Articles

  1. FEATURE LEVEL FUSION USING FACE AND PALMPRINT BIOMETRICS FOR SECURED AUTHENTICATIONDownload Article

    *1Mrs.R.Karthiga,M.E,(PhD), *2Dr.S.Mangai,M.E,PhD

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    Multibiometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a user, multiple matchers, etc.) in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in several distinct levels, including the feature extraction level, match score level and decision level. While fusion at the match score and decision levels have been extensively studied in the literature, fusion at the feature level is a relatively understudied problem. In this paper fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) fusion of LDA coefficients corresponding to the R,G,B channels of a face image; (iii) fusion of face and hand modalities is discussed. Preliminary results are encouraging and help in highlighting the pros and cons of performing fusion at this level. The primary motivation of this work is to demonstrate the viability of such a fusion and to underscore the importance of pursuing further research in this direction. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palm print images into k clusters. Index terms: Multibiometric, PCA, LDA, PAM.

  2. A STRATEGY FOR DEFENDING PACKETS AGAINST RECOGNIZED INTERNAL JAMMERS IN WIRELESS SENSOR NETWORKSDownload Article

    *1K.Manojkumar, 2M.Vinoth Kumar, 3Dr.G.Tholkappia Arasu

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    Denial of Service attacks poses a serious threat to the intended service provided to the users. Detection of the jammers is quite easy in case of external locality since they possess a significant pattern of attack and route to attack the victim. Being an internal attacker, the node would have adequate knowledge over the present defensive mechanism and additional tools to masquerade their identity. The proposed method includes a detection technique for identifying the internal compromised node based on the location attributes and markings of the packets. The packets are transmitted towards the destination node using dedicated channels and timing without the disclosure of the keys for decrypting the message to every user node. This method involves the detection of a attack with the help of marked attributes in the packet. The hash function marks all the blocks of the message, with the link to the preceding and succeeding packet. All the packets are required to reassemble the whole meaningful message. The packets without those attributes would be regarded as the attack packet. On detection of the attack, a dynamic routing algorithm would determine the least used bandwidth for previous communication and allocates a dedicated channel between the source and destination. Index terms: Denial of Service, Network Security, Detection, Message Splitting, Dynamic Routing Algorithm.

  3. CONTRADICTION COMMUNICATION RANGE OF SENSOR NETWORKSDownload Article

    *1Mr. G.Parthasarathy, 2Mr. P.Vijayan,M.E.,

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    The knowledge of sensors’ locations is crucial information for many applications in Wireless Sensor Networks (WSNs). When sensor nodes are deployed in hostile environments, the localization schemes are vulnerable to various attacks, e.g., wormhole attack, pollution attack, range enlargement/reduction attack, and etc. Therefore, sensors’ locations are not trustworthy and need to be verified before they can be used by location-based applications. Previous verification schemes either require group-based deployment knowledge of the sensor field, or depend on expensive or dedicated hardware, thus they cannot be used for low-cost sensor networks. In this paper, we propose a lightweight location verification system that performs both “on-spot” and “in-region” location verifications. The on-spot verification intends to verify whether the locations claimed by sensors are far from their true spots beyond a certain distance. We propose two algorithms that detect abnormal locations by exploring the inconsistencies between sensors’ claimed locations and their neighborhood observations. The in-region verification verifies whether a sensor is inside an application-specific verification region. Compared to on-spot verification, the in-region verification is tolerable to large errors as long as the locations of sensors don’t cause the application to malfunction. To study how to derive the verification region for different applications and design a probabilistic algorithm to compute in-region confidence for each sensor. Experiment results show that our on-spot and in-region algorithms can verify sensors’ locations with high detection rate and low false positive rate. They are robust in the presence of malicious attacks that are launched during the verification process. Moreover, compared with previous verification schemes, our algorithms are effective and lightweight because they do not rely on the knowledge of deployment of sensors, and they don’t require expensive or dedicated hardware, so our algorithms can be used in any low-cost sensor networks. Index terms: WSN, Lightweight, On-spot, In-region, Sensors.

  4. ANONYMIZATION OF PRIVACY PRESERVATIONDownload Article

    *1Mr. V.Balaganesh, 2Mr. Vini Coltin Roy,M.E.,

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    Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that generalization loses considerable amount of information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. A novel technique called slicing is used, which partitions the data both horizontally and vertically. Slicing preserves better data utility than generalization and can be used for membership disclosure protection. Another important advantage of slicing is that it can handle high-dimensional data. The slicing can be used for attribute disclosure protection and develop an efficient algorithm for computing the sliced data that obey the l-diversity requirement. The workload experiments confirms that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute. The experiments also demonstrate that slicing can be used to prevent membership disclosure. Index terms: Sensitive-attributes, quasive-identifiers, generalization, bucketization, multiset generalization.

  5. ENHANCING SECURITY IN CLOUD COMPUTING BY COMBINING DYNAMIC BROADCAST ENCRYPTION, BIT TORRENT AND GROUP SIGNATUREDownload Article

    *1Ms.R.Malar Priya, *2Ms.R.Kalpana, 3S.Saravanakumar,M.E.,

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    Cloud computing refers to a network that distributes processing power, applications, and large systems among many computers. Cloud computing seems to offer some incredible benefits for communicators: the availability of an incredible array of software applications, access to lightning-quick processing power, unlimited storage, and the ability to easily share and process information. All of this is available through your browser any time you can access the Internet. While this might all appear enticing, there remain issues of reliability, portability, privacy, and security. Since the data transmission on the internet or over any networks are vulnerable to the hackers attack. We are in great need of encrypting the data. This paper combines the techniques of cloud data storage and content Distribution by dynamic broadcast encryption algorithm along with the Bit Torrent application results in minimizing the difficulties of bulky data and aims in resulting efficient sharing of the secure storage services in cloud computing. Index terms: Bit torrent, content distribution, Dynamic broadcast encryption, group signature.

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