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Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
Fuzzing Project, includes tutorials, a list of security-critical open-source projects, and other resources. University of Wisconsin Fuzz Testing (the original fuzz project) Source of papers and fuzz software. Designing Inputs That Make Software Fail, conference video including fuzzy testing; Building 'Protocol Aware' Fuzzing Frameworks
It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, PricewaterhouseCoopers reported that fraud has impacted 46% of all businesses in the world. [1] The shift from working in person to working from home has brought increased access to data.
Fraud deterrence is based on the premise that fraud is not a random occurrence; fraud occurs where the conditions are right for it to occur. Fraud deterrence attacks the root causes and enablers of fraud; this analysis could reveal potential fraud opportunities in the process, but is performed on the premise that improving organizational procedures to reduce or eliminate the causal factors of ...
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In hacking, a shellcode is a small piece of code used as the payload in the exploitation of a software vulnerability.It is called "shellcode" because it typically starts a command shell from which the attacker can control the compromised machine, but any piece of code that performs a similar task can be called shellcode.
Used as part of computer security, IDMEF (Intrusion Detection Message Exchange Format) is a data format used to exchange information between software enabling intrusion detection, intrusion prevention, security information collection and management systems that may need to interact with them. IDMEF messages are designed to be processed ...
Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.