BITS Faculty Publications
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Item Weak links in Linkedin: enhancing fake profile detection in the age of llms(2025-07) Agarwal, VintiLarge Language Models (LLMs) have made it easier to create realistic fake profiles on platforms like LinkedIn. This poses a significant risk for text-based fake profile detectors. In this study, we evaluate the robustness of existing detectors against LLM-generated profiles. While highly effective in detecting manually created fake profiles (False Accept Rate: 6-7%), the existing detectors fail to identify GPT-generated profiles (False Accept Rate: 42-52%). We propose GPT-assisted adversarial training as a countermeasure, restoring the False Accept Rate to between 1-7% without impacting the False Reject Rates (0.5-2%). Ablation studies revealed that detectors trained on combined numerical and textual embeddings exhibit the highest robustness, followed by those using numerical-only embeddings, and lastly those using textual-only embeddings. Complementary analysis on the ability of prompt-based GPT-4Turbo and human evaluators affirms the need for robust automated detectors such as the one proposed in this study.Item Use of stem cell-derived cardiomyocyte and nasal epithelium models to establish a multi-tissue model platform to validate repurposed drugs against sars-cov-2 infection(2024-05) Agarwal, VintiThe novel coronavirus disease (COVID-19) and any future coronavirus outbreaks will require more affordable, effective and safe treatment options to complement current ones such as Paxlovid. Drug repurposing can be a promising approach if we are able to find a rapid, robust and reliable way to down-select and screen candidates using in silico and in vitro approaches. With repurposed drugs, ex vivo models could offer a rigorous route to human clinical trials with less time invested into nonclinical animal (in vivo) studies. We have previously shown the value of commercially available ex vivo/3D airway and alveolar tissue models, and this paper takes this further by developing and validating human nasal epithelial model and embryonic stem cells derived cardiomyocyte model. Five shortlisted candidates (fluvoxamine, everolimus, pyrimethamine, aprepitant and sirolimus) were successfully compared with three control drugs (remdesivir, molnupiravir, nirmatrelvir) when tested against key variants of the SARS-CoV-2 virus including Delta and Omicron, and we were able to reconfirm our earlier finding that fluvoxamine can induce antiviral efficacy in combination with other drugs. Scalability of this high-throughput screening approach has been demonstrated using a liquid handling robotic platform for future ‘Disease-X’ outbreaks.Item A clustering and graph deep learning-based framework for COVID-19 drug repurposing(Elsevier, 2024-09) Agarwal, Vinti; Deepa, P.R.Drug repurposing (or repositioning) is the process of finding new therapeutic uses for drugs already approved by drug regulatory authorities (e.g., the Food and Drug Administration (FDA) and Therapeutic Goods Administration (TGA)) for other diseases. This involves analysing the interactions between different biological entities, such as drug targets (genes/proteins and biological pathways) and drug properties, to discover novel drug–target or drug–disease relations. Machine learning and deep learning models have successfully analysed complex heterogeneous data with applications in the biomedical domain, and have also been used for drug repurposing. This study presents a novel unsupervised machine learning framework that utilizes a graph-based autoencoder for multi-feature type clustering on heterogeneous drug data. The dataset consists of 438 drugs, of which 224 are under clinical trials for COVID-19 (category A). The rest are systematically filtered to ensure the safety and efficacy of the treatment (category B). The framework solely relies on reported drug data, including its pharmacological properties, chemical/physical properties, interaction with the host, and efficacy in different publicly available COVID-19 assays. Our machine-learning framework revealed three clusters of interest and provided recommendations featuring the top 15 drugs for COVID-19 drug repurposing, which were shortlisted based on the predicted clusters that were dominated by category A drugs. Our framework can be extended to support other datasets and drug repurposing studies with the availability of our open-source code.Item Combined Hamartoma of the Retina and Retinal Pigment Epithelium: An Optical Coherence Tomography–Based Reappraisal(Elsevier, 2017-09) Agarwal, VintiTo analyze the optical coherence tomography (OCT) characteristics of combined hamartoma of the retina and retinal pigment epithelium (CHRRPE) involving the macula.Item Safeguards against Arrest and the GST Law(Heinonline, 2018) Agarwal, VintiItem Identifying Anomalous HTTP Traffic with Association Rule Mining(IEEE, 2019) Agarwal, VintiWeb applications are compromised by exploiting different vulnerabilities. The protection systems designed to detect such attacks, screen the HTTP requests to decide whether a particular request is benign or malicious. Generating effective screening rules governs the detection performance and false positive rate. In this paper, we propose to generate classification rules to identify malicious HTTP requests using co-occurrence between certain character combinations. Our idea is motivated by the fact that, a successful attack will have some combination of characters together. For e.g., in an SQL injection attack = sign may appear along with “'”. We propose to learn such character combinations using association rules with a set of carefully chosen feature (character) set. We experiment with a publicly available HTTP dataset and show that malicious HTTP requests can be identified with rules generated from such associations.Item Eye Share: The P.V. Ramana Reddy Judgment - Power to Arrest Under Special Laws vis-a-vis Code of Criminal Procedure(SSRN, 2019-08) Agarwal, VintiThe grant of powers of arrest under fiscal statutes has often come under the microscope and the GST law is no different. While enforcement of the new tax regime was initially put on the back burner, as the GST law progresses, tackling tax evasion has become one of the tax authorities’ top priorities. Of late, countless cases have been filed by persons seeking relief under the apprehension of arrest, and there have been multiple contradictory High Court judgments on the extent of the GST officials’ power to arrest. In a case before the High Court of Telangana, the court refused to take action to protect the petitioners against arrest, however the High Courts of Karnataka and the High Court of Bombay granted anticipatory bail to the aggrieved in similar matters. Many of these cases have also reached the Apex court. The Supreme Court dismissed the appeal against the aforementioned judgment of the High Court of Telangana, confirming the High Court’s order. However, in its order on the appeal filed against the judgment of the High Court of Bombay, a division bench of the Supreme Court acknowledged the need for clarification on the issue, and referred the matter to a three judge bench. In anticipation of this three judge bench Supreme Court judgment, the authors critically analyse the P.V. Ramana Reddy and Others v. Union of India (2019) judgment which was passed by the High Court of Telangana and affirmed by the Supreme Court in its order dated 27.5.2019.Item Inflammatory carcinoma of breast in a post menopausal woman - a case report(Obstetrics & Gynaecological Department, 2021) Agarwal, VintiInflammatory breast carcinoma (IBC) is also known as carcinoma mastitis (CM) and represents the most virulent form of breast cancer. It is an uncommon and aggressive form of breast cancer with inflammatory skin changes Usually presents in women between the 4th and 5 The first description of IBC / CM in the scientific literature was published in 1814 by Sir Charles Bell 1938 the terms “True IBC” and “Primary IBC” were coined to distinguish “IBC” and “secondary IBC”. Secondary IBC was defined by secondary changes in the breast or recurrence of breast cancer 3. The incidence of IBC varies in different regions of the world. More common in North Africa, 5 of all breast cancer in Tunisia 4, 4-5% in Morocco Egypt it has a rate of 11% 6.Item Learning to Detect: A Semi Supervised Multi-relational Graph Convolutional Network for Uncovering Key Actors on Hackforums(IEEE, 2021) Agarwal, VintiCybercriminals who interact extensively on underground forums, often, exchange illegal commodities and indulge in discussions on unwarranted topics. To facilitate the disruption of these highly proficient criminals, we propose a deep learning based multi-relational graph convolutional network approach to analyse the underground forum and identify key actors. We first modeled the hackforum into a homogeneous graph of users, where the multiple edges between users are captured based on their involvement in private conversations, group discussions and other miscellaneous activities. In addition, we also encode the textual content shared among users’ in form of distributed feature representation generated from BERT. To obtain ground truth labels for training data, we propose a hypothesis to calculate the scores for each user based on the quality and quantity of their involvement in the underground forum. The proposed framework jointly embeds the users’ and multi relational information to learn the nodes embeddings in the graph. We demonstrate the effectiveness of the proposed model on a neonazi underground forum, Iron March. We conducted an ablation study on the model parameters to generate the best results and achieved a classification accuracy of 82% which validates the proposed hypothesis for score computation and class labelling. To establish the robustness of our model, we compare its performance against state-of-art models. Though we used an underground forum as a showcase, the proposed model can be implemented to identify influential users’ on other social media platforms.Item POS-804 Donor vascular endothelial growth factor gene polymorphism association with acute allograft rejection in live related renal transplant recipient patients(Elsevier, 2022-02) Agarwal, VintiRenal allograft rejection risk associated with donor’s vascular endothelial growth factor (VEGF) gene polymorphism remain unelucidated till now. Although, studies have shown, an association of recipient’s VEGF polymorphism with the end-stage renal disease and early acute rejection. VEGF has pleiotropic function, which regulates vasculogenesis, endothelial cell survival signaling. Endothelial cell regulates tonicity, the permeability of blood vessels and egression of allo-stimulated inflammatory cell in intragraft compartments, thus regulate the events of rejection. In the current study, we aimed to investigate the distribution of VEGF -634C>G, -1154 G>A, -1190G>A, -1455T>C, -1499 C>T, -2578 C>A, -2549 18bp Insertion/Deletion, +405 C>G and +936 C>T SNPs among donors and recipients and to evaluate the VEGF mRNA and protein expression in intragraft tissue and in plasma.
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