A high efficient node capture attack algorithm in wireless sensor network based on route minimum key set

2012 ◽  
Vol 6 (2) ◽  
pp. 230-238 ◽  
Author(s):  
Guowei Wu ◽  
Xiaojie Chen ◽  
Mohammad S. Obaidat ◽  
Chi Lin ◽  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Node Capture Attack ◽  
High Efficient ◽  
Node Capture

scholarly journals Optimized and Executive Survey of Physical Node Capture Attack in Wireless Sensor Network

2014 ◽  
Vol 6 (11) ◽  
pp. 26-34
Author(s):  
Bhavana Butani ◽  
◽  
Piyush Kumar Shukla ◽  
Sanjay Silakari ◽  
◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Node Capture Attack ◽  
Node Capture ◽  
Physical Node

scholarly journals Finding Robust Assailant Using Optimization Functions (FiRAO-PG) in Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Piyush Kumar Shukla ◽  
Sachin Goyal ◽  
Rajesh Wadhvani ◽  
M. A. Rizvi ◽  
Poonam Sharma ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Low Cost ◽  
Multiple Objectives ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Cost ◽  
Node Capture Attack ◽  
Cryptographic Keys ◽  
Node Capture

Wireless sensor network consists of hundreds or thousands of low cost, low power, and self-organizing tiny sensor nodes that are deployed within the sensor network. Sensor network is susceptible to physical attacks due to deprived power and restricted resource capability and is exposed to external environment for transmitting and receiving data. Node capture attack is one of the most menacing attack in the wireless sensor network and may be physically captured by an adversary for extracting confidential information regarding cryptographic keys, node’s unique id, and so forth, from its memory to eliminate the confidentiality and integrity of the wireless links. Node capture attack suffers from severe security breach and tremendous network cost. We propose an empirically designed multiple objectives node capture attack algorithm based on optimization functions as an effective solution against the attacking efficiency of node capture attack. Finding robust assailant optimization-particle swarm optimization and genetic algorithm (FiRAO-PG) consists of multiple objectives: maximum node participation, maximum key participation, and minimum resource expenditure to find optimal nodes using PSO and GA. It will leverage a comprehensive tool to destroy maximum portion of the network realizing cost-effectiveness and higher attacking efficiency. The simulation results manifest that FiRAO-PG can provide higher fraction of compromised traffic than matrix algorithm (MA) so the attacking efficiency of FiRAO-PG is higher.

An Outline of Threats and Sensor Cloud Infrastructure in Wireless Sensor Network

2015 ◽  
pp. 412-432
Author(s):  
Bhavana Butani ◽  
Piyush Kumar Shukla ◽  
Sanjay Silakari
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Cloud Infrastructure ◽  
Node Capture Attack ◽  
Node Capture ◽  
Sensor Cloud ◽  
A New Technique ◽  
Commercial Applications

Wireless sensor networks are utilized in vital situations like military and commercial applications, traffic surveillance, habitat monitoring, and many other applications. WSNs have to face various issues and challenges in terms of memory, communication, energy, computation, and storage, which require efficient management of huge amount of sensor data. Therefore, storage is an important issue in the WSN. Emergence of Sensor-Cloud infrastructure overcomes several shortcomings of WSN such as storage capacity and offers high processing capabilities for huge sensor data. Security is also the major challenge that is faced by the sensor network. This chapter includes a brief overview of the importance of cloud computing in sensor networks and the goal of DDoS and Node Capture Attack in WSN. This chapter includes descriptions of different modeling techniques of Node Capture attack and various detection and key pre-distribution schemes to invent a new technique to improve network resilience against node capture attacks.

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