| Título: | A RESOURCEFUL PRIVACY SAFEGUARDING METHOD AGAINST TRAFFIC ANALYSIS ATTACKS |
| Autores: |
Subbaiah, S.Venkata; M.Tech Student, Dept of CSE, RRS College of Engineering and Technology, Patancheru,
Medak, A.P, Pravallika, A.; Assistant Professor, Dept of CSE, RRS College of Engineering and Technology, Patancheru, Medak, A.P |
| Fecha: | 2013-08-07 |
| Publicador: | International journal of computer and electronics research |
| Fuente: |
 |
| Tipo: | Peer-reviewed Article |
| Tema: | Privacy Safeguarding; Multi-hop Wireless Networks, Traffic Analysis Attacks; Onion Routing; Global Encoding Vectors |
| Descripción: | Wireless access networks have been extensively deployed due to their ease, portability, and low cost. For expanding the radio coverage range of the accessible wireless networks, a Multi-hop Wireless Networks (MWNs) are considered as extremely capable solution and they can also be used to get enhance the system reliability through multi-path packet forwarding. However, due to the open wireless medium, MWNs are vulnerable to a variety of attacks, such as eavesdropping, data alteration and node compromising. Due to the open wireless medium attacks the traffic analysis and flow tracing can be easily initiated by a hateful adversary as privacy hazard is one of the significant issues in multi-hop wireless networks. Since the network coding has the potential to prevent these attacks as the coding operation is encouraged at intermediate nodes. However, the simple consumption of network coding cannot accomplish the goal once adequate packets are collected by the adversaries. On the other hand, the coding nature averts the possibility of employing the available privacy safeguarding methods, such as Onion Routing. A novel network coding based privacy safeguarding scheme against traffic analysis in multi-hop wireless networks is proposed in this paper. The proposed scheme offers two important privacy preserving features with homomorphic encryption on Global Encoding Vectors (GEVs). The packet flow un-traceability and message content confidentiality are two features for resourcefully preventing the traffic analysis attacks. |
| Idioma: | Inglés |
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