AI can detect potential threats, even when it comes to a large portion of data
This is an exclusive interview conducted by the Editor Team of CIO News with Kavitha Srinivasulu, Global Head – Cyber Risk & Data Privacy – R&C BFSI at Tata Consultancy Services
About Kavitha Srinivasulu:
Kavitha Srinivasulu has around 20 years of experience focused on cybersecurity, data privacy, and business resilience across BFSI, financial services, retail, manufacturing, health care, IT services, and telecommunications domains. She has demonstrated her core expertise in risk advisory, business consulting, and delivery assurance with diverse experience across corporate and strategic partners. She is a natural leader with the versatility to negotiate and influence at all levels.
Historically, starting off with information security and changing to cybersecurity with lots of controls addressing the needs and demands of the changing environment has been a field governed by resource-intensive efforts. Analyzing, assessing, monitoring, responding, and recovering are all manual processes that take time and result in delayed detection, response, and remediation activities, increasing the exposure of threats and amplifying vulnerabilities to cyber predators. The global cybersecurity threat landscape is evolving, and end-users have faced huge threats to their data and privacy in the recent past.
Cybersecurity is one of the major concerns across industries, and cyberattacks have become a regular routine affecting individuals, businesses, organizations, and government bodies across the globe. Organizations must deal with emerging security and privacy threats to their assets, including hardware, software, data, and infrastructure, to overcome the challenges arising in the technology space.
Over the past few years, artificial intelligence (AI) in cybersecurity has evolved as an AI-driven security solution that has been used to deploy at various levels to ensure data security and detect potential security threats proactively to reduce business impact. They have rapidly matured to the point where they can bring substantial benefits to cyber security operations across a broad range of organisations and government bodies. AI can transform cyber workflows into streamlined, autonomous, continuous processes that speed up remediation and maximise protection.
To protect businesses from disruptions, the need for artificial intelligence (AI) in the technology space has grown significantly and is becoming a part of everyday life in some form or another. It has various features and functionalities, including predictive analytics, chatbots, digital identity, application security, network security, and data security. AI relies primarily on creative innovations like machine learning, deep learning, natural language processing, and so forth to make it difficult for programmers to access servers and other important data available inside the systems and network.
The benefits of AI implementation in cybersecurity help in:
The use of AI to prevent threats and vulnerabilities will be one of the key focus areas to utilise in the years ahead. It reduces incident response time, minimises risks, and prevents potential data breaches in times where security is a main concern to protect the business. AI can assist organisations in detecting cyber threats ahead of time by implementing proactive approaches based on AI algorithms, which reduces potential harm and strengthens data security.
Applying AI to increase Cybersecurity:
- AI self-learning capabilities
AI is intelligent enough to keep learning by itself, and this can help in developing robust applications and network security over time. AI uses machine learning and deep learning to recognise patterns on the network and cluster them to detect deviations or unusual behaviours before responding to them. This AI platform can help in early detection and response to reduce downtime and avoid potential damage.
- Identifying Unknown Threats
Some of the threats are too complex for humans to detect and report. Hackers can launch multiple attacks with various purposes and intentions. Some of the unidentified threats can cause massive damage to the network, resulting in potential damage. However, AI is more effective in mapping and blocking unknown threats within a fraction of a second, which helps reduce the impact on an organization.
- Securing Authentication:
Managing access controls is one of the most challenging areas, as most cyberattacks or cybercrimes arise from unauthenticated access and credential exploitation. As an organization, you need an extra security layer of protection to protect the environment, as it involves personal data and sensitive information. However, AI secures authentication using various tools such as facial recognition, CAPTCHA, and fingerprint scanners, amongst others, for identification.
4. AI Data Management:
AI can detect potential threats, even when it comes to a large portion of data. In an organization, there is a lot of data managed, both internal and external, which is highly susceptible to security threats in the current threat landscape. This data needs a highly protected environment to safeguard the data from malicious codes or malware. AI has a huge capability to detect any threats hidden in high traffic zones or paths, develop proactive approaches, and protect the data.
- Vulnerability Management
Vulnerability management is key to securing an organization’s network. High levels of scanning and testing capabilities are needed to detect, identify, and prevent vulnerabilities in the existing threat landscape. Analyzing and assessing existing applications to reduce vulnerabilities is critical, and AI research can aid in vulnerability management by utilising highly promising AI algorithms and tools to overcome challenges.
AI can be used to strengthen data security controls in the following areas of cybersecurity:
AI has proven itself and shown results in assisting organisations in identifying threats, intrusions, and any malicious activities using machine learning and AI algorithms. The use of AI algorithms is being used to automate investigations and identify indicators of attacks. It’s also being used for the real-time detection of deviations and changes in behaviours that will help organisations respond faster and in a more intelligent way.
AI can assist with user behavioural analytics to prevent unforeseen risks and online fraud. AI has many capabilities, including learning and identifying users’ behaviors, understanding patterns in their usage over time and across platforms, and effectively alerting them to unusual behavior. Login times, IP addresses, typing and scrolling patterns, and login timings are all examples of this behavior. AI-powered tools continuously monitor and alert system users to anomalies in data or behaviors, reducing the possibility of potential damage.
Organizations can use AI to mitigate the risk of social engineering and phishing attacks through timely detection and response. By using AI-driven security techniques, organisations can establish automated and efficient ways to respond to emerging attacks before they influence the network and create potential damage to the system or asset. AI algorithms are programmed to process a large amount of data in seconds, which is not possible for humans, which helps with timely responses and the reduction of business impact. AI tools are also widely used in anomaly detection to capture the unusual behaviours in the system. Real-time detection and automated processes help organisations respond with efficiency, speed, and business recovery.
One of the biggest advantages of using AI in cybersecurity is the possibility of notifying users before they access suspicious websites and fall prey to phishing attacks. As the adoption of AI in cybersecurity increases, organisations need to monitor and manage the impact of AI in their business environments. Organizations need to prioritise strengthening security controls and adhere to regulatory requirements to help AI identify risks faster and better than other resources.
AI is an emerging technology that will continue to grow across various sectors. Without AI, the future of cybersecurity is unimaginable, especially when we consider the scale, predictive analytics, behavioural analytics, avoiding unforeseen risks, and reducing social engineering threats in today’s threat landscape. As AI grows more prevalent, it will be easier to enhance human capability and minimise human errors.
Note: The views and opinions expressed by Kavitha in this article are solely her own and do not represent the views of her company or her customers.
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