The end of this decade is marked by a paradigm shift of the industrial information technology towards a pay-per-use service business model known as cloud computing. Cloud data storage redefines the security issues targeted on customer's outsourced data (data that is not stored/retrieved from the costumers own servers). In this work we observed that, from a customer's point of view, relying upon a solo for his outsourced data is not very promising. In addition, providing better privacy as well as ensuring data availability, can be achieved by dividing the user's data block into data pieces and distributing them among the available s in such a way that no less than a threshold number of s can take part in successful retrieval of the whole data block. In this paper, we propose a secured cost-effective multi-cloud storage (SCMCS) model in cloud computing which holds an economical distribution of data among the available s in the market, to provide customers with data availability as well as secure storage. Our results show that, our proposed model provides a better decision for customers according to their available budgets.

Mobile ad-hoc networks (MANETs) have attracted significant research attention recently because of the fast growth of laptops, personal digital assistant, and 802.11/Wi-Fi wireless networking. However, the flexible deployment nature and the lack of fixed infrastructure make MANETs suffer from a variety of security attacks. In this paper, we show how an adversary can utilize a colluding injected attack (CIA) in MANET by injecting malicious nodes in the network, while hiding their identities from other legitimate nodes. These injected nodes will work together (colluding) to create a collision at an arbitrary node, thus preventing it from receiving or relaying any packet. Because of this collision, a legitimate node could be reported as malicious nodes by monitoring nodes in the neighborhood. In this work, we propose a monitoring verification scheme to mitigate the effect of the CIA attack. Our proposed scheme is able to accurately detect malicious nodes in the network compared with previous detection schemes. Through simulations, we show that our proposed scheme outperforms previous detection schemes in terms of true/false detection of any malicious behavior in the network caused by the CIA attack.

Interference has been proven to have an effect on the performance in wireless mesh networks (WMN). Using multichannels can improve the performance of WMNs by reducing interference influence. In this paper, we study how to design a robust WMN for a set of mesh nodes, each with Q Networking Interface Cards (NICs) and pre-defined connection requests. Our scheme aims to construct an interference-aware network topology for the nodes, then set up a pair of link-disjoint paths for each request with fault-tolerant capability. We propose two novel schemes to improve the network design. First, we embrace the network interference for providing resource-efficient protections. Second, protection links are shared and reused by multiple connections for protection, which further improves the efficiency of network resource usage. Our simulation results show that our scheme outperformed previous schemes.

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Wireless mesh network (WMN) is a rapid deployed, self organized and multi-hop wireless networks. However, the wireless and distributed natures of WMN make it subject to various kinds of malicious attacks, which raise a great challenge in securing these networks. Most existing security mechanisms are based on cryptographic keys where a high degree key management services are in demand. In this paper, we present an effective secure key management scheme (SKeMS) which seeks an encryption key assignment such that the induced network is securely key connected and well protected against potential malicious eavesdropping attacks. Compared to previous work, our scheme assigns the available encryption keys among all the nodes in the network. Our simulation results show that our scheme outperforms previous schemes through providing a network that is resistant to malicious eavesdropping attack.