AI for IT Services Firms Backup Recovery And CybersecurityFebruary 17, 2019
The coming of the Age of Artificial Intelligence is an apt way to describe how IT services like cyber-security, recovery of data and backup of data has been impacted by AI developments globally. Any event on cybersecurity throws up newer requirements in cyber-security and a bouquet of innovative solutions using artificial intelligence, cloud storage, and data recovery tools.
Virus detection is a challenge-area that about 29 percent of surveyed professionals look to AI for as per ESG research. Besides speedy discovery, 27 percent of the surveyed professionals in the security field look to AI to hasten the response time of reported incidents.AI is being touted as today’s technological marvel that can analyze huge volumes of code in very short time periods. This is rightly true and the mind-boggling speeds and analysis of data have made AI all pervasive and the panacea to almost all ills in the IT sector.
AI Vs ML:
The terms AI and ML are being used oft interchangeably. In reality, both are useful tools that differ in their thinking abilities. ML uses algorithms to detect breaches in security which restricts their use to think outside the set framework. On the other hand, AI does not need algorithms or any further data when it comes to terms with any issue. It arrives at an unassisted intelligent conclusion.Both AI and ML techniques are the focus areas of dealing with advances in cyber threats. These techniques when applied can transform the scenario from defence to early detection and quick response to cyber infections.
Areas, where ML makes a huge difference, are
- In scouring huge data volumes across thousands on nodes looking for potential threats.
- In firewall applications, gateways, and APIs where traffic patterns need to be analyzed.
- In classifying data objects and governance of data
- In access-control and authorization systems and practices using auto-generate policies, and analysis of the regulatory measure, rules etc
- In detecting anomalies and setting baselines for user behavioural analysis and SIEM events of cybersecurity.
Hacker’s too can use ML and AI:
Alongside the new developments in AI, cyber-security, and ML there is a the all real possibility of hackers also using the same infection-detection technology and malware samples to advance the technology of cyber-threats. It is reasonable to predict that the very same techniques are used by hackers to create modified code-samples depending on the way AI detects infections. This then leads to a situation where the infections last longer and since the code is smaller it becomes near undetectable.
Storage challenges and Cybersecurity:
The feasible option for safe storage of data today is by backing data to a reliable disaster recovery cloud which enables rapid recovery of files while ensuring the data stays protected, safe and encrypted. The market has many technological options like Avast, CA Technologies secure, Keeper, etc that can help keep data copies out of reach by hackers and yet available on an easy-to-use platform.
In conclusion, the use of ML and AI can help resolve issues and challenges faced in cybersecurity, data recovery, and storage. The evolution of threats and detection techniques continue in tandem in a seemingly unending fashion where users and hackers are both looking to AL and ML for solutions.