Harrick Mayank Vin

Streamlining Service Levels for IT Infrastructure Support

For IT Infrastructure Support (ITIS), it is crucial to identify opportunities for reducing service costs and improving service quality. We focus on streamlining service levels i.e., finding right resolution level for each ticket, to reduce time, efforts and cost for ticket handling, without affecting workloads and user satisfaction. We formalize this problem and present two statistics-based search algorithms for identifying problems suitable for left-shift (from expensive, expertise intensive L2 level to cheaper, simpler L1 level) and right-shift (from L1 to L2). The approach is domain-driven: it produces directly usable and often novel results, without any trial-and error experimentation, along with detailed justifications and predicted impacts. This helps in acceptance among end-users and more active use of the results. We discuss one real-life case-study of results produced by the algorithms.

Towards automating the security compliance value chain

Information security is of paramount importance in this digital era. While businesses strive to adopt industry-accepted system-hardening standards such as benchmarks recommended by the Center for Internet Security (CIS) to combat threats, they are confronted with an additional challenge of ever-evolving regulations that address security concerns. These create additional requirements, which must be incorporated into software systems. In this paper, we present a generic approach towards automating different activities of the Security Compliance Value Chain (SCVC) in organizations. We discuss the approach in the context of the Payment Card Industry Data Security Standard (PCI-DSS) regulations. Specifically, we present automation of (1) interpretation of PCI-DSS regulations to infer system requirements, (2) traceability of the inferred system requirements to CIS security controls (3) implementation of appropriate security controls, and finally, (4) verification and reporting of compliance.

Conquering complexity in information systems

The complexity of large-scale “information plants” – consisting of a number of hardware and software components – has been increasing rapidly and is fast approaching a barrier. I argue that continuous “evolution” is a key contributor to this complexity. Information plants evolve to accommodate new software functionalities, hardware technology, application and user requirements, as well as changes in operating conditions (workload, faults, etc.). Today, evolving information plants in a timely manner while maintaining desired levels of performance, stability, and security is an art; system evolution tasks are manual and intuition-based. In this talk, I will illustrate, through examples, the complexity resulting from evolution in modern information systems, and advocate a broad research agenda in computing to conquer this complexity through managed evolution.