LV Manufacturing Company, one of India's leading automotive component manufacturers, had embarked on an ambitious digital transformation program by late 2024. They moved from legacy systems to SAP ERP tightly integrated

CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · PYQS · June 2026
LV Manufacturing Company, one of India's leading automotive component manufacturers, had embarked on an ambitious digital transformation program by late 2024. They moved from legacy systems to SAP ERP tightly integrated with Oracle Database 19c, deployed AWS S3 for backups, and adopted a Hyperledger-based blockchain to track raw material sourcing and shipment verification. LV Manufacturing Company also rolled out IoT-based factory sensors connected through a 5G private network to feed real-time production data into their Decision Support System (DSS). One of LV's largest trading partners was Mr. RK, a high-profile Mumbai-based stockbroker and commodities trader. Mr. RK was specialized in predictive investment strategies for manufacturing and logistics sectors, relying heavily on real-time operational data feeds from suppliers like LV. LV Manufacturing Company granted Mr. RK, API-based access to certain DSS metrics, secured through their corporate firewall and an API gateway. In early 2025, LV Manufacturing Company entered a large export contract with European automotive clients that required blockchain-verified shipping updates. Mr. RK's analytics platform consumed this blockchain data along with ERP metrics to predict LV's share performance. Mr. RK's analytics models flagged abrupt drops in LV's production output and delayed shipment logs. Blockchain ledger entries mismatched ERP shipment records. Firewall logs showed traffic spikes from unrecognized IP ranges—many geolocated outside India. Within days, Mr. RK's AWS-based data lake suffered corruption of historical performance datasets, causing predictive models to produce flawed investment signals. Forensics hinted at API credential compromise, likely through phishing of a LV admin user, coupled with firewall misconfiguration allowing API traffic from unvetted IP addresses. On Mr. RK's side, object versioning was disabled in S3, allowing corrupted data to overwrite originals without rollback. Investigators determined: Compromised API tokens were used to pull legitimate LV's data and inject falsified metrics. Attackers modified Oracle DB query responses in-transit before they hit the blockchain validation layer. Mr. RK's network security appliance was only in monitoring mode, so malicious packets were not blocked in real time. The attack impacted not only LV's credibility but also Mr. RK's financial standing, as some investments were made on the basis of tampered analytics. International clients demanded an independent blockchain audit, while both LV Manufacturing Company and Mr. RK had to halt operations temporarily for data restoration. Based on the above case answer the following: How IaaS storage can be beneficial for LV Manufacturing Company? What are main drawbacks of using these services?

Answer & Explanation:

Infrastructure as a Service (IaaS) enables end users to increase and reduce resources as needed, lowering the need for expensive, upfront capital expenditures or needless "owned" infrastructure. IaaS offers the most fundamental level of control over cloud resources in contrast to Platform as a Service (PaaS) and Software as a Service (SaaS) (even more modern computing paradigms like containers and serverless). Companies can use storage services to store data on the storage equipment of third-party providers. Customers can access cloud storage online, which is displayed to them as a collection of storage pools or buckets, utilizing sophisticated interfaces like command-line tools, web interfaces, or programming Application Programming Interface (API). Clients are unaware of the intricacy of the cloud storage architecture, although it is very sophisticated on the back end and often consists of distributed storage devices that are controlled by centralized software. Algorithms are used by sophisticated storage management software to manage data scattered across numerous distributed devices. Network slowness, reliance on internet accessibility, security issues, and restricted control are all potential drawbacks. Due to the cloud provider's data center's distinct geographic location, network latency is greater than with internal storage. If a customer doesn't have a local copy of their data and instead saves it all in a public cloud, they are entirely dependent on internet connectivity. To prevent information loss or compromise, a cloud provider should provide high-level security, and data transit must be encrypted.

Topics: Cloud Computing

Open in Interactive Practice Hub · Full Practice Hub · Chapter Weightage · More in this subject

Related Questions in this Topic