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Government CIO Outlook | Thursday, September 02, 2021
In order to render justice, AI can automate the forensic investigation procedure and collaborate with an expert.
FREMONT, CA: Artificial intelligence (AI) is a well-known field that focuses on resolving real-time complexities of the problems that may have arisen. Digital forensics is essentially the processing of data that has been intelligently provided. The use of artificial intelligence (AI) to solve difficulties in digital forensics is considered necessary.
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The critical difficulties in digital forensics are the exponential expansion of storage capacity, the ubiquity of data saved electronically, the prevailing disparate systems, and the degree of technical knowledge to decide the methodology to be worked on. The problems listed above can only be solved if AI is used to produce reasonability and uncover possibly diverse and vast amounts of data in a reasonable amount of time.
KNOWLEDGE REPRESENTATION
When addressing AI, one of the most significant ideas to consider is knowledge representation, which refers to expressing the information that people are interested in. Adding ontology to the row allows to discover the reason for the representation and make it more understandable. The focus is presently on XML and RDF, which can improve data standards, as it is the heart of digital forensics.
Standard domain ontology is the way of the future in digital forensics. Utilizing a standard domain would allow communication on different digital forensic jobs, like hidden information between forensic imaging tools, and establish a formal framework for discussing any digital exhibit. Further, increasing the ability to create a vast, reusable case repository.
RECOGNITION OF PATTERNS
Pattern recognition is used in the detection of data clusters. The recognition system works as a collection of significant classifiers, performing a possible pass-through of all surrounding pattern matches before deeming the most appropriate as successful. Artificial neural networks and decision trees allow early patterns detection, making them useful in digital forensics.
THE REASONING PROCESS
The reasoning of the algorithm used is the next key topic in the AI field of digital forensics. As a result, its value in digital forensics is limited. Symbolic and sub-symbolic characters could be utilized to differentiate the AI approaches used. Symbolic reasoning uses a pre-designed expert system to make the decision-making process more manageable. Even though there is a disadvantage to this pre-designed rule of thumb method, like analysis errors. A lack of a rule foundation may cause the error. The problem could be fixed by repairing the rule base, but this is a time-consuming operation.
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