Sliding Window Measurement for File Type Identification

نویسندگان

  • Gregory A. Hall
  • Wilbon P. Davis
چکیده

Knowing the file type associated with a sequence of bytes makes interpretation of those bytes far more meaningful. With the ever increasing number of file types in existence and the massive storage capacity of modern hardware, it is impractical to try interpreting a sequence of bytes as every known file type until one succeeds. Furthermore, some file types require specific header or footer information that, if missing, makes the data unusable. This paper presents new measurements that can be used to assist in determining the file type associated with a file of unknown type. These measurements can be used by a variety of algorithms to attempt to determine file type. Initial results are presented and avenues for future research are discussed.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

FDiBC: A Novel Fraud Detection Method in Bank Club based on Sliding Time and Scores Window

One of the recent strategies for increasing the customer’s loyalty in banking industry is the use of customers’ club system. In this system, customers receive scores on the basis of financial and club activities they are performing, and due to the achieved points, they get credits from the bank. In addition, by the advent of new technologies, fraud is growing in banking domain as well. Therefor...

متن کامل

Identification Applied to Dual Sensor Transient Temperature Measurement ⋆

The harsh environment presented by engines, particularly in exhaust systems, necessitates the use of robust and therefore low bandwidth temperature sensors. Consequently, high frequencies are attenuated in the sensor output. A number of techniques for addressing this problem involve measurement of the gas temperature using two thermocouples with different time-constants and mathematical reconst...

متن کامل

Design of the Nonlinear System Predictor Driven by the Bayesian-Gaussian Neural Network of Sliding Window Data

The model identification of the nonlinear system has been concerned by the industrial community all along. The relationship of the nonlinear dynamic system is contained in the data accumulated in the scene. To better utilize the data about the industrial objects, in this article, we put forward the nonlinear system predictor driven by the Bayesian-Gaussian neural network (NN) model, use the tra...

متن کامل

Adaptive Segmentation with Optimal Window Length Scheme using Fractal Dimension and Wavelet Transform

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...

متن کامل

Mining Frequent Patterns in Uncertain and Relational Data Streams using the Landmark Windows

Todays, in many modern applications, we search for frequent and repeating patterns in the analyzed data sets. In this search, we look for patterns that frequently appear in data set and mark them as frequent patterns to enable users to make decisions based on these discoveries. Most algorithms presented in the context of data stream mining and frequent pattern detection, work either on uncertai...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007