I am a Manager of Data Security Services at a large bank.
I am looking for a capability comparison between Broadcom Symantec DLP, Proofpoint DLP, and Microsoft Purview DLP. Any comparison reports provided between these products are appreciated.
Thank you for your help.
Network Security Services at ACE Managed Securty Services
Mar 23, 2023
Data loss prevention (DLP) is an important security technology that can help organizations protect their data from unauthorized access, misuse, and data loss. DLP solutions are designed to detect data breaches and alert companies about the possible security risks associated with data storage. They can be used to block data transfers or restrict access to data stored in cloud-based data stores. In addition, DLP solutions can be used to monitor data usage and detect malicious behavior such as data theft or data leakage. By implementing data loss prevention technology, companies can protect their data from external threats and unauthorized access.
When it comes to Email Cloud Security, Symantec DLP, Proofpoint DLP, and Microsoft Purview DLP are all strong contenders. But which solution is the right one for you? Well, that depends on your specific needs. If you prioritize ease of use and scalability in your Email Cloud Security solutions, then Symantec DLP is the right choice. If, on the other hand, you value data privacy and protection then Proofpoint DLP is a better option. Finally, Microsoft Purview DLP stands out for its comprehensive analytics tools that give users greater insight into their Email Cloud Security performance. So which Email Cloud Security solution do you pick? Choose wisely! It could make all the difference.
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Hi @Evgeny Belenky ,
Cognitive security can be interpreted as the application of AI technologies patterned on human thought processes to detect threats and protect physical and digital systems.
Like other cognitive computing applications, self-learning security systems use data mining, pattern recognition and natural language processing to simulate the human brain, albeit in a high-powered computer model. Such automated security systems that are designed to solve problems without requiring human resources.
Machine learning algorithms make it possible for cognitive systems to constantly mine data for significant information and acquire knowledge through advanced analytics. By continually refining methods and processes, the systems learn to anticipate threats and generate proactive solutions. The ability to process and analyze huge volumes of structured and unstructured data means that cognitive security systems can identify connections among data points and trends that would be impossible for a human to detect.
Cognitive security may be particularly helpful as a way to prevent cyberattacks that manipulate human perception. Such attacks, sometimes referred to as cognitive hacking, are designed to affect people's behaviors in a way that serves the attacker's purpose. Cognitive security efforts in this area include non-technical approaches to making individuals less vulnerable to manipulation as well as technical solutions designed to detect misleading data and disinformation and prevent its dissemination.
Cognitive Cybersecurity is a term used to describe the process of protecting computer systems from unauthorized access, use, disclosure, disruption, modification, or destruction. It involves protecting the systems from both external and internal threats. External threats can include malicious actors such as hackers or thieves, while internal threats can include negligent employees or malicious insiders.
Cognitive Cybersecurity is also known as Behavioral Security or Human Factors Security. It refers to the study of human behavior in relation to cybersecurity. This includes things such as how people interact with devices and software, how they respond to security warnings or alerts, and how they manage passwords and other security credentials. By understanding human behavior, organizations can design systems that are more secure and less likely to be