MHF-DZ stegano- graphic algorithm previously designed by the same authors. The calibration technique with the Feature Based Steganalysis (FBS) was employed in order to identify sta- tistical changes caused by embedding a secret data into original image. The steganalyzer concept utilizes Support Vector Machine (SVM) classification for training a model that is later used by the same steganalyzer in order to identify between a clean (cover) and steganographic image. The aim of the paper was to analyze the variety in accuracy of detection results (ACR) while detecting testing steganographic algorithms as F5, Outguess, Model Based Steganography without deblocking, JP Hide&Seek which represent the generally used steganographic tools. The comparison of four feature vectors with different lengths FBS (22), FBS (66) FBS(274) and FBS(285) shows prom- ising results of the proposed universal steganalytic method comparing to binary methods.

Martin Broda

Papers

Image steganography with using QR code and cryptography

Data hiding in still images based on blind algorithm of steganography

Image steganography based on combination of YC b C r color model and DWT

Performance evaluation of feature-based steganalysis in steganography

Universal Image Steganalytic Method