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In computer security, a threat is a potential negative action or event enabled by a vulnerability that results in an unwanted impact to a computer system or application.. A threat can be either a negative "intentional" event (i.e. hacking: an individual cracker or a criminal organization) or an "accidental" negative event (e.g. the possibility of a computer malfunctioning, or the possibility ...
An example of a physical security measure: a metal lock on the back of a personal computer to prevent hardware tampering. Computer security (also cybersecurity, digital security, or information technology (IT) security) is the protection of computer software, systems and networks from threats that can lead to unauthorized information disclosure, theft or damage to hardware, software, or data ...
An intrusion detection system (IDS) is a device or software application that monitors a network or systems for malicious activity or policy violations. [1] Any intrusion activity or violation is typically either reported to an administrator or collected centrally using a security information and event management (SIEM) system.
Internet security awareness or Cyber security awareness refers to how much end-users know about the cyber security threats their networks face, the risks they introduce and mitigating security best practices to guide their behavior. [1] [2] End users are considered the weakest link and the primary vulnerability within a network.
Advanced STIGs might cover the design of a corporate network, covering configurations of routers, databases, firewalls, domain name servers and switches. See also [ edit ]
Web threats pose a broad range of risks, including financial damages, identity theft, loss of confidential information/data, theft of network resources, damaged brand/personal reputation, and erosion of consumer confidence in e-commerce and online banking. It is a type of threat related to information technology
STRIDE is a model of threats, used to help reason and find threats to a system. It is used in conjunction with a model of the target system that can be constructed in parallel. This includes a full breakdown of processes, data stores, data flows, and trust boundaries.
Recent attempts at detecting DGA domain names with deep learning techniques have been extremely successful, with F1 scores of over 99%. [8] These deep learning methods typically utilize LSTM and CNN architectures, [ 9 ] though deep word embeddings have shown great promise for detecting dictionary DGA. [ 10 ]