Leakage-resilient biometric-based remote user authentication with fuzzy extractors

National Research Foundation (NRF) Singapor

Privacy-preserving biometric-based remote user authentication with leakage resilience

National Research Foundation (NRF) Singapor

Privacy and security protection in cloud integrated sensor networks

Wireless sensor networks have been widely deployed in many social settings to monitor human activities and urban environment. In these contexts, they acquire and collect sensory data, and collaboratively fuse the data. Due to resource constraint, sensor nodes however cannot perform complex data processing. Hence, cloud-integrated sensor networks have been proposed to leverage the cloud computing capabilities for processing vast amount of heterogeneous sensory data. After being processed, the sensory data can then be accessed and shared among authorized users and applications pervasively. Various security and privacy threats can arise when the people-centric sensory data is collected and transmitted within the sensor network or from the network to the cloud; security and privacy remain a big concern when the data is later accessed and shared among different users and applications after being processed. Extensive research has been conducted to address the security and privacy issues without sacrificing resource efficiency. Unfortunately, the goals of security/privacy protection and resource efficiency may not be easy to accomplish simultaneously, and may even be sharply contrary to each other. Our research aims to reconcile the conflicts between these goals in several important contexts. Specifically, we first investigate the security and privacy protection of sensory data being transmitted within the sensor network or from the sensor network to the cloud, which includes: (1) efficient, generic privacy preserving schemes for sensory data aggregation; (2) a privacy-preserving integrity detection scheme for sensory data aggregation; (3) an efficient and source-privacy preserving scheme for catching packet droppers and modifiers. Secondly, we further study how to address people\u27s security and privacy concerns when accessing sensory data from the cloud. To preserve privacy for sensory data aggregation, we propose a set of generic, efficient and collusion-resilient privacy-preserving data aggregation schemes. On top of these privacy preserving schemes, we also develop a scheme to simultaneously achieve privacy preservation and detection of integrity attack for data aggregation. Our approach outperforms existing solutions in terms of generality, node compromise resilience, and resource efficiency. To remove the negative effects caused by packet droppers and modifiers, we propose an efficient scheme to identify and catch compromised nodes which randomly drop packets and/or modify packets. The scheme employs an innovative packet marking techniques, with which selective packet dropping and modification can be significantly alleviated while the privacy of packet sources can be preserved. To preserve the privacy of people accessing the sensory data in the cloud, we propose a new efficient scheme for resource constrained devices to verify people\u27s access privilege without exposing their identities in the presence of outsider attacks or node compromises; to achieve the fine-grained access control for data sharing, we design privacy-preserving schemes based on users\u27 affiliated attributes, such that the access policies can be flexibly specified and enforced without involving complicated key distribution and management overhead. Extensive analysis, simulations, theoretical proofs and implementations have been conducted to evaluate the effectiveness and efficiency of our proposed schemes. The results show that our proposed schemes resolve several limitations of existing work and achieve better performance in terms of resource efficiency, security strength and privacy preservation

Attribute-Based Encryption Scheme for Secured data Storage in Cloud Computing

This a storage security model in Cloud Computing and making a considerable measure of convincing purposes behind organizations to convey cloud-based storage. For another business, start-up costs are fundamentally decreased in light of the fact that there is no compelling reason to contribute capital in advance for an inner to help the business. By a long shot, the main inquiry customers considering a move to cloud storage ask is regardless of whether their data will be secure. Stored data offsite doesn't change data security necessities; they are the same as those confronting data put away on location. Security ought to be based on business prerequisites for particular applications and data sets, regardless of where the data is stored. We trust that data storage security in Cloud Computing, a zone brimming with challenges and of fundamental significance, is still in its earliest stages now, and numerous examination issues are yet to be distinguished. In this paper, we examined the issue of data security in cloud data storage, to guarantee the rightness of customers' data in cloud data storage. We proposed a Hierarchical Attribute-Based Secure Outsourcing for moldable Access in Cloud computing which likewise guarantees data storage security and survivability accordingly giving put stock in condition to the customers. To battle against unapproved data spillage, delicate data must be encoded before outsourcing in order to give end-to-end data confidentiality affirmation in the cloud and past. It upgrades the security in the proposed model successfully.

The Secured Attribute-Based Document Collection Hierarchical Encryption Scheme in Cloud Computing

This paper is an endeavor to give an upgraded data storage security model in Cloud Computing and making a put stock in condition in cloud computing. There are a considerable measure of convincing purposes behind organizations to convey cloud-based storage. For another business, start-up costs are fundamentally decreased in light of the fact that there is no compelling reason to contribute capital in advance for an inner to help the business. By a long shot, the main inquiry customers considering a move to cloud storage ask is regardless of whether their data will be secure. Stored data offsite doesn't change ata security necessities; they are the same as those confronting data put away on location. Security ought to be based on business prerequisites for particular applications and data sets, regardless of where the data is stored. We trust that data storage security in Cloud Computing, a zone brimming with challenges and of fundamental significance, is still in its earliest stages now, and numerous examination issues are yet to be distinguished. In this paper, we examined the issue of data security in cloud data storage, to guarantee the rightness of customers' data in cloud data storage. We proposed a Hierarchical Attribute-Based Secure Outsourcing for moldable Access in Cloud computing which likewise guarantees data storage security and survivability accordingly giving put stock in condition to the customers. To battle against unapproved data spillage, delicate data must be encoded before outsourcing in order to give end-to-end data confidentiality affirmation in the cloud and past. It upgrades the security in the proposed model successfully

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Garbling Schemes and Applications

The topic of this thesis is garbling schemes and their applications. A garbling scheme is a set of algorithms for realizing secure two-party computation. A party called a client possesses a private algorithm as well as a private input and would like to compute the algorithm with this input. However, the client might not have enough computational resources to evaluate the function with the input on his own. The client outsources the computation to another party, called an evaluator. Since the client wants to protect the algorithm and the input, he cannot just send the algorithm and the input to the evaluator. With a garbling scheme, the client can protect the privacy of the algorithm, the input and possibly also the privacy of the output. The increase in network-based applications has arisen concerns about the privacy of user data. Therefore, privacy-preserving or privacy-enhancing techniques have gained interest in recent research. Garbling schemes seem to be an ideal solution for privacy-preserving applications. First of all, secure garbling schemes hide the algorithm and its input. Secondly, garbling schemes are known to have efficient implementations. In this thesis, we propose two applications utilizing garbling schemes. The first application provides privacy-preserving electronic surveillance. The second application extends electronic surveillance to more versatile monitoring, including also health telemetry. This kind of application would be ideal for assisted living services. In this work, we also present theoretical results related to garbling schemes. We present several new security definitions for garbling schemes which are of practical use. Traditionally, the same garbled algorithm can be evaluated once with garbled input. In applications, the same function is often evaluated several times with different inputs. Recently, a solution based on fully homomorphic encryption provides arbitrarily reusable garbling schemes. The disadvantage in this approach is that the arbitrary reuse cannot be efficiently implemented due to the inefficiency of fully homomorphic encryption. We propose an alternative approach. Instead of arbitrary reusability, the same garbled algorithm could be used a limited number of times. This gives us a set of new security classes for garbling schemes. We prove several relations between new and established security definitions. As a result, we obtain a complex hierarchy which can be represented as a product of three directed graphs. The three graphs in turn represent the different flavors of security: the security notion, the security model and the level of reusability. In addition to defining new security classes, we improve the definition of side-information function, which has a central role in defining the security of a garbling scheme. The information allowed to be leaked by the garbled algorithm and the garbled input depend on the representation of the algorithm. The established definition of side-information models the side-information of circuits perfectly but does not model side-information of Turing machines as well. The established model requires that the length of the argument, the length of the final result and the length of the function can be efficiently computable from the side-information function. Moreover, the side-information depends only on the function. In other words, the length of the argument, the length of the final result and the length of the function should only depend on the function. For circuits this is a natural requirement since the number of input wires tells the size of the argument, the number of output wires tells the size of the final result and the number of gates and wires tell the size of the function. On the other hand, the description of a Turing machine does not set any limitation to the size of the argument. Therefore, side-information that depends only on the function cannot provide information about the length of the argument. To tackle this problem, we extend the model of side-information so that side-information depends on both the function and the argument. The new model of side information allows us to define new security classes. We show that the old security classes are compatible with the new model of side-information. We also prove relations between the new security classes.Tämä väitöskirja käsittelee garblausskeemoja ja niiden sovelluksia. Garblausskeema on työkalu, jota käytetään turvallisen kahden osapuolen laskennan toteuttamiseen. Asiakas pitää hallussaan yksityistä algoritmia ja sen yksityistä syötettä, joilla hän haluaisi suorittaa tietyn laskennan. Asiakkaalla ei välttämättä ole riittävästi laskentatehoa, minkä vuoksi hän ei pysty suorittamaan laskentaa itse, vaan joutuu ulkoistamaan laskennan toiselle osapuolelle, palvelimelle. Koska asiakas tahtoo suojella algoritmiaan ja syötettään, hän ei voi vain lähettää niitä palvelimen laskettavaksi. Asiakas pystyy suojelemaan syötteensä ja algoritminsa yksityisyyttä käyttämällä garblausskeemaa. Verkkopohjaisten sovellusten kasvu on herättänyt huolta käyttäjien datan yksityisyyden turvasta. Siksi yksityisyyden säilyttävien tai yksityisyyden suojaa lisäävien tekniikoiden tutkimus on saanut huomiota. Garblaustekniikan avulla voidaan suojata sekä syöte että algoritmi. Lisäksi garblaukselle tiedetään olevan useita tehokkaita toteutuksia. Näiden syiden vuoksi garblausskeemat ovat houkutteleva tekniikka käytettäväksi yksityisyyden säilyttävien sovellusten toteutuksessa. Tässä työssä esittelemme kaksi sovellusta, jotka hyödyntävät garblaustekniikkaa. Näistä ensimmäinen on yksityisyyden säilyttävä sähköinen seuranta. Toinen sovellus laajentaa seurantaa monipuolisempaan monitorointiin, kuten terveyden kaukoseurantaan. Tästä voi olla hyötyä etenkin kotihoidon palveluille. Tässä työssä esitämme myös teoreettisia tuloksia garblausskeemoihin liittyen. Esitämme garblausskeemoille uusia turvallisuusmääritelmiä, joiden tarve kumpuaa käytännön sovelluksista. Perinteisen määritelmän mukaan samaa garblattua algoritmia voi käyttää vain yhdellä garblatulla syötteellä laskemiseen. Käytännössä kuitenkin samaa algoritmia käytetään usean eri syötteen evaluoimiseen. Hiljattain on esitetty tähän ongelmaan ratkaisu, joka perustuu täysin homomorfiseen salaukseen. Tämän ratkaisun ansiosta samaa garblattua algoritmia voi turvallisesti käyttää mielivaltaisen monta kertaa. Ratkaisun haittapuoli kuitenkin on, ettei sille ole tiedossa tehokasta toteutusta, sillä täysin homomorfiseen salaukseen ei ole vielä onnistuttu löytämään sellaista. Esitämme vaihtoehtoisen näkökulman: sen sijaan, että samaa garblattua algoritmia voisi käyttää mielivaltaisen monta kertaa, sitä voikin käyttää vain tietyn, ennalta rajatun määrän kertoja. Tämä näkökulman avulla voidaan määritellä lukuisia uusia turvallisuusluokkia. Todistamme useita relaatioita uusien ja vanhojen turvallisuusmääritelmien välillä. Relaatioiden avulla garblausskeemojen turvallisuusluokille saadaan muodostettua hierarkia, joka koostuu kolmesta komponentista. Tieto, joka paljastuu garblatusta algoritmista tai garblatusta syötteestä riippuu siitä, millaisessa muodossa algoritmi on esitetty, kutsutaan sivutiedoksi. Vakiintunut määritelmä mallintaa loogisen piiriin liittyvää sivutietoa täydellisesti, mutta ei yhtä hyvin Turingin koneeseen liittyvää sivutietoa. Tämä johtuu siitä, että jokainen yksittäinen looginen piiri asettaa syötteensä pituudelle rajan, mutta yksittäisellä Turingin koneella vastaavanlaista rajoitusta ei ole. Parannamme sivutiedon määritelmää, jolloin tämä ongelma poistuu. Uudenlaisen sivutiedon avulla voidaan määritellä uusia turvallisuusluokkia. Osoitamme, että vanhat turvallisuusluokat voidaan esittää uudenkin sivutiedon avulla. Todistamme myös relaatioita uusien luokkien välillä.Siirretty Doriast