Cyber Forensics Intelligence Center
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11875/2423
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Browsing Cyber Forensics Intelligence Center by Author "Bing, Zhou"
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Item A Logic Approach to Granular computing(International Journal of Cognitive Informatics and Natural Intelligence, 2008-04) Bing, Zhou; Yiyu, YaoGranular computing is an emerging field of study that attempts to formalize and explore methods and heuristics of human problem solving with multiple levels of granularity and abstraction. A fundamental issue of granular computing is the representation and utilization of granular structures. The main objective of this article is to examine a logic approach to address this issue. Following the classical interpretation of a concept as a pair of intension and extension, we interpret a granule as a pair of a set of objects and a logic formula describing the granule. The building blocks of granular structures are basic granules representing an elementary concept or a piece of knowledge. They are treated as atomic formulas of a logic language. Different types of granular structures can be constructed by using logic connectives. Within this logic framework, we show that rough set analysis (RSA) and formal concept analysis (FCA) can be interpreted uniformly. The two theories use multilevel granular structures but differ in their choices of definable granules and granular structures.Item Android System Partition to Traffic Data?(International Journal of Knowledge Engineering, 2017-12) Bing, Zhou; Liu, Qingzhong; Byrd, BrittanyThe familiarity and prevalence of mobile devices inflates their use as instruments of crime. Law enforcement personnel and mobile forensics investigators, are constantly battling to gain the upper-hand at developing a standardized system able to comprehensively identify and resolve the vulnerabilities present within the mobile device platform. The Android mobile platform can be perceived as an antagonist to this objective, as its open nature provides attackers direct insight into the internalization and security features of the most popular platform presently in the consumer market. This paper identifies and demonstrates the system partition in an Android smartphone as a viable attack vector for covert data trafficking. An implementation strategy (comprised of four experimental phases) is developed to exploit the internal memory of a non-activated rooted Android HTC Desire 510 4g smartphone. A set of mobile forensics tools: AccessData Mobile Phone Examiner Plus (MPE+ v5.5.6), Oxygen Forensic Suite 2015 Standard, and Google Android Debug Bridge adb were used for the extraction and analysis process. The data analysis found the proposed approach to be a persistent and minimally detectable method to exchange dataItem In Search of Effective Granulization with DTRS for Ternary Classification(International Journal of Cognitive Informatics and Natural Intelligence, 2011) Bing, Zhou; Yiyu, YaoDecision-Theoretic Rough Set (DTRS) model provides a three-way decision approach to classification problems, which allows a classifier to make a deferment decision on suspicious examples, rather than being forced to make an immediate determination. The deferred cases must be reexamined by collecting further information. Although the formulation of DTRS is intuitively appealing, a fundamental question that remains is how to determine the class of the deferment examples. In this paper, the authors introduce an adaptive learning method that automatically deals with the deferred examples by searching for effective granulization. A decision tree is constructed for classification. At each level, the authors sequentially choose the attributes that provide the most effective granulization. A subtree is added recursively if the conditional probability lies in between of the two given thresholds. A branch reaches its leaf node when the conditional probability is above or equal to the first threshold, or is below or equal to the second threshold, or the granule meets certain conditions. This learning process is illustrated by an example.