Abstract Cloud computing enables sharing of resources and services. In the cloud computing the client (user) puts his data in the cloud, and any computations on his stored data will be implemented in the cloud. To produce the effective services, some of the cloud service providers share the information with third parties. The third party can reach to the client private... Cloud computing enables sharing of resources and services. In the cloud computing the client (user) puts his data in the cloud, and any computations on his stored data will be implemented in the cloud. To produce the effective services, some of the cloud service providers share the information with third parties. The third party can reach to the client private data and modifies the information to make it beneficial to him. Therefore, the security becomes the main thing in cloud computing. The scheme that allows to executing several computations on the encrypted message without decrypting the message is called homomorphic encryption. This paper provides a Fully Homomorphic Encryption Scheme SA that we can apply it for security of a cloud computing. The proposed scheme is based on Euler’s theorem, which proved both addition and multiplication operations at the same time on ciphertext without decryption. We compute the time complexity of the encryption and decryption function for the Elgamal and RSA cryptosystems compared to the proposed SA scheme and also compared the execution time among the three schemes with varies sizes of messages and varies lengths of secret key, and finally the security of the three schemes is analyzed. As a result, in calculations of the execution time of ElGamal and RSA cryptosystems compared to the proposed SA scheme, it was observed that the length of the secret key effect on the execution time, in which the execution time increased when the length of the private key was increased. The proposed scheme showed a good security for the stored data on the cloud. Read More Read Less

Abstract Malware is a major computer security concern as many computing systems are connected to the Internet. The number of malware has increased over the years and new malware has emerged, where new variants are capable of evading conventional system detection through obfuscations. One of the promising methods used to detect malware is machine learning (ML) techniques. This work presents a static malware detection... Malware is a major computer security concern as many computing systems are connected to the Internet. The number of malware has increased over the years and new malware has emerged, where new variants are capable of evading conventional system detection through obfuscations. One of the promising methods used to detect malware is machine learning (ML) techniques. This work presents a static malware detection system using n-gram and machine learning techniques, using known malware subsignatures to reduce large feature search spaces, which are generated due to n-gram feature extraction methods. The feature space directly affects the performance and the detection accuracy of malware ML classifiers. Analysis of multiple feature selection methods to minimize the number of features and analysis of multiple ML classifiers are also presented to improve the malware detection accuracy. The results show that analyzing n-gram with Snort sub-signature features using machine learning give good malware detection accuracy of more than 99.78% and zero FPR when 4-gram features are used for most of the verified ML classifiers. Read More Read Less

Abstract Internet of things (IoT) is considered as a new technology to connect the resource-constrained things to the unreliable and untrusted world of the Internet through IPv6 and 6LowPAN network. The things are exposed wireless attacks from inside or outside the network. To prevent against these attacks, the existence of Intrusion Detection Systems (IDS) are necessary. In this paper, we design, implement, and evaluate... Internet of things (IoT) is considered as a new technology to connect the resource-constrained things to the unreliable and untrusted world of the Internet through IPv6 and 6LowPAN network. The things are exposed wireless attacks from inside or outside the network. To prevent against these attacks, the existence of Intrusion Detection Systems (IDS) are necessary. In this paper, we design, implement, and evaluate our IDS. We implement the IDS in Contiki OS and evaluate it. The result of the evaluation shows the positive rate of IDS is 100% when the the malicious node is in the range of the IPv6 Border Router (6BR). We challenged our IDS in divergent position of the malicious node. However, the true positive rate depends on the position of the malicious node on the network. Read More Read Less