Disruptive impact of emerging technologies on cyber security, IT News, ET CIO | #cybersecurity | #cyberattack

By Manish Jain

Banking and telecom industries are racing to adopt technologies to keep up with the influx of digital disruption caused by– artificial intelligence (AI), extended reality (XR), machine learning (ML), and the internet of things (IoT). However, growing legacy systems, trends in advancement, and demand for multi-channel customer-centric solutions are posing their own set of cyber challenges.

The cyber security market is projected to reach a marker valuation of around $245 billion by 2023 globally, as highlighted in – Analytics Insight Report, March 17, 2019.

Growing cyber security risks

Cyber security involves protecting an organization or individual’s data from malicious attacks, unauthorized access, identity/ monetary theft or damage to data. Transactional services in banking and telecom depend on processing information that requires verification and coding. Many of these services are powered by flawed protocols such as SS7 (Signaling System No. 7) or Diameter.
While hackers have used the SS7 protocol to intercept 2FA authentication codes and drain user accounts, newer protocols such as SIP (Session Initiation Protocol) are also vulnerable to cyber threats. Attackers have managed to stage denial of service (DoS) attacks by taking advantage of malformed SIP traffic.

Additionally, DNS (Domain Name Security) attacks have proved costly for telcos. As per the Global DNS Threat Report, around 79% of the organizations faced DNS attacks in 2020. On average, the cost of a security incident was $924,000. Telcos are also the prime target for DDoS (Distributed Denial of Service) attacks where attackers aim to exceed a website’s capacity by sending multiple requests to prevent it from functioning properly. DDoS incidents are significant as they have a ripple effect on the telecom sector. In 2021, Gartner estimated 25 billion IoT devices to be connected to telecom networks. And so, the key security challenges for telcos today are managing data of this volume, preventing unauthorized access, securing data transmissions, and ensuring smooth monitoring of a much larger attack surface.

Adoption of AI/ML strategies to detect cyber threats

Telcos are heavily investing to ensure AI is embedded in their security surface for enriched outcomes. Leveraging ML and Big Data with supervised AI algorithms have helped identify irregular patterns that help in threat detection. The more structured the data, the easier it is to stream process it with programming languages like Python. Furthermore, automating processes to respond to security alerts enables the system to trigger predictable remediation.

Further, the use of SIEM (Security, Information and Event Management) platforms helps forward alerts to automate procedures. Subsequently, this helps reduce the number of instances. In addition to counteracting cyber threats, AI/ML has also been adopted by telcos to increase revenue streams through improved real-time customer management campaigns and new intelligence-driven digital engagements.

All this is made possible by collecting real-time Big Data using AI and ML to create greater visibility into service characteristics, build targeted loyalty programs and deliver more personalized services.

Serverless clouds and containers for cyber security

The use of cloud services to deliver solutions, software, infrastructure, and data via the internet has helped companies scale at an accelerated pace. Serverless cloud technology such as AWS or Google Cloud and open-source containers such as Kubernetes have helped revolutionize the creation and deployment of complex API (Application Programming Interface). This has enabled seamless customer experience across multi-channel solutions. Furthermore, languages like Python or NodeJS have helped accelerate the creation of customized APIs that can be linked to messaging or queuing systems from SIEM platforms.

Continuous integration/continuous delivery (CI/CD) workflows are vital to these container-based systems. Embedded AI in APIs, SIEM platforms to manage security incidents, and log monitoring solutions are key for threat detection and mitigation. That said, the use of cloud-native APIs has also transformed the way customers save, borrow, transfer and spend money.

Moreover, introduction of digital lending through telcos has empowered consumers across unbanked segments to perform cashless payments through reliable cloud-native platforms built using micro-services. The use of open APIs has enabled rapid service expansions for developers and third-party service providers.

Zero-Trust Security framework to prevent cyber threats

Zero-Trust Security framework focuses on protecting enterprise data by improving identity management and device security. According to Forrester’s original Zero Trust concept, Zero Trust eXtended (ZTX) is a conceptual and architectural framework for moving security from a network-oriented, perimeter-based security model to one based on continuous verification of trust.
In this framework, executives create a detailed roadmap outlining the main workstreams and projects necessary for their ZTX strategy. This helps them plot their maturity to identify Zero Trust starting point – people, workloads, device, networks, size of the investment, business and security outcomes, as well as plan of delivery4.


Undoubtedly, digital disruptions via AI, XR, ML and IoT have led to an increase in the cyber security market size. These trends can be leveraged to detect and mitigate cyber threats, and if innovatively used can create new revenue streams. The first step in cyber security requires adopting a Zero-Trust security framework and the next to invest in cloud native platforms to expand revenue streams.

The author is Chief Technology Officer at Comviva

Original Source link

Leave a Reply

Your email address will not be published. Required fields are marked *

− one = 9