I work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First. ...Full Bio
I work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First.
Success story of Haptik
851 days ago
Who is afraid of automation?
851 days ago
What's happening in AI, Blockchain & IoT
852 days ago
3 million at risk from the rise of robots
852 days ago
5 ways Machine Learning can save your company from a security breach
A recent release from Centrify and Dow Jones Customer Intelligence study titled ' CEO Disconnect is Weakening Cybersecurity' revealed certain interesting factors related to security breach of companies.The study cited that despite advancement in cyber security technology,breach in security of more than two thirds of companies occurred in the year 2017.However a little over 50 percent of CEOs actually accepted that their company experienced a security breach and nearly one fourth of them were unaware of the breach in their security.Good majority of CEOs inaccurately blamed the malware as the main cyber security threat.
The study further highlights how the CEOs can reduce the security breach risk by focussing on and improving their strategies of identity and access management.Most CEOs are however sceptical about the process of multi-factor authentication.
How Machine learning can save companies from security breach meltdowns ?
1. Use of behavioral pattern matching and analysis: Machine learning has the advantage of using constraint- based and pattern matching algorithms to analyze behavioral pattern of people who are signing into a system.This can specially be used for identifying the correct user in system that are loaded with sensitive informations.By learning the behavioral pattern of individuals with the right credentials for a system, the ML process can help to stop people with wrong credentials to access the system.
2. Use of risk scoring models according to businesses changing requirements: Machine learning can help to develop Zero Trust Security (ZTS) frameworks and help the CEOs to identify and remove major security related roadblocks affecting the future growth of the company.
3. Streamlining the security access for new employees: Machine learning features are improving so as to enable development of models which can learn the behavioral pattern of the employees on how they access the system and over the time automatically change the level of authentication.This helps to improve the user experience and easier access of secured data by authentic employees.
4. Identify probable sources of threat and their profiles: For minimizing security breaches , the Chief Intelligence Officer of a company should be able to predict possible security threats and also able to prioritize them according to their potential severity.Machine learning algorithms can help to identify and prioritize these threats.
5. Helping to stop Malware- based breaches: The biggest security threats for a company is by the hackers who penetrate the network of a company who use impersonation- based logins and passwords to pass malware into the servers of big corporates.Machine learning can help to implement the ZTS framework to identify, trap and stop malware activity that appears to be of suspicious nature.