A Field Guide to Hidden Accounting Information Detection
ABSTRACT A covert system is in objective to hide critical information. If a company has a covert system, it may have had illegible information. Who has it? Why? Most companies want to make good progress of debt finance, inducement of investment and to get a good company image. If the company doesn 't get a good condition on its finance and management, it commits some frauds. The company manipulates financial statements in order to get good assessment results about the state of its finance and management from investors and manages actual data in a covert system. When the company's fraud comes out and the investigation launches, the management may want to secrete his covert system. On the step of data acquisition, the covert system detection influences on the investigation results. If the investigator couldn 't detect the covert system and the fraud company having a covert system may not say about it, the data on the covert system may not come to the front. It is difficult for the investigator to find out the covert system on the physical place or the network. So it is required a field guide to detection of a covert system with meeting the situation of the investigation field. This paper introduces the field investigation guide for detecting the covert system having accounting information and the detection skill according to the types of the covert system.
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ABSTRACT: Computer crimes are on the rise and unfortunately less than two percent of the reported cases result in conviction. The process (methodology and approach) one adopts in conducting a digital forensics investigation is immensely crucial to the outcome of such an investigation. Overlooking one step or interchanging any of the steps may lead to incom-plete or inconclusive results hence wrong interpretations and conclusions. A computer crime culprit may walk Scot-free or an innocent suspect may suffer negative consequences (both monetary and otherwise) simply on account of a forensics investigation that was inadequate or improperly conducted. In this paper, we present a brief overview of forensic models and propose a new model based on the Integrated Digital Investigation Model.
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ABSTRACT: In this paper, a process model for digital investigations is defined using the theories and techniques from the physical investigation world. While digital investigations have recently become more common, physical investigations have existed for thousands of years and the experience from them can be applied to the digital world. This paper introduces the notion of a digital crime scene with its own witnesses, evidence, and events that can be investigated using the same model as a physical crime scene. The proposed model integrates the physical crime scene investigation with the digital crime scene investigation to identify a person who is responsible for the digital activity. The proposed model applies to both law enforcement and corporate investigations.
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ABSTRACT: Investigative profiling is an important activity in computer forensics that can narrow the search for one or more computer perpetrators. Data mining is a technique that has produced good results in providing insight into large volumes of data. This paper describes how the association rule data mining technique may be employed to generate profiles from log data and the methodology used for the interpretation of the resulting rule sets. The process relies on background knowledge in the form of concept hierarchies and beliefs, commonly available from, or attainable by, the computer forensic investigative team. Results obtained with the profiling system has identified irregularities in computer logs.Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on; 02/2002