Milos Stojmenovic

Privacy Preserving Access Control with Authentication for Securing Data in Clouds

In this paper, we propose a new privacy preserving authenticated access control scheme for securing data in clouds. In the proposed scheme, the cloud verifies the authenticity of the user without knowing the users identity before storing information. Our scheme also has the added feature of access control in which only valid users are able to decrypt the stored information. The scheme prevents replay attacks and supports creation, modification, and reading data stored in the cloud. Moreover, our authentication and access control scheme is decentralized and robust, unlike other access control schemes designed for clouds which are centralized. The communication, computation, and storage overheads are comparable to centralized approaches.

A social network approach to trust management in VANETs

In the past few years, vehicular ad hoc networks(VANETs) was studied extensively by researchers. VANETs is a type of P2P network, though it has some distinct characters (fast moving, short lived connection etc.). In this paper, we present several limitations of current trust management schemes in VANETs and propose ways to counter them. We first review several trust management techniques in VANETs and argue that the ephemeral nature of VANETs render them useless in practical situations. We identify that the problem of information cascading and oversampling, which commonly arise in social networks, also adversely affects trust management schemes in VANETs. To the best of our knowledge, we are the first to introduce information cascading and oversampling to VANETs. We show that simple voting for decision making leads to oversampling and gives incorrect results in VANETs. To overcome this problem, we propose a novel voting scheme. In our scheme, each vehicle has different voting weight according to its distance from the event. The vehicle which is more closer to the event possesses higher weight. Simulations show that our proposed algorithm performs better than simple voting, increasing the correctness of voting.

An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme. We propose an alignment-free fingerprint bio-cryptosystem based on modified VNSs.The scheme is able to compensate the VNS change caused by large non-linear distortion.Encrypted matching is performed and protected by the secure sketch, PinSketch.The Experimental results show the validity of the proposed scheme.

Balancing System Survivability and Cost of Smart Grid Via Modeling Cascading Failures

As a typical emerging application of cyber physical system, smart power grid is composed of interdependent power grid and communication/control networks. The latter one contains relay nodes for communication and operation centers to control power grid. Failure in one network might cause failures in the other. In addition, these failures may occur recursively between the two networks, leading to cascading failures. We propose a k-to- n interdependence model for smart grid. Each relay node and operation center is supported by only one power station, while each power station is monitored and controlled by k operation centers. Each operation center controls n power stations. We show that the system controlling cost is proportional to k. Through calculating the fraction of functioning parts (survival ratio) using percolation theory and generating functions, we reveal the nonlinear relation between controlling cost and system robustness, and use graphic solution to prove that a threshold exists for the proportion of faulty nodes, beyond which the system collapses. The extensive simulations validate our analysis, determine the percentage of survivals and the critical values for different system parameters. The mathematical and experimental results show that smart grid with higher controlling cost has a sharper transition, and thus is more robust. This is the first paper that focuses on on improving smart power grid robustness by changing monitoring strategies from an interdependent complex networks perspective.

Characterization of Cascading Failures in Interdependent Cyber-Physical Systems

In this paper, we focus on the cyber-physical system consisting of interdependent physical-resource and computational-resource networks, e.g., smart power grids, automated traffic control system, and wireless sensor and actuator networks, where the physical-resource and computational-resource network are connected and mutually dependent. The failure in physical-resource network might cause failures in computational-resource network, and vice versa. A small failure in either of them could trigger cascade of failures within the entire system. We aim to investigate the issue of cascading failures occur in such system. We propose a typical and practical model by introducing the interdependent complex network. The interdependence between two networks is practically defined as follows: Each node in the computational-resource network has only one support link from the physical-resource network, while each node in physical-resource network is connected to multiple computational nodes. We study the effect of cascading failures using percolation theory and present detailed mathematical analysis of failure propagation in the system. We analyze the robustness of our model caused by random attacks or failures by calculating the size of functioning parts in both networks. Our mathematical analysis proves that there exists a threshold for the proportion of faulty nodes, above which the system collapses. Using extensive simulations, we determine the critical values for different system parameters. Our simulation also shows that, when the proportion of faulty nodes approaching critical value, the size of functioning parts meets a second-order transition. An important observation is that the size of physical-resource and computational-resource networks, and the ratio between their sizes do not affect the system robustness.

Mobile Cloud Computing for Biometric Applications

The cloud computing concept became popular in 2006 and encapsulates a business model of providing services across the Internet. The Mobile Cloud Computing (MCC) concept was proposed in 2007. Recent advances in cloud computing have given a platform to various computationally heavy tasks and made them readily accessible to even mobile devices. Biometric applications are dedicated to fingerprint, face, or iris scanning and they typically work in a laboratory setting where the client computer has unlimited access to the throughput and computational resources of the network. Mobile devices can bring biometric evidence back to the laboratory in order for it to be processed. On a cloud infrastructure, information processing could be completed much faster. The limiting factor then becomes the battery power of the device and the throughput of the communication channel of the client node to the cloud. It is important to reduce as much as possible the packet size of the query or task given to the cloud, and also minimize the size of the received response to be able to incorporate cloud biometric technology for real time evidence processing. This position paper sets the mobile cloud computing agenda for biometric applications.

Fast iris detection via shape based circularity

We define an iris detection algorithm that performs an order of magnitude faster than the state of the art, while preserving accuracy. The algorithm isolates the pupil boundary by extracting image edges, then finding the largest contiguous set of points that satisfy the circularity criterion and contain mostly dark pixels. The iris/sclera boundary is found by horizontally and simultaneously searching along both directions of the pupil center for the highest cumulative difference in intensities. Current detection systems mainly rely on the methods proposed by [D] in order to isolate the iris pattern reliably, yet they are computationally expensive and expectedly slow. We apply a measure of circularity to isolate both the sclera and pupil boundaries, avoiding the exhaustive search required by [D]. Our method correctly identifies the iris region in 95% of test cases in the CASIA 3 dataset [CA]. While the detection rate is slightly lower compared to competitors, our method performs in O(n2) time compared to Ω(n3) that [D] offers. The iris detection procedure of [D], implemented in Matlab runs an average of roughly 15 seconds per image, while our own implementation in C++ on a single core 2.0 Ghz processor takes about 5 milliseconds on the same system, which is also faster than [HAK].

NDTC: A novel topology-based fingerprint matching algorithm using N-layer Delaunay triangulation net check

The problem of recognizing an individual using minutiae of fingerprints can be considered as a point matching problem. However, several factors such as the translation, rotation and deformation of the fingerprints as well as the presence of spurious minutiae and the absence of genuine minutiae, make it difficult to find correspondent minutia-pairs. In this paper, we proposed a novel topology-based fingerprint matching algorithm named N-layer Delaunay Triangulation Net Check (NDTC). This scheme fully utilizes the advantages of the special features of Delaunay triangulation net, e.g. local structural stability and global structural uniqueness, to tackle these problems, in order to provide reliable and robust minutiae matching. Our algorithm performance is evaluated on a public domain database FVC2002 DB2_A.

An exchanged folded hypercube-based topology structure for interconnection networks

This paper focuses on the topology structure of interconnection networks. To overcome drawbacks in the existing hypercube structure, we present an exchanged folded hypercube (EFH) structure, which is an improvement of the exchanged hypercube. Compared with the existing hypercube structures, EFH shows better performance in terms of many metrics such as smaller diameter, lower cost factor, and constant node degree. In this paper, we first introduce the structure of an EFH; then, we propose a routing algorithm and a load‐balancing algorithm for EFHs. Finally, we analyze the fault tolerance characteristics of EFHs including fault diameter and the cost effectiveness factor. Copyright

A Low Transmission Overhead Framework of Mobile Visual Search Based on Vocabulary Decomposition

Due to the bandwidth limitation in wireless networks, transmission overhead is a big problem in Mobile Visual Search (MVS). Existing work proposes transmitting the compressed local feature descriptors instead of the query image to reduce the transmission overhead. Although many kinds of compressed descriptors are proposed, designing a suitable lossless compressed descriptor has proven elusive. In this paper, we propose a novel framework for MVS with low transmission overhead rather than focusing on compressed descriptors. The key point of the proposed framework is to migrate the vector quantization in the bag of visual words model from the server to the client. In this framework, no matter what descriptors are used, the client only transmits the ID numbers of the visual words to the server, thereby reaching the minimal possible transmission overhead. To achieve this goal, we present vocabulary decomposition by which we can decompose the large vocabulary into several small ones satisfying storage constraints on mobile devices. In this paper, we first formulate vocabulary decomposition as an optimization problem. We then present Joint Product Quantization (JPQ) and Joint Optimized Product Quantization (JOPQ) to address the proposed optimization problem. Finally , we conduct a large number of simulation experiments and real experiments. The experimental results show that the proposed framework outperforms the existing framework by reducing more than 95% of the transmission overhead.