638 research outputs found

    A Novel Approach for Preserving Privacy of Content Based Information Reterival System

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    Content based information retrieval system (CBIR) are advanced version of retrieval systems where search is based upon specific criteria in order to get relevant items. In networking environment, as search is based on content it is easy for server to know client’s interest, where client has to trust server to get relevant items. Sometimes query contains sensitive information that client does not want to reveal it, but still search should be performed. This is achieved by our proposed structure, where mainly it will deal with multimedia items such as image or audio files. In order to preserve privacy , client selects multimedia file of which hash value is generated, this value is fired towards cloud server. Cloud server contains database of stored hash values of multimedia items and based upon hamming distance and similarity search, encrypted candidate list is prepared and send it to client. Client finds best item by carrying decryption

    THRIVE: Threshold Homomorphic encryption based secure and privacy preserving bIometric VErification system

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    In this paper, we propose a new biometric verification and template protection system which we call the THRIVE system. The system includes novel enrollment and authentication protocols based on threshold homomorphic cryptosystem where the private key is shared between a user and the verifier. In the THRIVE system, only encrypted binary biometric templates are stored in the database and verification is performed via homomorphically randomized templates, thus, original templates are never revealed during the authentication stage. The THRIVE system is designed for the malicious model where the cheating party may arbitrarily deviate from the protocol specification. Since threshold homomorphic encryption scheme is used, a malicious database owner cannot perform decryption on encrypted templates of the users in the database. Therefore, security of the THRIVE system is enhanced using a two-factor authentication scheme involving the user's private key and the biometric data. We prove security and privacy preservation capability of the proposed system in the simulation-based model with no assumption. The proposed system is suitable for applications where the user does not want to reveal her biometrics to the verifier in plain form but she needs to proof her physical presence by using biometrics. The system can be used with any biometric modality and biometric feature extraction scheme whose output templates can be binarized. The overall connection time for the proposed THRIVE system is estimated to be 336 ms on average for 256-bit biohash vectors on a desktop PC running with quad-core 3.2 GHz CPUs at 10 Mbit/s up/down link connection speed. Consequently, the proposed system can be efficiently used in real life applications

    DRSIG: Domain and Range Specific Index Generation for encrypted Cloud data

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    One of the most fundamental services of cloud computing is Cloud storage service. Huge amount of sensitive data is stored in the cloud for easy remote access and to reduce the cost of storage. The confidential data is encrypt before uploading to the cloud server in order to maintain privacy and security. All conventional searchable symmetric encryption(SSE) schemes enable the users to search on the entire index file. In this paper, we propose the Domain and Range Specific Index Generation(DRSIG) scheme that minimizes the Index Generation time. This scheme adopts collection sort technique to split the index file into D Domains and R Ranges. The Domain is based on the length of the keyword; the Range splits within the domain based on the first letter of the keyword. A mathematical model is used to encrypt the indexed keyword that eliminates the information leakage. The time complexity of the index generation is O(NT × 3) where NT - Number of rows in index document and 3 is Number of columns in index document. Experiments have been conducted on real world dataset to validate proposed DRSIG scheme. It is observed that DRSIG scheme is efficient and provide more secure data than Ranked Searchable Symmetric Encryption(RSSE) Scheme

    Salattujen komento- ja ohjauskanavien havaitseminen verkkosormenjälkien avulla

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    The threat landscape of the Internet has evolved drastically into an environment where malware are increasingly developed by financially motivated cybercriminal groups who mirror legitimate businesses in their structure and processes. These groups develop sophisticated malware with the aim of transforming persistent control over large numbers of infected machines into profit. Recent developments have shown that malware authors seek to hide their Command and Control channels by implementing custom application layer protocols and using custom encryption algorithms. This technique effectively thwarts conventional pattern-based detection mechanisms. This thesis presents network fingerprints, a novel way of performing network-based detection of encrypted Command and Control channels. The goal of the work was to produce a proof of concept system that is able to generate accurate and reliable network signatures for this purpose. The thesis presents and explains the individual phases of an analysis pipeline that was built to process and analyze malware network traffic and to produce network fingerprint signatures. The analysis system was used to generate network fingerprints that were deployed to an intrusion detection system in real-world networks for a test period of 17 days. The experimental phase produced 71 true positive detections and 9 false positive detections, and therefore proved that the established technique is capable of performing detection of targeted encrypted Command and Control channels. Furthermore, the effects on the performance of the underlying intrusion detection system were measured. These results showed that network fingerprints induce an increase of 2-9% to the packet loss and a small increase to the overall computational load of the intrusion detection system.Internetin uhkaympäristön radikaalin kehittymisen myötä edistyksellisiä haittaohjelmia kehittävät kyberrikollisryhmät ovat muuttuneet järjestäytyneiksi ja taloudellista voittoa tavoitteleviksi organisaatioiksi. Nämä rakenteiltaan ja prosesseiltaan laillisia yrityksiä muistuttavat organisaatiot pyrkivät saastuttamaan suuria määriä tietokoneita ja saavuttamaan yhtämittaisen hallintakyvyn. Tutkimukset ovat osoittaneet, että tuntemattomien salausmenetelmien ja uusien sovellustason protokollien käyttö haittaohjelmien komento- ja hallintakanavien piilottamiseksi tietoverkoissa ovat kasvussa. Tämän kaltaiset tekniikat vaikeuttavat oleellisesti perinteisiä toistuviin kuvioihin perustuvia havaitsemismenetelmiä. Tämä työ esittelee salattujen komento- ja hallintakanavien havaitsemiseen suunnitellun uuden konseptin, verkkosormenjäljet. Työn tavoitteena oli toteuttaa prototyyppijärjestelmä, joka analysoi ja prosessoi haittaohjelmaliikennettä, sekä kykenee tuottamaan tarkkoja ja tehokkaita haittaohjelmakohtaisia verkkosormenjälkitunnisteita. Työ selittää verkkosormenjälkien teorian ja käy yksityiskohtaisesti läpi kehitetyn järjestelmän eri osiot ja vaiheet. Järjestelmästä tuotetut verkkosormenjäljet asennettiin 17 päiväksi oikeisiin tietoverkkoihin osaksi tunkeilijan havaitsemisjärjestelmää. Testijakso tuotti yhteensä 71 oikeaa haittaohjelmahavaintoa sekä 9 väärää havaintoa. Menetelmän käyttöönoton vaikutukset tunkeilijan havaitsemisjärjestelmän suorituskykyyn olivat 2 – 9 % kasvu pakettihäviössä ja pieni nousu laskennallisessa kokonaiskuormituksessa. Tulokset osoittavat, että kehitetty järjestelmä kykenee onnistuneesti analysoimaan haittaohjelmaliikennettä sekä tuottamaan salattuja komento- ja hallintakanavia havaitsevia verkkosormenjälkiä
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