Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
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Item Video surveillance for the crime detection using features(Springer, 2021) Chowdhary, A.; Rudra, B.This paper aims at extending the comparison between two images and locating the query image in the source image by matching the features in the videos by presenting a method for the recognition of a particular person or an object. The frames matching the feature (not feature its query) object in a given video will be the output. We describe a method to find unique feature points in an image or a frame using SIFT, i.e., scale-invariant feature transform method. SIFT is used for extracting distinctive feature points which are invariant to image scaling or rotation, presence of noise, changes in image lighting, etc. After the feature points are recognized in an image, the image is tracked for comparison with the feature points found in the frames. The feature points are compared using homography estimation search to find the required query image in the frame. In case the object is not present in the frame, then it will not present any output. © Springer Nature Singapore Pte Ltd 2021.Item Software verification using state diagrams(Grenze Scientific Society, 2021) Bhowmik, M.; Chowdhary, A.; Rudra, B.During the development of software, a programmer will commit many logical errors unknowingly such that the software is not in accordance with the requirements. Such logical errors affect the correctness of the software. The requirements specify some important properties of the software and this knowledge about it will allow to know the behavior of the software which can be leveraged to find certain logical errors. This paper proposes a method which helps to find bugs as well as describes a way by which the programmer can specify software requirements. Based on these programmer specified requirements, the system can be automatically used to verify the software. Also, the method proposed in this paper does not need to use the expected result of a test case to verify the software’s correctness. The proposed algorithm completely relies on the requirements specified by the programmer for finding bugs in the software. The software verification process and the algorithm used is explained with the help of a case study. The paper highlights the advantages of the method and algorithm proposed for software verification along with the implementation details. © Grenze Scientific Society, 2021.Item FQDN similarity and cache-miss property based DNS tunneling detection technique(Grenze Scientific Society, 2021) Bhowmik, M.; Chowdhary, A.; Rudra, B.Although there are many effective methods to detect DNS Tunneling attacks, the attacks still happen, and the attackers can mock genuine queries to bypass such checks. However, in data exfiltration, the DNS queries are continuously changing as some part of it represents the data itself. Thus, all such queries would result in a cache miss, and therefore we can use such properties to detect DNS Tunneling attacks. However, relying on this is not enough as it will also have many false positives. To overcome the problem, we propose three criteria-based methods that consider DNS Tunneling queries’ properties and use them to reduce the number of false positives and thus accurately detect DNS Tunneling traffic. We even discussed the bypassing checks in this paper, and they are both costly and require the attacker to make redundant queries. © Grenze Scientific Society, 2021.Item DNS tunneling detection using machine learning and cache miss properties(Institute of Electrical and Electronics Engineers Inc., 2021) Chowdhary, A.; Bhowmik, M.; Rudra, B.In a DNS Tunneling attack, data or other useful information is embedded within a DNS query and exfiltrated. Such attacks are difficult to detect because DNS is a fundamental protocol and blocking legitimate domain names can lead to an unpleasant experience for the users. Thus, detecting whether the DNS query is exfiltrating data or not is a challenging task. Mimicking genuine queries by the attacker makes this even more difficult. This research work presents two different methods for detecting the DNS Tunneling query and later they are combined to build a DNS Tunneling Attack Detector that can inform the client about a potential attack going on in real time. The first method uses cache misses in a DNS cache server and the second method utilizes machine learning techniques to classify a given DNS query. Overall, with around 93% accuracy of certain Machine Learning classifiers on classifying on a per packet basis along with extra validation from the cache-miss approach, a detector has been developed to accurately report DNS tunneling traffic © 2021 IEEE.Item Blockchain based Framework for Student Identity and Educational Certificate Verification(Institute of Electrical and Electronics Engineers Inc., 2021) Chowdhary, A.; Agrawal, S.; Rudra, B.With the rise in digitization of documents stored online, it is important to have a document verification process. It involves customized verification and authentication of a document based on the content of the document. Among all the certificates, the educational certificate is one of the most important certificates, especially for students. Unfortunately, it is very easy to fake documents that are hard to identify nowadays and are often considered original. Blockchain has recently emerged as a potential alternative to manual verification of certificates. It provides a distributed ledger that is verifiable with cryptographic mechanisms. Also, it provides a common platform for easily sharing, storing, and accessing documents. The identity of the students can be verified using government authorized identity proofs. This paper proposes the use of such unique identity number and secret phrase provided by the student to further improve the security of the certificate verification system. The student's identity and document are both verified by matching the hashes already present in the Blockchain. Also, in the proposed method the documents are linked to the student to add another layer of verification. The implementation of this proposed platform can be used to issue, receive and verify the certificates. © 2021 IEEE.Item Content-based medical image retrieval system for lung diseases using deep CNNs(Springer Science and Business Media B.V., 2022) Agrawal, S.; Chowdhary, A.; Agarwala, S.; Mayya, V.; Kamath S․, S.K.Content-based image retrieval (CBIR) systems are designed to retrieve images that are relevant, based on detailed analysis of latent image characteristics, thus eliminating the dependency of natural language tags, text descriptions, or keywords associated with the images. A CBIR system maintains high-level image visuals in the form of feature vectors, which the retrieval engine leverages for similarity-based matching and ranking for a given query image. In this paper, a CBIR system is proposed for the retrieval of medical images (CBMIR) for enabling the early detection and classification of lung diseases based on lung X-ray images. The proposed CBMIR system is built on the predictive power of deep neural models for the identification and classification of disease-specific features using transfer learning based models trained on standard COVID-19 Chest X-ray image datasets. Experimental evaluation on the standard dataset revealed that the proposed approach achieved an improvement of 49.71% in terms of precision, averaging across various distance metrics. Also, an improvement of 26.55% was observed in the area under precision-recall curve (AUPRC) values across all subclasses. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.Item Benzidine-based chemosensors for the selective detection of phosphate, carbonate and copper ions: Applications in water and food sample analysis and on-field detection kit(Elsevier Inc., 2024) Chowdhary, A.; Dhawale, A.; Trivedi, D.R.In this work, benzidine-based chemosensors were synthesized. A5R1 had a cage-like structure along with 2-OH binding sites for encapsulation of Cu2+, A5R2 was found to bind with PO43¯ and CO32¯ ion; whereas A5R3 was innocent towards any cations or anions. The LOD for A5R1 with Cu2+ was found to be 2.63 ppm. A5R2 detected PO43¯ and CO32¯ with limit of detections 4.13 ppm and 5.40 ppm respectively. The interference studies indicated that there was no other ion which could restrain the analysis. Job's Plots showcased the 1:2 binding of the receptors with the analyte ion(s). The practical applicability of the probes was demonstrated by on-field detection kit and test-strip fabrication with colour change chart. Logic gate formulation with active simulation governed by the reversibility studies envisaged the reversibility and reusability of the probe and its solicitation in making electric devices. Furthermore, spiking studies proved the application of the receptors for convenient analyte detection in real-life food and water samples. © 2024 Elsevier B.V.