M Tech Dissertations

Permanent URI for this collectionhttp://drsr.daiict.ac.in/handle/123456789/3

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    Privacy-Preserving Iris Based Authentication System
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Agrawal, Radha; Singh, Priyanka; Joshi, Manjunath V.
    Biometric authentication systems have gained immense popularity due to theirability to provide secure and convenient authentication. However, the leakageof sensitive biometric data can compromise an individual�s privacy and security.To address this issue, a privacy-preserving biometric authentication system basedon iris data is proposed in this paper. The framework exploits the homomorphicproperties to process encrypted data, thereby ensuring the privacy of sensitivedata, even while using the services of third-party cloud service providers (CSPs).In the initial stage of the experiment, we encrypt the data, and comparison wasdone by using hamming distance, but after completion of the first experiment,we realized that data can be morphed through an insecure channel by using multipleattacks to overcome this we have proposed framework were morphing isperformed on the iris data by using a man-in-the-middle attack. Two iris identificationAlgorithms are proposed, with a success rate of over 60% and a false matchrate of 5%, and are vulnerable to morph attacks. We also examine how comparablethe original and morphed iris images must be. Using original images, we presentour findings for morphing iris detection. The proposed privacy-preserving biometricauthentication system offers a robust framework that minimizes time complexitycompared to other state-of-the-art approaches. This framework ensuresthe privacy of sensitive data and provides a secure biometric authentication system.
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    Investigating Robustness of Face Recognition System against Adversarial Attacks
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Sarvaiya, Maulik Karshanbhai; Bhilare, Shruti
    Facial Recognition (FR) systems based on deep neural networks (DNNs) are widelyused in critical applications such as surveillance and access control necessitat-ing their reliable working. Recent research has highlighted the vulnerability ofDNNs to adversarial attacks, which involve adding imperceptible perturbationsto the original image. The presence of these adversarial attacks raises seriousconcerns about the security and robustness of deep neural networks. As a re-sult, researchers are actively exploring and developing strategies to strengthenthe DNNs against such threats. Additionally, the object used should look natu-ral and not draw undue attention. Attacks are carried out in white-box targetedas well as untargeted settings on Labeled Faced in Wild (LFW) dataset. Attacksuccess rate of 97.76% and 91.78% are achieved in untargeted and targeted set-tings, respectively demonstrating the high vulnerability of the FR systems to suchattacks. The attacks will be evaluated in the digital domain to optimize the adver-sarial pattern, its size and location on the face.
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    Security and Privacy concerns in Voice Assistants Devices
    (2021) Trivedi, Revant; Das, Manik Lal
    Voice assistant devices are the new generation devices which provides voice interfaces to interact. They are backed with powerful technologies and service providers. These devices perform various tasks by just providing voice commands. Although it has many uses but there is a risk associated with it. The main concern with these devices is continuous listening. In order to provide a real time response, these devices keep their microphone on. Which compromises user’s privacy as well as security. Numerous approaches have been carried out but still it’s an issue which requires strong attention. In this work, we are focusing on how to avoid the continuous listening and how to protect user’s privacy. Adversaries target the Voice assistant devices when user is not aware or user is not around. They can collect the data, control the connected IoT devices, or can waste user’s resources. We present an approach that provides solution to all these problems. We propose a Jammer mechanism which can be controlled by the mobile phone. It jams the microphone whenever the user wants and protect user’s privacy as well as keep safe from unknown attacks. The jammer gets one more layer of protection by Bluetooth module, which does not let an attacker connect to the device.
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    Query interceptor
    (2020) Suthar, Shubham Lalitkumar; Tiwari, Saurabh
    Query Interceptor is a product comprising three components which aims to maintain healthy database by restricting bad queries from hitting the database and restrict user access to only permitted data. It intercepts queries before hitting the database, identifies queries that are bad for cluster health, sanitizes those queries and applies security filters on queries to ensure authorized access to the database. Apart from this, Query Interceptor also gives information about queries like aliases, subqueries, tables, columns, joins, table count and join count.
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    ItemOpen Access
    Medical image security with cheater identification using secret sharing scheme
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2015) Krishnan, Arun; Das, Manik Lal
    The progress in the field of information and communication technology has brought about quick and efficient transfer of textual as well as multimedia data . However, the growth of technology has also provided new ways for unauthorized access and illegal modifications of data, thereby, affecting data security. Secure data transmission is a necessity, especially in medical and legal fields. Doctors need to be convinced about the legitimacy of the medical images as well as associated health records they receive, especially in networking applications such as telediagnosis, teleconsultation,telesurgery etc. Furthermore, medical images should not be discernible to malignant agents with evil intentions on patient’s health. This thesis proposes a (k,n) secret sharing scheme for secure transfer of medical images and related electronic patient records (EPR) to a team of doctors through public insecure channels. The scheme prevents unauthorized access and detects illegal tampering of transmitted images and records. The scheme also considers the presence of a deceiver among the group of participants and includes techniques to detect any deception from the participant doctors and uniquely identify the deceiver. Furthermore, the scheme includes procedures to prevent the unauthorized release of medical image by any of the participating doctors. Simulation results shows that the proposed scheme satisfies all the security features discussed above.