Due to recent indiscriminate attacks of ransomware, damage cases including encryption of users’ important files are constantly increasing. The existing vaccine systems are vulnerable to attacks of new pattern ransomware because they can only detect the ransomware of existing patterns. More effective technique is required to prevent modified ransomware. In this paper, an effective method is proposed to prevent the attacks of modified ransomware on Android platform. The proposed technique specifies and intensively monitors processes and specific file directories using statistical methods based on Processor usage, Memory usage, and I/O rates so that the process with abnormal behaviors can be detected. If the process running a suspicious ransomware is detected, the proposed system will stop the process and take steps to confirm the deletion of programs associated with the process from users. The information of suspected and exceptional processes confirmed by users is stored in a database. The proposed technique can detect ransomware even if you do not save its patterns. Its speed of detection is very fast because it can be implemented in Android source code instead of mobile application. In addition, it can effectively determine modified patterns of ransomware and provide protection with minimum damage.
Thermal motion in complex fluids is a complicated stochastic process but ubiquitously exhibits initial ballistic, intermediate subdiffusive, and long-time diffusive motion, unless interrupted. Despite its relevance to numerous dynamical processes of interest in modern science, a unified, quantitative understanding of thermal motion in complex fluids remains a challenging problem. Here, we present a transport equation and its solutions, which yield a unified quantitative explanation of the mean-square displacement (MSD), the non-Gaussian parameter (NGP), and the displacement distribution of complex fluids. In our approach, the environment-coupled diffusion kernel and its time correlation function (TCF) are the essential quantities that determine transport dynamics and characterize mobility fluctuation of complex fluids; their time profiles are directly extractable from a model-free analysis of the MSD and NGP or, with greater computational expense, from the two-point and four-point velocity autocorrelation functions. We construct a general, explicit model of the diffusion kernel, comprising one unbound-mode and multiple bound-mode components, which provides an excellent approximate description of transport dynamics of various complex fluidic systems such as supercooled water, colloidal beads diffusing on lipid tubes, and dense hard disk fluid. We also introduce the concepts of intrinsic disorder and extrinsic disorder that have distinct effects on transport dynamics and different dependencies on temperature and density. This work presents an unexplored direction for quantitative understanding of transport and transport-coupled processes in complex disordered media.
The lifetime and diffusion distance of singlet oxygen in air at 23 °C under 1 atm are 2.80 seconds and 0.992 cm, far longer than previously reported.
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