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Cyril Okpoli, Michael Oladunjoye and Toluwaleke Ajayi

, Expanded Abstracts, 338-343. [15] Shima, H., (1992). 2D and 3D resistivity image reconstruction using crosshole data: Geophysics, 57, 1270-1281. [16] White, P.A., (1994). Electrode arrays for measuring groundwater flow direction and velocity:Geophysics, 59, 192-201. [17] Park, S., (1998). Fluid migration in the vadose zone from 3D inversion of resistivity monitoring data: Geophysics, 63, 41-51. [18] Binley, A.S. Henry-Poulter, and B. Shaw, (1996). Examination of solute transport in an undisturbed soil column

Open access

Chen Liu, Hoda Aghaei Khouzani and Chengmo Yang

Abstract

Securely deleting invalid data from secondary storage is critical to protect users’ data privacy against unauthorized accesses. However, secure deletion is very costly for solid state drives (SSDs), which unlike hard disks do not support in-place update. When applied to SSDs, both erasure-based and cryptography-based secure deletion methods inevitably incur large amount of valid data migrations and/or block erasures, which not only introduce extra latency and energy consumption, but also harm SSD lifetime.

This paper proposes ErasuCrypto, a light-weight secure deletion framework with low block erasure and data migration overhead. ErasuCrypto integrates both erasurebased and encryption-based data deletion methods and flexibly selects the more cost-effective one to securely delete invalid data. We formulate a deletion cost minimization problem and give a greedy heuristic as the starting point. We further show that the problem can be reduced to a maximum-edge biclique finding problem, which can be effectively solved with existing heuristics. Experiments on real-world benchmarks show that ErasuCrypto can reduce the secure deletion cost of erasurebased scheme by 71% and the cost of cryptographybased scheme by 37%, while guaranteeing 100% security by deleting all the invalid data.

Open access

Oluseun Adetola Sanuade, Rasheed Babatunde Adesina, Joel Olayide Amosun, Akindeji Opeyemi Fajana and Olayiwola Grace Olaseeni

. Geological Survey Nigeria Bulletin, 40, pp. 725-731. [13] Krishanaiah, S. (2003): Centrifuge modelling of heat migration in geomaterials. Ph.D. Thesis, IIT Bombay: India. [14] Sheldrick, B.H., Wang, C. (1993): Particle size distribution. P. 499-511. In Carter (ed.) Soil sampling and methods analysis. Canadian Society of Soil Science: Lewis Publishers. Ann Arbor. [15] ASTM D7928-17 (2017): Standard test method for particle size distribution (gradation) of fine grained soils using the sedimentation (hydrometer) analysis. ASTM

Open access

Jakob Novak

., Wolf, D., Phillpot, S. R., Furtkamp, M. (1997): Molecular-dynamics method for the simulation of grain-boundary migration. Interface Science , 5, pp. 245–262. [8] Yamakov, V., Wolf, D., Phillpot, S. R., Mukherjee, A. K., Gleiter, H. (2002): Dislocation processes in the deformation of nanocrystalline aluminium by molecular-dynamics simulation. Nature Materials , 1, pp. 45–49. [9] Yamakov, V., Wolf, D., Salazar, M., Phillpot, S. R., Gleiter, H. (2001): Length-scale effects in the nucleation of extended dislocations in nanocrystalline Al by molecular