3 research outputs found
ANALYSIS OF NEW CHAOTIC MAP AND PERFORMANCE EVALUATION IN ITS APPLICATION TO DIGITAL COLOR IMAGE ENCRYPTION
In this research a new chaotic map which is a modification from composition of MS map and Improved logistics map is proposed. New map’s chaotic behavior is proven by the bifurcation diagram and Lyapunov exponent. This map will be used in chaos-based cryptography as a keystream generator and then it will be processed in the encryption and decryption algorithms through XOR operations. The results of the encryption and decryption processes were evaluated by several tests such as key sensitivity analysis, histogram analysis, correlation analysis, and image quality analysis. All the tests are doing to evaluate the performance new chaotic map in encryption of digital color image. Based on the results of several tests, a conclusion can be drawn that the encryption and decryption process is successful and difficult to attack with various kinds of attacks. The key that built from new chaotic map has a good sensitivity
Privacy Intelligence: A Survey on Image Sharing on Online Social Networks
Image sharing on online social networks (OSNs) has become an indispensable
part of daily social activities, but it has also led to an increased risk of
privacy invasion. The recent image leaks from popular OSN services and the
abuse of personal photos using advanced algorithms (e.g. DeepFake) have
prompted the public to rethink individual privacy needs when sharing images on
OSNs. However, OSN image sharing itself is relatively complicated, and systems
currently in place to manage privacy in practice are labor-intensive yet fail
to provide personalized, accurate and flexible privacy protection. As a result,
an more intelligent environment for privacy-friendly OSN image sharing is in
demand. To fill the gap, we contribute a systematic survey of 'privacy
intelligence' solutions that target modern privacy issues related to OSN image
sharing. Specifically, we present a high-level analysis framework based on the
entire lifecycle of OSN image sharing to address the various privacy issues and
solutions facing this interdisciplinary field. The framework is divided into
three main stages: local management, online management and social experience.
At each stage, we identify typical sharing-related user behaviors, the privacy
issues generated by those behaviors, and review representative intelligent
solutions. The resulting analysis describes an intelligent privacy-enhancing
chain for closed-loop privacy management. We also discuss the challenges and
future directions existing at each stage, as well as in publicly available
datasets.Comment: 32 pages, 9 figures. Under revie