Digital communication witnesses a noticeable and continuous development in many applications in the Internet. Hence, secure communication sessions must be provided. The security of data transmitted across a global network has turned into a key factor on the network performance measures. So, the confidentiality and the integrity of data are needed to prevent eavesdroppers from accessing and using transmitted data. Steganography and Cryptography are two important techniques that are used to provide network security. In this paper, we survey a number of methods combining cryptography and steganography techniques in one system. Moreover, we present some differences between cryptography and steganography. The aim of this paper is to develop a new approach to hiding a secret information in an image or audio or video, by taking advantage of benefits of combining cryptography and steganography. In this method first, the message is encrypted by using AES algorithm and hashed the key using SHA-2 to prevent from attacks. After that, we performed some modifications on LSB algorithm by adding a key to make hiding process non sequential. Results achieved indicate that our proposed method is encouraging in terms of robustness and security.

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Abstract-In this paper, we propose a novel method using ensemble learning scheme for classifying network intrusion detection from the most renowned KDD cup dataset. We have shown that reducing the dimensionality of the large dataset provides most accurate detection. Additionally, several machine learning algorithms are used to generate the accuracy metrics and analyzed further for proper comparison. Our approach found out that this algorithm outperforms all other learning techniques. Our goal is to analyze the network intrusion data and find out the best components and use them for the attack analysis. This scheme can be used in parallel with the intrusion detection system to augment its prediction performance for the future data packets. Empirical results show that the input dimensionality reduction can provide lightweight intrusion detection system that can be embedded with the vulnerable system for generating correct classification with significance improvement in execution time.

Cloud computing is a significant model for permitting on-demand network access to shared data, software's, infrastructure, and platform resources. However, cloud storage needs a certain level of availability, confidentiality, and integrity. Information sensitivity and value encourage users to select a highly secure protocol. This work proposes a new mechanism to increase the user trust in cloud computing using the secret sharing technique. The proposed algorithm is using Base64 encoding to convert any file type to ASCII strings. Base64 strings do not need any extra process to be compressed and this can speed up the share building process. Each string is used to produce N shares (using Shamir Secret Sharing Scheme) where each share is stored in a separate location in the cloud.