International journal of security and its applications 

About: International journal of security and its applications is an academic journal. The journal publishes majorly in the area(s): Encryption & Cloud computing. It has an ISSN identifier of 1738-9976. Over the lifetime, 1159 publications have been published receiving 4934 citations.

A Hybrid Malicious Code Detection Method based on Deep Learning

Abstract: In this paper, we propose a hybrid malicious code detection scheme based on AutoEncoder and DBN (Deep Belief Networks). Firstly, we use the AutoEncoder deep learning method to reduce the dimensionality of data. This could convert complicated high-dimensional data into low dimensional codes with the nonlinear mapping, thereby reducing the dimensionality of data, extracting the main features of the data; then using DBN learning method to detect malicious code. DBN is composed of multilayer Restricted Boltzmann Machines (RBM, Restricted Boltzmann Machine) and a layer of BP neural network. Based on unsupervised training of every layer of RBM, we make the output vector of the last layer of RBM as the input vectors of BP neural network, then conduct supervised training to the BP neural network, finally achieve the optimal hybrid model by fine-tuning the entire network. After inputting testing samples into the hybrid model, the experimental results show that the detection accuracy getting by the hybrid detection method proposed in this paper is higher than that of single DBN. The proposed method reduces the time complexity and has better detection performance.

A Review and Comparative Analysis of Various Encryption Algorithms

Abstract: Now days, Data security is very challenging issue that touches many areas including computers and communication. Recently, we came across many attacks on cyber security that have played with the confidentiality of the users. These attacks just broke all the security algorithms and affected the confidentiality, authentication, integrity, availability and identification of user data. Cryptography is one such way to make sure that confidentiality, authentication, integrity, availability and identification of user data can be maintained as well as security and privacy of data can be provided to the user. Encryption is the process of converting normal data or plaintext to something incomprehensible or cipher-text by applying mathematical transformations or formulae. These mathematical transformations or formulae used for encryption processes are called algorithms. We have analysed ten data encryption algorithms DES, Triple DES, RSA, AES, ECC, BLOWFISH, TWOFISH, THREEFISH, RC5 and IDEA etc. Among them DES, Triple DES, AES, RC5, BLOWFISH, TWOFISH, THREEFISH and IDEA are symmetric key cryptographic algorithms. RSA and ECC are asymmetric key cryptographic algorithms. In this paper, we have analysed various encryption algorithms on the basis of different parameters and compared them to choose the best data encryption algorithm so that we can use it in our future work.

Face Recognition Using Neural Network : A Review

Abstract: Face recognition from the real data, capture images, sensor images and database images is challenging problem due to the wide variation of face appearances, illumination effect and the complexity of the image background. Face recognition is one of the most effective and relevant applications of image processing and biometric systems. In this paper we are discussing the face recognition methods, algorithms proposed by many researchers using artificial neural networks (ANN) which have been used in the field of image processing and pattern recognition. How ANN will used for the face recognition system and how it is effective than another methods will also discuss in this paper. There are many ANN proposed methods which give overview face recognition using ANN. Therefore, this research includes a general review of face detection studies and systems which based on different ANN approaches and algorithms. The strengths and limitations of these literature studies and systems were included, and also the performance analysis of different ANN approach and algorithm is analysing in this research study.

A survey of cyber attack detection strategies

Abstract: Homeland security field deals with diverse subjects, audio processing, video surveillance, image detection, geolocation determination, and cyber attack detection. Audio processing and video surveillance area are significant for public places safety and land border area. However the big threat for homeland security is cyber attacks. Cyber terror attacks and cyber crime attacks may move over virtual networks and can get every home. Nowadays, we consider the homeland security field however we set the cyber attack detection area the highest priority in our research. This paper introduces the overview of the state of the art in cyber attack detection strategies.