We propose new construction methods of secret sharing schemes realizing general access structures. Our proposed construction methods are perfect secret sharing schemes and include Shamir's (k, n)-threshold schemes as a special case. Furthermore, except for some access structures for which the efficiency is the same as the previous ones, the proposed construction methods are more efficient than Benaloh and Leichter's scheme and the scheme I of TUM05.
This paper gives a first security evaluation of a lightweight stream cipher RAKAPOSHI. In particular, we analyze a slide property of RAKAPOSHI such that two different Key-IV pairs generate the same keystream but n-bit shifted. To begin with, we demonstrate that any Key-IV pair has a corresponding slide Key-IV pair that generates an n-bit shifted keystream with a probability of 2-2n. In order to experimentally support our results, some examples of such pairs are given. Then, we show that this property is able to be converted into key recovery attacks on RAKAPOSHI. In the related-key setting, our attack based on the slide property can recover a 128-bit key with a time complexity of 241 and 238 chosen IVs. Moreover, by using a variant of slide property called partial slide pair, this attack is further improved, and then a 128-bit key can be recovered with a time complexity of 233 and 230 chosen IVs. Finally, we present a method for speeding up the brute force attack by a factor of 2 in the single key setting.
This paper aims to detect features of coordinated attacks by applying data mining techniques, namely Apriori with PrefixSpan, to the CCC DATAset 2008-2010, which comprises captured packet data and downloading logs. Data mining algorithms enable us to automate the detection of characteristics in large amounts of data, which conventional heuristics cannot deal with. Apriori achieves a high recall but with false positives, whereas PrefixSpan has high precision but low recall. We therefore propose a hybrid of these two algorithms. Our analysis shows a change in the behavior of malware over the past three years.
This paper proposes a new privacy-preserving recommendation method classified into a randomized perturbation scheme in which a user adds a random noise to the original rating value and a server provides a disguised data to allow users to predict the rating value for unseen items. The proposed scheme performs a perturbation in a randomized response scheme, which preserves a higher degree of privacy than that of an additive perturbation. To address the accuracy reduction of the randomized response, the proposed scheme uses a posterior probability distribution function, derived from Bayes' estimation for the reconstruction of the original distribution, to revise the similarity between items computed from the disguised matrix. A simple experiment shows the accuracy improvement of the proposed scheme.
ISO/IEC TR 19791 is an international standard that must be used as the basis for the security evaluation of operational systems. This standard has been recently developed, and the first version was made available in May 2006. ISO/IEC TR 19791 is intended to be an extension of ISO/IEC 15408, known as “Common Criteria” (CC). In order to evaluate an IT product or system using CC or ISO/IEC TR 19791, developers must create a Security Target (ST), or a System Security Target (SST). However, a problem encountered in creating these is the determination of the Security Problem Definitions (SPDs), because the SPDs fall outside of the scope of CC. Neither ISO/IEC 15408 nor ISO/IEC TR 19791 provides a framework for risk analysis or the specification of threats. In this paper, we propose a threat model based on multiple international standards and evaluated ST information, and describe a Web application that can be used for security specifications in the production of STs and SSTs which are to be evaluated by CC and ISO/IEC TR 19791, respectively.
Gaining complete understanding of the active services and open communication paths is often difficult because of the rapidly expanding complexity of those services and their wide-ranging functions. Furthermore, the IT administrators of hand-designed systems often lack ways to identify and close unnecessary services and communication pathways. In this paper, firstly we propose an automated approach to discover all active services and the permitted communications paths in networked system. Secondly, we propose a method to detect all unexpected services and communication paths in networked system for IT system administrators. We then show how hand-designed networked systems containing such devices are prone to contain numerous unnecessary active services and communication paths, which are exploited by malicious actions such a service denial, information theft, and/or cyber espionage. The evaluation result shows the effectiveness of our proposed approach.
We consider the transmission of confidential data over a wireless quasi-static fading wiretap channel when the main and eavesdropper channels are correlated there. Under the assumption that before transmission the transmitter only knows the channel state information (CSI) of the main channel but has no idea about the CSI of the eavesdropper channel, we derive the asymptotic outage probability and also asymptotic outage secrecy capacity as the transmission power goes to infinity, which cover the corresponding results when the main and eavesdropper channels are independent as special cases. Based on the theoretical results, the effects of channel correlation on the asymptotic outage probability and asymptotic outage secrecy capacity are explored. Remarkably, our results reveal that the correlation between the main and eavesdropper channels has a significant impact on both the asymptotic outage probability and asymptotic outage secrecy capacity and that such an impact can be helpful or harmful depending on the relative channel condition between the main and eavesdropper channels.
Some recent researches have shown that using a monitoring service outside the target system above hypervisors is an efficient way to protect the target system. The hypervisors isolate the monitoring service based on MMU-methods to improve security. However, The MMU-method may cause heavy overhead when there is no hardware support, which makes this method not viable for embedded processors that are rarely equipped with hardware virtualization extensions. In addition, the vulnerabilities that exist in hypervisors may compromise the isolation. In this paper, we propose a secure OS architecture that fits embedded systems without the dependency of a hypervisor. It provides a robust isolation between the monitoring service and the guest OS based on local memory, a hardware feature. In order to generalize this architecture, we adopt a secure pager to extend the local memory space (physically small) virtually by a swap mechanism with integrity checking of the monitoring service. The secure pager can also update the monitoring service to extend monitoring functions without disturbing the running of the guest OS. Comprehensive evaluations are made in our framework with one instance of embedded Linux as the guest OS and an isolated monitoring service running with the secure pager. The results demonstrate functions of the secure pager and influence of the secure pager on Linux in our system. On processors with a proper architecture, we can build an extensible secure OS architecture with reasonable resource consumption, without the issue of heavy overhead to the guest OS.
A rectangular drawing is a partition of a rectangle into a set of rectangles. Rectangular drawings have many important applications including VLSI layout. Since the size of rectangular drawings may be huge, compact encodings are desired. Several compact encodings of rectangular drawings without degree four vertices are known. In this paper, we design two compact encodings for rectangular drawings with degree four vertices. We give 5f - B - n4 bits and 5f - B - W - 3 bits encodings for rectangular drawings, where f is the number of inner faces, n4 is the number of vertices with degree four, and B (resp. W) is the number of inner faces touching the bottommost horizontal (resp. rightmost vertical) line segments.
In this paper, we propose a novel sensor data collection method using an overlay network that forwards collection request messages to the sensor nodes which have sensor data needed to create interpolated contour lines maps. When there is an enormous number of sensor nodes, it is redundant to collect all sensor data from a target area since geographically close sensor data can be interpolated. Moreover, since the interpolation process requires heavy CPU load, the process may not be finished within a reasonable time period if too much sensor data arrived. On the other hand, there is a trade-off between the number of collected sensor data and the accuracy of the created contour lines map. In our proposed method, the number of collected sensor data can be limited to a constant number. At the same time, granularity of characteristic points in the contour lines maps can be specified by users in order to satisfy the various requirements. Our proposed method extends the hierarchical Delaunay overlay network (HDOV) and forwards the collection request messages according to the feature amounts that correspond to the characteristic points for each layer of the HDOV. Simulation results showed that our proposed method could create contour lines maps while satisfying the requested granularity of the characteristic points within the constant number of sensor data.
This paper presents an accurate method for computing the surface velocity which is used to advect the vertex in mesh-based surface tracking. We propose a curvature invariance condition that accurately captures the movement of a surface, especially in the case of rotating objects. The method uses the least-squares method and mesh fairing to solve the problem that the surface velocity would not be calculated when the implicit function defining the surface does not change. We show that the method works well in scenes including rotation and deformation.