Artificial Intelligence and Machine learning

Artificial intelligence and machine learning technology push for more sophisticated threat detection and monitoring of human behavior. Artificial intelligence and big data has played major roles on futuristic robots, games technology, and recreation development. Big data and artificial intelligence have also played major roles in search and utilization of information in that it promises faster answers, improved outcomes and better productivity (Thomas 1). Machine learning, artificial intelligence, big data, digital twins, intelligent apps and conversational systems are emerging with a huge disruption across the technology, information and communication and many other industries despite the fact that these industries have ad advancements with artificial intelligence algorithms in healthcare, cognitive science and predictive analysis.

Many developments in artificial intelligence have been employed in any fields such as the cyber security space with the advent of sophisticated malware, ransom ware and many others. Many companies in the technology industry including Google, Microsoft, Cisco and Symantec are investing heavily in artificial intelligence and cyber security and major antivirus companies. The last few years have seen an increase in startups that deal with security tools with the advent of machine learning and artificial intelligence including AlienVault, Darktrace and Cylance.

Importance of robust securities

Companies invest a lot of monies in robust, multi-layered security strategy to protect their networks. The organizations are pursing escalated Artificial Intelligence defenses to combat cyber criminals and others on the offensive that are also becoming advanced in Artificial Intelligence and security. In light of these, companies have to invest in end-user training, social engineering training, knowledgeable technical staff, AI/machine learning and solid products to detect and combat cyber attacks such as strengthening the traditional intrusion prevention system and firewall with advanced endpoint monitoring system that uses machine learning in the identification and prevention of bad codes from executing and a tool that provides a real-time holistic view of the entire network to identify advanced threats such as silent, unconventional and stealthy hackers (Thomas 3). In this regard, companies have to give regular and updated end-user security training with the change in trends in phishing and social engineering.

Healthcare realm risks

There is a gamut of cyber security risks apart from the financial ones that are very devastating to organizations. Cyber attackers in the healthcare industry in the recent years struck various health centers in virtual sneak attacks. This strategy is gradually changing as cyber attackers are taking a more slow and methodical approach to steal and later data without being detected. These attacks might have long term devastating consequences and to healthcare organizations and companies as they try to isolate real information from fake ones out of the altered data. Altered health information has life-altering effects that result in critical misdiagnoses that can in turn affect lives and health of patients. This implies that healthcare organizations, just like financial ones, have to put cyber security measures and artificial intelligence installations in place to protect their clientele. In this regard, a lot of security technology companies are embracing technologically advanced ways of important data protection based on advanced algorithm and artificial intelligence able to adapt and learn life patterns for every user and device in the network and single out anomalies.

Advances in threat detection

The main focus of machine learning and artificial intelligence today is threat detection, monitoring f human behavior and detecting anomalies so that it raises an alarm. Bid data comes handy with artificial intelligence to collect, monitor and analyze increasing data volumes to tame hackers and malicious actors such as spying governments and disgruntled customers. Big data, machine learning and artificial intelligence are playing a crucial role in handling large data streams and decreasing threat levels through advanced analytics and sophisticated technology on the internet, company networks and connected machines (Thomas 4). There is an ongoing battle of wills against cyber criminals with Artificial intelligence playing a crucial role in who wins the battle.

Works Cited

Thomas, Brian E (2017). Why AI is crucial to cyber security. CIO. Retrieved from https://www.cio.com/article/3201147/why-ai-is-crucial-to-cyber-security.html