Monday, August 20, 2012



Research Paper Summary-Engg. Branch (CS)
Title: A Fault Tolerant, Secure and Distributed Group Key Diffie Hellman Key  
             Exchange Protocol for Mobile Adhoc Networks
          National conference on “Advances in Computer Networks and Information Technology (NCANIT)”
1.   Abstract
      A mobile adhoc network (MANET) is a Multi hop wireless network capable of autonomous operation and requiring no infrastructural support. The purpose of an adhoc network is to set up possibly a short lived network for a collection of nodes. Security in mobile adhoc networks is difficult to achieve notably because of vulnerability of wirelees links, limited physical protection of nodes, dynamically changing topology, absence of certification authority and lack of centralized monitoring or management point.
                    In this paper they present, design and implementation of a A Fault
Tolerant, Secure and Distributed Group Key Diffie Hellman (FASED-GDH) Key    Exchange Protocol which is a n-party generalization of the basic two party Diffie-Hellman Protocol for key exchange. FASED-GDH is a ring based protocol in which each peer contribute its partial factor for the final establishment of secure session key. The protocol provides a secure multicast of pseudo final key leading to an inbuilt intrusion detection system. The protocol is simple as compared to previous approaches. Failure of a subset of nodes leaves the system unaffected, thereby proving its robustness and fault tolerance.




2.   Introduction
Group Key Diffie Hellman protocol provides both the things: it uses public key technique to allow the exchange of a private encryption key. It is an Authenticated Key Exchange protocol which is designed to provide a pool of players with a shared secret key which may later be used. For example: to achieve multicast message integrity.Over the years the several schemes have been proposed. However no formal treatment for cryptographic problem is suggested. In this paper, they present a security model, FASED-GDH, for this problem and use it to precisely define AKE as the fundamental goal. In AKE, each player is assured that no other player aside from the arbitrary pool of players can learn any information about the session key.They then define in this model the execution of an authenticated group Diffie-Hellman scheme and prove its security.
3.   System Model
In FASED-GDH they have assumed a session of adhoc network which consist of a collection of nodes or peers that need a secret secure session key to start the communication. The system design for this establishment of key is as follows:
Each peer can act as both client and server. Any peer who wants to start the communication named Init Server sends its contribution to its neighbor, the neighbor add its contribution and then sends the combined result to its neighbor.
This process goes on till the final establishment of key. Now the destination server will not send this final key to remaining peers instead it send their partial factor to the corresponding peers which then further add their own private factor for the final establishment of key.

Research Paper Summary-IE
  Title: Optimization of cutting in primary wood transformation in industries
            Published In Journal of Industrial Engineering Management
Summary:


Need: Raw materials loss in wood cutting industries has reached high ratios (30 to 36% of volume yield). The purpose of this paper is to solve the problem of optimising the production on the basis of the commercial value of the cuts.
Architecture: To tackle this problem, they started with the general method of primary conversion of wood in Cameroon. After that, they studied the various methods of cutting and the different products obtained. They then proceeded with the formulation of the log cutting optimisation  problem  based  on  real  shape  model  of  the  logs. They finally completed their work with the design and the presentation of a software package called cutting optimiser.
          Calculation Model: Dynamic programming is used by them which is a
          method of  exact sequential optimisation problems.The  formalism    
         of dynamic   programming leads to many possibilities and variants. As a   
         general rule,   it is a problem (P) whose goal is to optimise a series of
        decision making with respect to the cost it involves. Here they consider
         theKnapsack Problem” denoted here as KP, is a problem of
         combinatorial optimisation
           Limitations:  In this paper,  the  optimisation  problem concerns problems       
           where the objective function is non-explicit, the variables discreet, and the
           constraints non-explicit.


Results: They start by having some knowledge on the geometry of the logs, cutting strategies and classification of cuts. This classification enables them to determine the quality and quantity of the production, and to estimate the commercial value of the log. The solution to this problem then led to the design of a software package.

Application: The solution to this problem then led to the design of a software package to be themed as a cutting optimiser. The automation of the cutting operation leads to an accelerated work and an increase in the volume of the cuts produced daily.

Difficulties: This research is among the few to solve discrete optimization problems with constraints. Some constraints concerning the mechanical characteristics of the logs are taken into account. The constraints can equally be non-explicit.  Moreover the market standards  impostechnological  constraints which render the problem of optimisation even more complex
             Conclusion: The purpose for this work was to develop a production   
            optimising tool in primary  conversion wood industrieof Cameroon. This
         technological procedure enables enterprises to improve on the material
         output of the transformed wood and also on their  profitability.  The
           modelling of the real shape of the log enabled us to identify the input
           parameters to generate the log in real shape. The formulation of the
            optimisation problem similated to a knapsack problem was solved using the
            method of dynamic programming. That enabled us to set up an algorithm for
            optimum cutting of the log, alongside a cutting optimiser.
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