E-CAPTCHA: A Two Way Graphical Password based Hard AI Problem

CAPTCHA is a Turing test that people can succeed, however current PC program could not succeed. The primary motivation behind CAPTCHA is to restrict automated scripts that are posted spam content. To upgrade the security another system Enhanced-CAPTCHA(E-CAPTCHA) is going to develop which includes some new elements specifically the Novel security based Grid-Box method where high security can accomplished by including 2 level of accessing

Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature

Usable, secure and deployable graphical passwords

PhD ThesisEvaluations of the usability and security of alphanumeric passwords and Personal Identification Numbers (PINs) have shown that users cannot remember credentials considered to be secure. However, the continued reliance upon these methods of user authentication has placed end-users and system designers in a coevolutionary struggle, with each defending competing concerns of usability and security. Graphical passwords have been proposed as an alternative, and their use is supported by cognitive theories such as the picture superiority effect which suggest that pictures, rather than words or numbers, could provide a stronger foundation upon which to design usable and secure knowledge-based authentication. Indeed, early usability studies of novel systems harnessing this effect appear to show promise, however, the uptake of graphical passwords in real-world systems is low. This inertia is likely related to uncertainty regarding the challenges that novel systems might bring to the already delicate interplay between usability and security; particularly the new challenges faced in scaffolding user behaviours that comply with context-specific security policies, uncertainty regarding the nature of new socio-technical attacks, and the impact of images themselves upon usability and security. In this thesis we present a number of case studies incorporating new designs, empirical methods and results, that begin to explore these aspects of representative graphical password systems. Specifically, we explore: (i) how we can implicitly support security-focused behaviours such as choosing high entropy graphical passwords and defending against observation attack; (ii) how to capture the likely extent of insecure behaviour in the social domain such as graphical password sharing and observation attack; and (iii) how through the selection of appropriate properties of the images themselves we can provide security and usability benefits. In doing so, we gen- erate new insights into the potential of graphical passwords to provide usable, secure and deployable user authentication.Microsoft Research

On the Use of Secret Sharing as a Secure Multi-use Pad

Secret sharing (SS) is a cryptographic method proposed independently by Adi Shamir and George Blakley in 1979 to encode the keys of public-key cryptography by splitting them into maximally entropic shares that are distributed to participants, only revealing the secret when combined. Each new sharing instance, even of the same key, produces a different set of shares to distribute anew. This paper investigates SS as an independent cipher to secure confidential messages between a limited set of trusted participants by eliminating the need to redistribute shares. A participant's master share is permanently fixed and unlimited temporary shares are created and combined with it to reveal new messages. Security is argued against specific and general attacks

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Cluster J Mycobacteriophages: Intron Splicing in Capsid and Tail Genes

Bacteriophages isolated on Mycobacterium smegmatis mc2155 represent many distinct genomes sharing little or no DNA sequence similarity. The genomes are architecturally mosaic and are replete with genes of unknown function. A new group of genomes sharing substantial nucleotide sequences constitute Cluster J. The six mycobacteriophages forming Cluster J are morphologically members of the Siphoviridae, but have unusually long genomes ranging from 106.3 to 117 kbp. Reconstruction of the capsid by cryo-electron microscopy of mycobacteriophage BAKA reveals an icosahedral structure with a triangulation number of 13. All six phages are temperate and homoimmune, and prophage establishment involves integration into a tRNA-Leu gene not previously identified as a mycobacterial attB site for phage integration. The Cluster J genomes provide two examples of intron splicing within the virion structural genes, one in a major capsid subunit gene, and one in a tail gene. These genomes also contain numerous free-standing HNH homing endonuclease, and comparative analysis reveals how these could contribute to genome mosaicism. The unusual Cluster J genomes provide new insights into phage genome architecture, gene function, capsid structure, gene mobility, intron splicing, and evolution. © 2013 Pope et al

Bit inverting map method for improved steganography scheme

Achieving an efficient and accurate steganography scheme for hiding information is the foremost priority in the information and communication technology era. The developed scheme of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography scheme is the main issue to be addressed. This study proposes an improved Bit Inverting Map (BIM) method and a new scheme for embedding secret message into an image. This newly developed scheme is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select pixels before random embedding to select block of (64 64) pixels, followed by the Knight Tour algorithm to select sub-block of (8 8) pixels, and finally by the random pixels selection. The proposed BIM is distributed over the entire image to maintain high level of security against any kind of attack. One-bit indicator is used to decide if the secret bits are inserted directly or inversely, which enhanced the complexity of embedding process. Color and gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. Self-captured images are used to test the efficacy of the proposed BIM method. The results show good PSNR values of 72.9 and these findings verified the worthiness of the proposed BIM method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing scheme in the literature