The network infrastructure of any organization is always under constant threat to a variety of attacks; namely, break-ins, security breach or system misuse. The Network Intrusion Detection System (NIDS) employed in a network detects such penetration attacks and intrusions within a network. Known classes of attacks can be detected easily by performing pattern matching while the unknown attacks are harder to detect. An attempt has been made to design a system using a deep learning approach for intrusion detection that not only learns but also adjusts itself to the patterns not defined earlier. Sparse auto-encoder has been used for unsupervised feature learning. Logistic classifier is then utilized for classification on NSL-KDD dataset. The performance of the system has been measured with respect to accuracy, precision and recall and the results have been found to be very promising for future use and modifications.
Steganography is the technique of hiding data in an appropriate multimedia carrier, e.g., image, audio, and video files known as Cover. Images are mostly used as the cover medium due to their pervasiveness in different applications and representation with high redundancy. This paper provides a review and analysis of many existing methods for digital image steganography in the spatial as well as transform domain. The performance evaluation of the algorithms with respect to the proposed analysis parameters are summarized along with their limitations inorder to throw some light on the utility of the algorithm as per the requirement of application.
The exponential growth of data and our dependence on it has increased security concerns over the protection of data. Various methodologies have been suggested to meet the security services namely; confidentiality, authentication and authorization. The (k:n) secret sharing scheme was recommended to isolate the dependence on a single entity for the safety of data. Random Grids Visual Secret Sharing (RGVSS), a category of a Visual Cryptography Secret Sharing scheme aims at encrypting a secret image into several shares using a simple algorithm. The encrypted information can be revealed by stacking the shares which can be recognized by the Human Visual System (HVS). The proposed VSS scheme exploits the geometrical configuration of the cube without distorting any of the secret information embedded on the shares. The rest of the secrets are decrypted by stacking the cubes and changing the orientation of one of the cube over the fixed one. Each side of the cube encrypts up to four secrets, the first secret can be decrypted by stacking the two cubical shares and rotating the stacked face of the cube at 90 degrees, 180 degrees and 270 degrees, reveals the other three shares respectively The proposed scheme increases the capacity of secret communication avoiding the pixel expansion problem which in turn reduces the overhead of storage and communication significantly without compromising on security and authenticity of the secret information.
The visual secret sharing (VSS) scheme encrypts the secret information into various meaningless shares. These shares are distributed to the authorized participants and the secret information can be retrieved by any k out of n participants by stacking their respective shares on top of each other. This scheme uses HVS (Human Visual System) to decrypt the information, and thus no technical or financial investment is required. Moreover, it is a one-time pad technique, so decrypting the information by an attacker is almost impossible. This paper proposes an improved visual secret sharing technique in which we aim to build upon the random grid approach of visual cryptography and test the feasibility of Recursive Image Hiding to hide multiple secrets at varying levels of the grids generated. Since we are using circular random grids, it is even possible to hide multiple images in the same grids and obtain the secret images for different angles of rotation of the grids. The participants need to be in possession of both the shares, as well as the fixes angle of rotation for which the secret can be obtained, in order to decrypt the image. In case of recursive image hiding, numerous secrets are hidden recursively in the shares of the original images at each level. Shares carry information for the subsequent secrets as well, thus leading to increased capacity. Also, the limitation on the number of secrets that can be hidden can be overcome because for each grid, multiple secrets can be recursively hidden. Thus, not only will we be able to hide multiple images, but multiple grids as well which in turn carry the information for multiple images. General TermsVisual cryptography, visual secret sharing scheme
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