Tania , Bhaskaracharya College of Applied Sciences, (University of Delhi); Srishti Prajapati, Bhaskaracharya College of Applied Sciences, (University of Delhi); Sarika Jha, Bhaskaracharya College of Applied Sciences, (University of Delhi); Sohil Jain, Bhaskaracharya College of Applied Sciences, (University of Delhi); Tejpal Dhewa, Bhaskaracharya College of Applied Sciences, (University of Delhi)
GIT, GDP, DNA
Today there is an emerging need to develop technique and tools for detecting microorganism useful in different sectors including food safety, health, agriculture, defense, etc. Already there are many detection methods, but due to some limitations, these not suitable for commercial applications. However, an intensive research for the commercial biosensor still under progress. In this paper, we intend to present the essence for such sensors with the review of present and future trends. Also, we hereby propose a viable design that could achieve the required goals at low cost.
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Call For Journal Paper and Publishing :
Research Paper On :
PRIVACY PRESERVING AGAINST NETWORK
INTRUSION DETECTION IN VIRTUAL NETWORK SYSTEM
SHRUTHI S , RNS INSTITUTE OF TECHNOLOGY
Cloud security is one of most important issues that has attracted a lot of research and development effort in past few years. Particularly, attackers can explore vulnerabilities of a cloud system and compromise virtual machines to deploy further large-scale Distributed Denial-of-Service(DDoS). DDoS attacks usually involve early stage actions such as multi-step exploitation, low frequency vulnerability scanning, and compromising identified vulnerable virtual machines as zombies, and finally DDoS attacks through the compromised zombies. Within the cloud system, especially the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is extremely difficult. This is because cloud users may install vulnerable applications on their virtual machines. To prevent vulnerable virtual machines from being compromised in the cloud, we propose a multi-phase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph based analytical models and reconfigurable virtual network-based countermeasures.
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