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DNA based steganography plays a vital role in the field of privacy and secure communication. Here, we propose a DNA properties-based mechanism to send data hidden inside a video file. Initially, the video file is converted into image frames. Random frames are then selected and data is hidden in these at random locations by using the Least Significant Bit substitution method. We analyze the proposed architecture in terms of peak signal-to-noise ratio as well as mean squared error measured between the original and steganographic files averaged over all video frames. The results show minimal degradation of the steganographic video file. Keywords: Chaotic map, DNA, Linear congruential generator, Video steganography, Least significant bit

Cybercrimes and phishing scams have increased multi-folds over the past few years. Now a days, hackers are coming up with new techniques to hack accounts and gain sensitive information about people and organisations. Social networking site like Twitter is one such tool. And due to its large audience hackers use such sites to reach large number of people. They use such sites to circulate malicious URLs, phishing mails etc. which serve as the entry point into the target system. And with the introduction of Twitter Bots, this work got even easier. Twitter bots can send tweets without any human intervention after a fixed regular interval of time. Also their frequency of tweets is much more than humans and therefore they are frequently used by hackers to spread malicious URLs. And due to large number of active members, these malicious URLs are reaching out to more people, therefore increasing the phishing scams and frauds. So this paper proposes a model which will use different algorithms of machine learning, first to detect twitter bots and then find out which of them is posting malicious URLs. In the proposed model, some features have been suggested which distinguishes a twitter bot account from a benign account. Based on those statistical features, model will be trained. The model will help us to filter out the malicious bots which are harmful for legitimate users.

Medical Image protection is one of the primary concerns of health care services. There has been a lot of research in this field in the past decade. But unfortunately, in India, the implementation is very poor and unstructured. In this paper, a secured model for MRI image encryption and decryption using DNA Encoding and Logistic Chaotic Map is proposed. Initially a key is generated using logistic map function to generate a sequence K1,i this sequence is multiplied with a factor of 255, another sequence K2,i generated from Linear Feedback Right Shift Register (LFRSR) using an initial seed value, then both the sequences are XORed to form the key. After the key is generated the sequence is again XORed with the 8-bit image pixel of the MRI Image. The generated cipher is then converted into a DNA sequence using DNA Encoding. The generated text of DNA sequence is then passed to the network. This sequence is extremely secure and robust, the Root Mean Square Error (RMSE) value measured between the original and encrypted sequence is very high.

Expression detection or Emotion Recognition is one of the rising fields of research on intelligent systems. Emotion plays a significant role in non-verbal communication. An efficient face and facial feature detection algorithms are required to detect emotion at that particular moment. The paperpresents a new approach to the problem of extracting the facial components from a still facial image which will be used further for Facial Expression detection. Robust extraction of such facial feature locations is a crucial problem which is used in a wide range of applications. Facial features such as lip corners, eye corners and nose tip are critical points in a human face. Thepaper approach relies on image segmentation based on skin color algorithm and fiducial point detection. First, the face region is extracted from the image by skin-color filter and window growing. Second, eyes and mouth are approximately located by projection of fiducial point. It is been observed for subjects not wearing glasses, the extraction of eyes could be correctly located in 94% of the images and in over 90% of these images they could be accurately extracted, while for subjects wearing glasses, the success rate is somewhat lower. Also, in certain moods or depending on the facial expression, the detection of lips in case of mouth opening and closing varies which can also be extracted by our method. Keywordsextraction, fiducial point, facial expression.

In this paper, a new steganography method for spatial domain has been proposed, which includes a new mapping technique for the secret messages. The algorithm coverts any kinds of message to text using bit manipulation tables, applies hill cipher techniques to it and finally hides the message into red, green and blue images of a selected image. Therefore, the proposed algorithm is a combination of encryption of the message first then hiding the message into the cover image which provides double security. The result of the proposed algorithm is analyzed and discussed using MSE, PSNR, SC, AD, MD and NAE. The histogram of the cover and stegano image is also shown.