K. Eepsita Saranya

Bio: K. Eepsita Saranya is an academic researcher from K L University. The author has contributed to research in topics: Cryptography & Computer science. The author has an hindex of 1, co-authored 2 publications receiving 3 citations.

Security Enhancement in Image Steganography a MATLAB Approach

Abstract: Steganography helps in communication of secured data in several carries like images, videos and audio. It undergoes many useful applications and well known for ill intentions. It was mainly proposed for the security techniques in the increase of computational power, in order to have security awareness like individuals, groups, agencies etc. The factors that are separated from cryptography and water making are data is not detectable; capacity of hidden data is unknown and robustness of medium. The steganography provides different methods existing and guidelines. The current technology of image steganography involves techniques of LSB in image domain but once the attacker acknowledges that medium is containing embedded data he will attack the medium and breaks into the secured content. In this paper we are discussing how to protect the steganography image by embedding it into another medium using mat lab. Here we work on image matrices to perform the steganography. Lightness adjustment on the matrix is done to reduce the brighter pixels in image. The lightness decreased image then embedded into another cover image by matrix difference technique (will be discussed in detail). This enhances the security to a higher level because to acquire the steganography image embedded we need to have the key image which will be having only by the receiver. And from millions of images on the internet it is impossible for an attacker to guess the key image. And this enhances the level of security.

Detecting Malicious URLs using Data Analytics

Abstract: Phishing is a type of social engineering hack in which attackers trick victims into providing their login information on a form that sends the information to a malicious server. The fast developing subfield of data science is dependent on the application of machine learning as a central component. One vs All Classification is a strong machine learning technique that may be used to detect dangerous URLs by classifying them as belonging to one of several categories, such as malware, phishing, or spam. This algorithm can be used to detect malicious URLs by classifying them as belonging to one of these categories. Training numerous binary classifiers is required for this method. Each of these classifiers is responsible for differentiating one category from the others. The suggested approach makes use of One Vs All Classification in order to obtain a high level of accuracy in the detection of dangerous URLs. It is possible to train the system using a tiny dataset that just includes the pertinent aspects of the URLs, such as the domain and the path. In conclusion, one vs All Classification is a promising strategy for detecting malicious URLs. It can deliver high accuracy even with tiny datasets and low computational resources, which is a significant advantage over existing approaches.

A Novel Approach for Implementing LFSRs Using QCA Technology

Abstract: Quantum random number generators have attracted the research community for providing secure communication. This paper presents a novel Quantum LFSR, designed using the novel construction of D-Flip-Flop (DFF) and XOR gates in QCA. The suggested Quantum LFSR comprises 216 cells with an area of 0.23μm2 and the total power dissipation is 0.31442 eV, 0.41729 eV, and 0.54389 eVat different standard tunnelling energy levels. The power parameters are analysed using QCA Pro, and the calculated outcomes show that the Quantum LFSR has low power consumption and reduced footprint compared to conventional designs.

Application of MFFC and Edge Detection for Remote Driven Vehicles Through Matlab

Abstract: Speech recognition is a rapidly emerging technology in Human Computer Interaction HCI. It has many applications as we use it from search engines to the device control it serves many areas we interact every day from dawn to dusk. Along with the uses we have many limitations in speech processing such as Language barrier, Accent and Noise, so to implement the speech processing we have many challenges. To enable the advantages of this speech processing most of the leading software companies like Apple, Microsoft and Google are continuously evolving their speech enabled applications. The speech processing eases the physically challenged people’s interaction with the devices and makes them productive. The Idea of the automatically driven cars is introduced by Google and Audi, but they are not acceptable in most of the cases because of lacking trust in current technology. Thus we here worked on the remote driven vehicle in a more secured method using the Mel Frequency cepstral Coefficient. The secure driving of the vehicle can be ensured by the remote driver. This technique is very rapid and more reliable for the speech detection thus the remote driver can use the MFCC and the video from the vehicle needed to be broadcasted to the remote driver that can be done an IP camera running on a data network. And the instructions can from the remote driver can be sent to the vehicle by an app created with python that connected to a micro controller. To minimize the limitations in the remote drive the vehicle must be enabled with automatic braking when obstacle approaches which can be done by the Ultrasonic sensors that do the distance estimation. The remote drivers usually have a very limited view of road they drive and they must get the precise edges of the road this can be achieved by processing the stream of images to calculate the edge in Matlab.

Improvement of Image Steganography Using Discrete Wavelet Transform

Abstract: Recently the Discrete-Wavelet-Transform (DWT) has been represented as signal processing powerful tool to separate the signal into its band frequency components. In this paper, improvement of the steganography techniques by hiding the required message into the suitable frequency band is presented. The results show that the increase of the message length will reduce the Peak Signal to Noise Ratio (PSNR), while the PSNR increases with the increasing the DWT levels. It should be noted that the PSNR reduction was from -13.8278 to -17.77208 when increasing the message length from 161 to 505 characters. In this context, the PSNR is increased from -13.8278 to 7.0554 and from -17.7208 to 1.7901 when the DWT increased from level (1) to level (2).

Analysis of Image Steganography Performance Check Using Bit Selection

Abstract: Hidden communication is important since ancient times to provide the secrecy of information which may be for personal work or for professional work. In the ancient times cryptography was the main method for secret communication. In cryptography message is encrypted in some way but the existence of message is known to the third party which gives the possibility of hacking of the message by third party easily. Here comes the use of steganography which overcomes the drawback of cryptography. In steganography the existence of message is not known to the third party that makes it easy for two parties to communicate in an imperceptible manner. There are various techniques using steganography. Following work has been done using bit steganography in which bits of one image have been used which is called cover image to hide message image. This technique has been used on every bit of each pixel of cover image starting from LSB to MSB and then comparison of results has been done on the basis of mean square error ad peak signal to noise ratio.

A Novel Approach of Encoding for Image Steganography with Reduced Data Content

Abstract: Image Steganography is the technology that is being used to provide secure communication between the sender and the receiver. As the technology enhances, security becomes the important concern. Thus, image Steganography helps in embedding the data behind the image with the original image so that unauthorized user cannot access the data. In this paper, different techniques of image Steganography are discussed. This paper also concludes the comparison of the proposed technique with the existing techniques. Encoding of the data will reduce the risk of data tampering by unauthorized user and increase the security of the system. So the image format conversion is also used that will provide additional security to the data. Experiments have been performed with the proposed and existing technique and result proves that the efficiency of the proposed method is better in terms of security.