Naoshi Nakaya

Development of System for the Automatic Generation of Unknown Virus Extermination Software

In recent years, there has been a frequent occurrence of virus-related incidents, including cases where a virus infection has caused the unauthorized release of confidential information. Viruses should be considered a society-level security risk. However, the mainstream approach to addressing a virus is basically to implement countermeasures for the virus after the damage has occurred. Some of these countermeasures are unable to keep up with the current pace at which viruses are occurring. To address this problem, in this research, we developed a system to generate unknown virus extermination software automatically, without any manual operations. The developed system is designed to automatically generate software that detects and exterminates an unknown virus, by using both a dynamic heuristic that uses a virtual PC and a technique to automatically generate a signature from header data in the virus executable. We were able to verify the effectiveness of this system when we conducted experiments to check whether or not an actual virus could be exterminated by a vaccine that was automatically created for the virus with the developed system

HACC: Heterogeneous-aware cooperative clustering hierarchy for wireless sensor networks

In this paper we present a low complexity cooperative diversity clustering protocol for heterogeneous wireless sensor networks. Here we analyze the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are clustered in a co-operative fashion to prolong the effective network lifetime. In contrast to these approaches, we propose HACC, a heterogeneous-aware cooperative clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to its residual energy. We then propose a simple modification in the clustering algorithm to exploit virtual MIMO based cooperative transmission. In place of selecting a single cluster head at network layer, we proposed multiple cluster heads in each cluster to obtain a full diversity gain over long distance communication without sacrificing transmission data rate, and established virtual MIMO based cooperative transmission. We treated the cooperative cluster head selection method as a Facility Location Problem (FLP) to gain better energy utilization. Finally, the simulation results demonstrate that our cooperative clustering approach is more effective in prolonging the time interval before the death of the first node (we refer to as stability period) compared to the one obtained using current clustering protocols, and observe that this proposal can achieve higher order diversity gain with improved spectral efficiency when the distance to Base Station is over a given threshold.

Virus extermination by vaccine with pursuit function

Due to the recent increase of computer viruses, anti-virus measures for the safety control of networks occupies the important decision. Since general anti-virus measures depend on the countermeasures by individual users, it is difficult for the network managers to manage these viruses. We propose a novel virus extermination method which enables control of anti-virus measures at the manager level, and evaluate the effectiveness of the proposed method by computer simulations. By using this method, the vaccine which has the infection capability that is equal to the viruses spreads the following viruses and exterminate them. Therefore, it is possible to exterminate all viruses if the network manager prepares some computers that detect and exterminate the viruses.