Shriti Priya

Phani Krishna Uppala, Abhishek Bamotra, Shriti Priya et al.

The recent success of the CLIP model has shown its potential to be applied to a wide range of vision and language tasks. However this only establishes embedding space relationship of language to images, not to the video domain. In this paper, we propose a novel approach to map video embedding space to natural langugage. We propose a two-stage approach that first extracts visual features from each frame of a video using a pre-trained CNN, and then uses the CLIP model to encode the visual features for the video domain, along with the corresponding text descriptions. We evaluate our method on two benchmark datasets, UCF101 and HMDB51, and achieve state-of-the-art performance on both tasks.

Shriti Priya, Julian James Stephen, Arjun Natarajan

Enterprises and organizations today increasingly deploy in-house, cloud based applications and APIs for internal operations or external customers. These deployments deal with increasing number of threats, despite security features offered by cloud service providers. This work focus on threats that exploit application layer vulnerabilities of cloud workloads. Prevention and mitigation measures against such threats need to be cognizant of application semantics, posing a hurdle to existing solutions. In this work, we design and implement a security framework that allow cloud workload administrators to easily define and enforce policies capable of preventing (i) unrestricted resource consumption, (ii) unrestricted access to sensitive business flows, and (iii) broken authentication. Our framework, Paladin, leverages large language models to extract sufficient semantic meaning from API requests to provide cloud administrators with an application agnostic policy definition interface. Once defined, requests are automatically matched with relevant policies and enforced by high performance proxies. Evaluations with our prototype show that such a framework has broad applicability across applications, good policy identification accuracy, and reasonable overheads, making it substantially easier to define and enforce cross application policies.