Every coin has two faces which include a head and a tail. Similarly, technology has its pros and cons. While pros are essential to rule every organization, the cons represent the weaknesses in technology that are hard to overlook. Artificial Intelligence, therefore, is not an exception to those limitations which every technology carries with itself.
Throughout the years, the information security challenge to AI has evolved. Given the reality that AI is being used by businesses for facial recognition and to enhance the operating climate, the challenges and threats remain evident. Computer attackers are becoming even more aggressive in targeting organizations, corporations, and government bodies. Additionally, social networking sites are at the forefront of cyber malware attacks.
In 2019, Israeli Spyware Pegasus issued an awareness of Artificial Intelligence being the major loophole to data security. This exposed the possibility of misusing AI for unethical breach of privacy. Nevertheless, Pegasus is not the only threat that represents AI’s information security vulnerabilities. The possibilities of exposure of government data, the challenge to national security, bias, and exploitation of consumer data are among the challenges to information security imposed by AI.
Organizations also need to be more proactive in recognizing the risks associated with AI in data collection and in determining the appropriate steps to integrate AI with cybersecurity. In October 2019, the World Economic Forum listed cyber threats as one of the ten global dangers which need immediate attention. It is projected that US$ 90 trillion companies will be destroyed in 10 years if the requisite steps are not taken to counter cyber-attacks.
The volume of data generated from various web sites, social networking, apps, sensors, and the Web is immense. Computer ransomware, which is sometimes veneered in the form of anonymous info, is difficult to recognize.
Many authentication snags inside an organization serve as a medium through which data may be discriminated against through zip-code weaving. This is a violation of the privacy of the customer. It is thus important for a company to recognize places that need the greatest potential focus, acknowledge the absence of a risk management program, and seek out a strategy to detect and resolve threats to data security.
That can be done by implementing AI and cybersecurity together, to enable certain security-related decisions to be taken in cyberspace itself. The risks to cyberspace must be classified, defined, and assessed. It specifies the flaws in the cybersecurity system and network that need an urgent strategic response to any emerging cyber threat.
Incorporating an AI-driven security infrastructure to improve current technologies allows the identification of emerging risks within the network. It improves the efficiency and efficacy of information protection activities and identifies irregular operational habits. Furthermore, it strengthens identification and reaction, prioritizes recovery of weaknesses, and highly in stored identification and review methods.
The partnership between AI and cybersecurity is critical and equally important for every company to operate smoothly. It is a strategy that gives visibility about the current activity, to predict and react to the threat. This allows AI to make data-driven decisions. Protocols, processes, and stringent steps are also required to strengthen the interaction between AI and the Data protection process, which strengthens the risk reduction mechanism and helps to develop plans to enhance information protection.