31-07-2012, 01:41 PM
Achieving Network Level Privacy in Wireless Sensor Networks
Achieving Network Level Privacy in Wireless Sensor Networks.doc (Size: 402 KB / Downloads: 22)
Abstract:
Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem.
The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks.
Project Goal:-
Efficiency of Sensor Network is
• Energy,
• Memory
• Computation power
Application Area is Health-care, Military, Habitat monitoring ect
1.Sender node identity privacy: no intermediate node can get any information about who is sending the packets except the source, its immediate neighbors and the destination,
2. Sender node location privacy: no intermediate node can have any information about the location (in terms of physical distance or number of hops) about the sender node except the source, its immediate neighbors and the destination,
3. Route privacy: no node can predict the information about the complete path (from source to destination). Also, a mobile adversary gets no clue to trace back the source node either from the contents and/or directional information of the captured packet(s),
4. Data packet privacy: no node can see the information inside in a payload of the data packet except the source and the destination.
Existing System:-
Existing privacy schemes such as, that have specifically been proposed for WSNs only provide partial network level privacy. Providing a full network level privacy is a critical and challenging issue due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor network (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and trustworthiness). Thus, an energy-efficient privacy solution is needed to address these issues. In order to achieve this goal, we incorporate basic design features from related research fields such as geographic routing and cryptographic systems. To our knowledge, we propose the first full network level privacy solution for WSNs.
Proposed System:-
.
• A new Identity, Route and Location (IRL) privacy algorithm is proposed that ensures the anonymity of source node’s identity and location. It also assures that the packets will reach their destination by passing through only trusted intermediate nodes.
• A new reliable Identity, Route and Location (r-IRL) privacy algorithm is roposed, which is the extension of our proposed IRL algorithm. This algorithm has the ability to forward packets from multiple secure paths to increase the packet reach-ability.
• A new data privacy mechanism is proposed, which is unique in the sense that it provides data secrecy and packet authentication in the presence of identity anonymity.
Adversary Model
We have assumed that an adversary can mostly perform passive attacks (like eavesdropping ,and traffic analysis), since such attacks helps to conceal the adversary’s presence in the network. Nevertheless, the adversary is also capable of performing some active attacks like fabrication and packet drop attacks. We also assumed that the adversary is both device-rich and resource-rich. These
characteristics are defined below.
• Device-rich: the adversary is equipped with devices like antenna and spectrum analyzers, so thatthe adversary can measure the angle of arrival of the packet and received signal strength. These devices will help the adversary to find out the immediate sender of the packet and move to that node. This kind of hop-by-hop trace back mechanism will be carried out by the adversary until the actual sender node is reached.
• Resource-rich: the adversary has no resource constraint in computation power, memory or energy. It is also assumed that the adversary has some basic domain knowledge like the range of identities assigned to the sensor nodes, the public key of the base station and information about the cipher algorithms used in the network. However, adversary has no knowledge which identity is physically
associated with which node.
A detection and prevention strategy against non-privacy disclosure attacks at various layers such as jamming attacks is out of the scope of this paper. However, trust management methodology that we adopted in this paper is useful to detect and prevent some non-privacy disclosure threats such as, black hole attack, sink hole attack, and selective forwarding or gray hole attack.