LocJam: A novel jamming-based approach to secure localization in wireless networks

Boustani, Arash; Alamatsaz, Navid; Jadliwala, Murtuza; Namboodiri, Vinod

doi:10.1109/ccnc.2014.6866592

Cited by 4 publications

(1 citation statement)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Every SM senses the channel, picks a random element of the matrix, decodes it with appropriate OCS (which it already learnt in the initialization phase) and uses that pseudo-random number to perturb its data. After the j th element of the matrix is fetched and decoded, the SM will jam that element of the matrix (representing an invalid or already-used pseudo-random number) [60]. Assume SM k has fetched and decoded pseudo-random number α j spread with OCS λj .…”

Section: And Consequently Av G I = Av G I ) This Implies Thatmentioning

confidence: 99%

Towards Efficient Privacy Preserving Data Aggregation for Advanced Metering Infrastructure

Alamatsaz¹,

Boustani²,

Alamatsaz³

et al. 2017

IJCNC

Self Cite

View full text Add to dashboard Cite

Recent changes to the existing power grid are expected to influence the way energy is pro-vided and consumed by customers. Advanced Metering Infrastructure (AMI) is a tool to incorporate these changes for modernizing the electricity grid. Growing energy needs are forcing government agencies and utility companies to move towards AMI systems as part of larger smart grid initiatives. The smart grid promises to enable a more reliable, sustainable, and efficient power grid by taking advantage of information and communication technologies. However, this information-based power grid can reveal sensitive private information from the user's perspective due to its ability to gather highly-granular power consumption data. This has resulted in limited consumer acceptance and proliferation of the smart grid. Hence, it is crucial to design a mechanism to prevent the leakage of such sensitive consumer usage information in smart grid. Among different solutions for preserving consumer privacy in Smart Grid Networks (SGN), private data aggregation techniques have received a tremendous focus from security researchers. Existing privacy-preserving aggregation mechanisms in SGNs utilize cryptographic techniques, specifically homomorphic properties of public-key cryptosystems. Such homomorphic approaches are bandwidth-intensive (due to large output blocks they generate), and in most cases, are computationally complex. In this paper, we present a novel and efficient CDMA-based approach to achieve privacy-preserving aggregation in SGNs by utilizing random perturbation of power consumption data and with limited use of traditional cryptography. We evaluate and validate the efficiency and performance of our proposed privacy-preserving data ag-gregation scheme through extensive statistical analyses and simulations.

show abstract

Section: And Consequently Av G I = Av G I ) This Implies Thatmentioning

confidence: 99%