Journal Articles
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884
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Item Object detection in hyperspectral images(Elsevier Inc., 2022) Lone, Z.A.; Pais, A.R.Object Detection is a task of estimating and locating an object precisely in an image. It is a fundamental problem in computer vision and has been studied extensively in low dimensional images like RGB, grayscale, etc. High dimensional images like Hyperspectral images (HSI) contain ample information and are very powerful in enhancing the fine spectral differences between different objects. The advancement in spectral sensor technologies is making hyperspectral data more readily available, making it a promising technology for image analysis tasks. HSI has been explored in the fields of remote sensing, biomedical imaging, mineral classification, goods quality assessment, and object detection etc. The research concerning object detection in HSI has been gathering pace in recent times. This survey paper is an attempt to create a resource for researchers in the field. This paper provides a comprehensive review of both Supervised and Salient object detection. Moreover, a collection of important datasets is mentioned. We conclude the paper by mentioning research challenges and the future directions for the research in the field. © 2022 Elsevier Inc.Item Machine learning models for phishing detection from TLS traffic(Springer, 2023) Kumar, M.; Kondaiah, C.; Pais, A.R.; Rao, R.S.Phishing is a fraudulent tactic for attackers to obtain victims personal information, such as passwords, account details, credit card details, and other sensitive information. Existing anti-phishing detection methods using at the application layer and cannot be applied at the transport layer. A novel machine learning (ML) based phishing detection technique from transport layer security (TLS) 1.2 and TLS 1.3 encrypted traffic without decryption is proposed in this paper. Our proposed model detects phishing URLs at the transport layer and classifies them as legitimate or phishing. The features are extracted from TLS 1.2 and TLS 1.3 traffic, and phishing detection is performed using ML algorithms based on the extracted features. The datasets for legitimate and phishing sites are created using features derived from TLS 1.2 and TLS 1.3 traffic. According to the experimental results, the proposed model effectively detects phishing URLs in encrypted traffic. The proposed model achieves an accuracy of 93.63% for Random Forest (RF), 95.07% for XGBoost (XGB), and the highest accuracy of 95.40% for Light GBM (LGBM). © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Item A new probabilistic rekeying method for secure multicast groups(2010) Pais, A.R.; Joshi, S.The Logical Key Hierarchy (LKH) is the most widely used protocol in multicast group rekeying. LKH maintains a balanced tree that provide uniform cost of O(log N) for compromise recovery, where N is group size. However, it does not distinguish the behavior of group members even though they may have different probabilities of join or leave. When members have diverse changing probabilities, the gap between LKH and the optimal rekeying algorithm will become bigger. The Probabilistic optimization of LKH (PLKH) scheme, optimized rekey cost by organizing LKH tree with user rekey characteristic. In this paper, we concentrate on further reducing the rekey cost by organizing LKH tree with respect to rekey probabilities of members using new join and leave operations. Simulation results show that our scheme performs 18 to 29% better than PLKH and 32 to 41% better than LKH. © 2010 Springer-Verlag.Item Automatic shadow removal algorithm for VOP, DWT based watermarking algorithm for VOP and generation of super resolved VOP(2011) Pais, A.R.; D'Souza, J.; Reddy, R.M.; Hari Krishna, P.Removal of shadow from Video Object Planes (VOPs) will assist in surveillance applications for comprehensive detection of activities. We have proposed a method for removal of shadows from the VOP. Also noise removal is done using existing methods from the VOP. To authenticate the surveillance VOP, digital watermarking is used. We have proposed digital watermarking using localized Biorthogonal wavelets for VOP. Super-resolved VOP is generated using multi-frame method. Edge model based super resolution method is used to get the better results. Also the effect of digital watermarking is studied for the super-resolved VOP. A number of test cases have been proposed and found out a best method for video surveillance application. Our proposed super resolution (SR) method gives better results than bilinear and bi-cubic methods.Item Super-resolution video generation algorithm for surveillance applications(Maney Publishing Suite 1C, Joseph's Well, Hanover Walk Leeds LS3 1AB, 2014) Pais, A.R.; D'Souza, J.; Reddy, R.M.Video surveillance is one of the major applications where high-resolution (HR) images are crucial. Since the video camera has limited spatial and temporal resolution, there is a need for super resolution video generation algorithms. In this paper, we have presented a novel technique for activity detection in the surveillance video. To achieve this goal, we have proposed and investigated efficient algorithms for Video Object Plane (VOP) generation, shadow removal from VOP and super-resolved VOP generation, for activity detection from surveillance video. The proposed VOP generation algorithm is computationally efficient and works for both dynamic and static backgrounds. The novel shadow removal algorithm for the VOP is based on texture and its performance has been studied based on average shadow detection and discrimination rates. The proposed super-resolution video generation algorithm has been designed using edge models. The performance of this algorithm has been evaluated using a numerical analysis technique and is found to be better than bi-cubic and bi-linear interpolation techniques. © 2014 RPS.Item Securing native XML database-driven web applications from XQuery injection vulnerabilities(Elsevier Inc. usjcs@elsevier.com, 2016) Palsetia, N.; Deepa, G.; Ahmed Khan, F.; Santhi Thilagam, P.S.; Pais, A.R.Database-driven web applications today are XML-based as they handle highly diverse information and favor integration of data with other applications. Web applications have become the most popular way to deliver essential services to customers, and the increasing dependency of individuals on web applications makes them an attractive target for adversaries. The adversaries exploit vulnerabilities in the database-driven applications to craft injection attacks which include SQL, XQuery and XPath injections. A large amount of work has been done on identification of SQL injection vulnerabilities resulting in several tools available for the purpose. However, a limited work has been done so far for the identification of XML injection vulnerabilities and the existing tools only identify XML injection vulnerabilities which could lead to a specific type of attack. Hence, this work proposes a black-box fuzzing approach to detect different types of XQuery injection vulnerabilities in web applications driven by native XML databases. A prototype XQueryFuzzer is developed and tested on various vulnerable applications developed with BaseX as the native XML database. An experimental evaluation demonstrates that the prototype is effective against detection of XQuery injection vulnerabilities. Three new categories of attacks specific to XQuery, but not listed in OWASP are identified during testing. © 2016 Elsevier Inc.Item En-Route Filtering Techniques in Wireless Sensor Networks: A Survey(Springer New York LLC barbara.b.bertram@gsk.com, 2017) Kumar, A.; Pais, A.R.Majority of wireless sensor networks (WSNs) are deployed in unattended environments and thus sensor nodes can be compromised easily. A compromised sensor node can be used to send fake sensing reports to the sink. If undetected these reports can raise false alarms. To deal with the problem of fake report generation, a number of en-route filtering schemes have been proposed. Each of these schemes uses different cryptographic methods to check the authenticity of reports while they are being forwarded hop by hop toward base station. However, majority of these techniques can handle only limited compromised nodes or they either need node localization or statically configured routes for sending reports. Furthermore, majority of en-route filtering techniques are vulnerable to various denial of service attacks. Our main aims in this survey are: (a) to describe the major en-route filtering techniques, (b) to analyze these techniques on various parameters including security and (c) to outline main unresolved research challenges in en-route filtering in WSNs. © 2017, Springer Science+Business Media New York.Item Batch verification of Digital Signatures: Approaches and challenges(Elsevier Ltd, 2017) Kittur, A.S.; Pais, A.R.Digital Signatures can be considered analogous to an ordinary handwritten signature for signing messages in the Digital world. Digital signature must be unique and exclusive for each signer. Multiple Digital Signatures signed by either single or multiple signers can be verified at once through Batch Verification. There are two main issues with respect to Batch Verification of Digital Signatures; first is the security problem and the second is the computational speed. Due to e-commerce proliferation, quick verification of Digital Signatures through specific hardware or efficient software becomes critical. Internet companies, banks, and other such organizations use Batch verification to accelerate verification of large number of Digital Signatures. Many Batch Verification techniques have been proposed for various Digital Signature algorithms. But most of them lack the security requirements such as signature authenticity, integrity, and non-repudiation. Hence there is a need for the study of batch verification of Digital Signatures. The main contributions of our survey include: (a) Identifying and categorizing various Batch verification techniques for RSA, DSS, and ECDSA(includes schemes based on Bilinear Pairing) (b) Providing a comparative analysis of these Batch Verification techniques (c) Identifying various research challenges in the area of Batch verification of signatures. © 2017 Elsevier LtdItem Deterministic En-Route Filtering of False Reports: A Combinatorial Design Based Approach(Institute of Electrical and Electronics Engineers Inc., 2018) Kumar, A.; Pais, A.R.Wireless sensor networks are an easy target for report fabrication attack, where compromised sensor nodes can be used by an adversary to flood the network with bogus/false reports. En-route filtering is a mechanism where intermediate forwarding nodes identify and drop false reports while they are being forwarded toward the sink. Most of the existing en-route filtering schemes are probabilistic, where sensor nodes in each cell share secret keys with a fixed probability with intermediate nodes. Thus, forwarded reports are verified probabilistically by intermediate nodes, because of which false reports can travel several hops before being dropped. Few deterministic en-route filtering schemes have also been proposed in the literature, but all such schemes require a source to send the reports through a fixed path to reach the sink. In this paper, we propose a novel deterministic en-route filtering scheme based on a combinatorial design to overcome the above-mentioned limitations of the existing schemes. The use of combinatorial design-based keys ensures direct communication between all the sensor nodes while maintaining low key storage overhead in the network. We provide a comprehensive analysis of the proposed scheme. The proposed scheme notably performs better than the existing schemes in terms of the expected filtering position of false reports. Furthermore, the proposed scheme improves data authenticity in the network and is more buoyant to selective forwarding and report disruption attacks. © 2013 IEEE.Item Black-box detection of XQuery injection and parameter tampering vulnerabilities in web applications(Springer Verlag service@springer.de, 2018) Deepa, G.; Santhi Thilagam, P.S.; Ahmed Khan, F.A.; Praseed, A.; Pais, A.R.; Palsetia, N.As web applications become the most popular way to deliver essential services to customers, they also become attractive targets for attackers. The attackers craft injection attacks in database-driven applications through the user-input fields intended for interacting with the applications. Even though precautionary measures such as user-input sanitization is employed at the client side of the application, the attackers can disable the JavaScript at client side and still inject attacks through HTTP parameters. The injected parameters result in attacks due to improper server-side validation of user input. The injected parameters may either contain malicious SQL/XML commands leading to SQL/XPath/XQuery injection or be invalid input that intend to violate the expected behavior of the web application. The former is known as an injection attack, while the latter is called a parameter tampering attack. While SQL injection has been intensively examined by the research community, limited work has been done so far for identifying XML injection and parameter tampering vulnerabilities. Database-driven web applications today rely on XML databases, as XML has gained rapid acceptance due to the fact that it favors integration of data with other applications and handles diverse information. Hence, this work proposes a black-box fuzzing approach to detect XQuery injection and parameter tampering vulnerabilities in web applications driven by native XML databases. A prototype XiParam is developed and tested on vulnerable applications developed with a native XML database, BaseX, as the backend. The experimental evaluation clearly demonstrates that the prototype is effective against detection of both XQuery injection and parameter tampering vulnerabilities. © 2017, Springer-Verlag Berlin Heidelberg.