Earticle

Co-evolutionary mechanism is now used into evolutionary algorithms and provides these algorithms the power to promote the convergence. In order to promote the performance of the traditional quantum-inspired evolutionary algorithm (QEA), we proposed a novel quantum-inspired co-evolutionary algorithm (NQCEA), in this paper. The quantum state population is firstly divided into multiple sub-populations, which complete the evolution processes independently. In each evolution cycle, every sub-population will produce an elitist individual, which is then selected to construct an elite library. Subsequently, these individuals in this elite library can help the poor sub-population to find the global optimal solution or near-optimal solution. In addition, a diversity indicator is defined for every sub-population and is used to measure the diversity of the corresponding sub-population. As for the sub-population with poor diversity, the mutation strategies are implemented in order to expand its diversity and improve its global search ability. Finally, the NQCEA is compared with the traditional QEA to test their performance. Experiments are performed on the global numerical optimization functions and the simulation results indicate that this new algorithm has the characteristics of good global search capability and more stable performance than the traditional QEA.

Since the separation of the control plane and the data plane for Software-Defined Networking (SDN) leads to more and more security threats on the control plane and the SDN controllers, issues related to threat detection and defense of SDN must be seriously considered. This paper tries to introduce Extenics into the research on threat detection and defense of SDN and proposes an extension approach from a formal viewpoint. It first uses the matter-elements and the composite-elements to formally represent four security-related roles of SDN. It then utilizes the extension theory and basic-elements, by applying the dependent function to threat detection of SDN and making use of the affair-elements to formalize the NETCONF operations for threat defense of SDN. Finally, case study validates the feasibility of proposed extension approach in promoting the formalization of not only the security-related roles of SDN but also threat detection and defense of SDN.

Security in terms of Networks have turn out to be more significant to Organizations, Military and personal computer user’s. Since various kinds of threats are for data from sending it from sender side over internet till it reaches to receiver. Here we will focus on SSL it is a technique used to give client and server authentication, data confidentiality and data integrity. It transform our data into unintelligible form, data which we will be sending can be text or no text form, by encrypting our data we can save it from attacks like eavesdropping, in which interception of communication by unauthorized person, he can either listen or can add malicious information in our data which can lead to catastrophic results. This technique of secure data transmission is very useful in securing the integrity of data sent by the Unmanned Aerial Vehicles in military application to commercially used Electricity meter. Since the above mentioned devices uses microcontroller to send data through internet hence this data is always going to be susceptible to above mentioned threats so it is important to ensure that it doesn’t fall in wrong hands, our objective is that our microcontroller sends the data to remote location has authenticity, confidentiality and integrity. First we will send some meaningful text already stored in controller of STM3240G Eval-board then that data will be sent to server. These encrypted packets will be sending to remote server through Ethernet. At the receiver end this data will be received and decrypted to get the original captured data.

To establish pairwise keys for each pair of neighboring sensor nodes is a basic service, forming the basis other security services, such as authentication and encrypted in wireless sensor networks (WSNs). However, due to constrained energy, memory, and computational capabilities of sensor nodes to establish the pairwise key is challenging task. Here, a combination of polynomial pool-based and the probabilistic key predistribution scheme for WSN is presented. In the proposed scheme part of sensor nodes are pre-loaded polynomial shares, and the polynomial shares are used to compute the keys which make up a key pool. And the rest of sensor nodes are preloaded the keys selected from this key pool. The proposed scheme is analyzed based on connectivity, resistance against attacks, memory consumption and communication overhead. And the simulation results show that the proposed scheme performs better in terms of network resilience to node capture compared to the existing schemes.

In this paper, Linear Feedback Shift Register (LFSR) based IPv6 address generation has been proposed for low IP acquisition time during handoff in Vehicular Adhoc Networks (VANET). The mechanism reduces handoff latency and packet loss rate by removing link layer address conflict and duplicate address detection (DAD). VANETs are characteristics by frequent handoffs that need regular address reconfiguration which increases the handoff latency. The latency increases further due to the need for DAD to prevent link layer address conflict. LFSR based IPv6 in VANET decreases the address reconfiguration time and handoff latency by providing a unique seed value in Router Advertisement (RA) which is generated through modified LFSR algorithm and is combined with vehicle’s MAC ID to give a unique host ID. Since the mechanism is able to generate different unique host ID for same MAC ID, it eliminates the need of DAD by minimizing the probability of link layer address conflict to a negligible value. This also increases the IP configuration scalability. The algorithm only modifies the control signal RA and does not require any change in the VANET architecture. Simulation results confirm that this mechanism performs better than Mobile IPv6 (MIPv6) and can be incorporated as a standard IP acquisition technique for high mobility networks like VANET.

The development of the Internet brought us into an era of big data information, give people bring convenient while and also make people ragged when choosing the required information and recommendation system arises at the historic moment, and get the wide attention and applications. Therefore, to enhance the traditional method, we propose a novel intelligent recommendation algorithm based on Web data mining technique under the background of the deep neural network. Firstly, we review the state-of-the-art web data mining algorithms and revise the traditional ones with the parallel data mining algorithm on the multiple processors to perform tasks that will enhance the accuracy and efficiency. Then, we analyze basic neural network model through the inner connection and weight transfer. Later, we introduce the deep network structure to enhance the traditional network. Finally, we combine the revised prior theories into the recommending tasks for enhancement. The experimental analysis show that our algorithm accuracy is enhanced by the extent of 56% and overall time is reduced to the 87% of traditional ones which proves the feasibility. Later, more optimization work will be introduced to modify the current methodology.