Biblio
The paper presents a secure solution that provides VoIP service for mobile users, handling both pre-call and mid-call mobility. Pre-call mobility is implemented using a presence server that acts as a DNS for the moving users. Our approach also detects any change in the attachment point of the moving users and transmits it to the peer entity by in band signaling using socket communications. For true mid-call mobility we also employ buffering techniques that store packets for the duration of the signaling procedure. The solution was implemented for Android devices and it uses ASP technology for the server part.
Blind Source Separation (BSS) deals with the recovery of source signals from a set of observed mixtures, when little or no knowledge of the mixing process is available. BSS can find an application in the context of network coding, where relaying linear combinations of packets maximizes the throughput and increases the loss immunity. By relieving the nodes from the need to send the combination coefficients, the overhead cost is largely reduced. However, the scaling ambiguity of the technique and the quasi-uniformity of compressed media sources makes it unfit, at its present state, for multimedia transmission. In order to open new practical applications for BSS in the context of multimedia transmission, we have recently proposed to use a non-linear encoding to increase the discriminating power of the classical entropy-based separation methods. Here, we propose to append to each source a non-linear message digest, which offers an overhead smaller than a per-symbol encoding and that can be more easily tuned. Our results prove that our algorithm is able to provide high decoding rates for different media types such as image, audio, and video, when the transmitted messages are less than 1.5 kilobytes, which is typically the case in a realistic transmission scenario.
Mobile social networks (MSNs) facilitate connections between mobile users and allow them to find other potential users who have similar interests through mobile devices, communicate with them, and benefit from their information. As MSNs are distributed public virtual social spaces, the available information may not be trustworthy to all. Therefore, mobile users are often at risk since they may not have any prior knowledge about others who are socially connected. To address this problem, trust inference plays a critical role for establishing social links between mobile users in MSNs. Taking into account the nonsemantical representation of trust between users of the existing trust models in social networks, this paper proposes a new fuzzy inference mechanism, namely MobiFuzzyTrust, for inferring trust semantically from one mobile user to another that may not be directly connected in the trust graph of MSNs. First, a mobile context including an intersection of prestige of users, location, time, and social context is constructed. Second, a mobile context aware trust model is devised to evaluate the trust value between two mobile users efficiently. Finally, the fuzzy linguistic technique is used to express the trust between two mobile users and enhance the human's understanding of trust. Real-world mobile dataset is adopted to evaluate the performance of the MobiFuzzyTrust inference mechanism. The experimental results demonstrate that MobiFuzzyTrust can efficiently infer trust with a high precision.
As the cornerstone of the future intelligent transportation system, vehicular ad hoc networks (VANETs) have attracted intensive attention from the academic and industrial research communities in recent years. For widespread deployment of VANETs, security and privacy issues must be addressed properly. In this paper, we introduce the notion of pseudonym-based cryptography, and present a provable secure pseudonym-based cryptosystems with a trusted authority that includes a pseudonym-based multi-receiver encryption scheme, a pseudonym-based signature scheme, and a pseudonym-based key establishment protocol. We then propose a secure and efficient data access scheme for VANETs based on cooperative caching technology and our proposed pseudonym-based cryptosystems. On the one hand, the efficiency of data access are greatly improved by allowing the sharing and coordination of cached data among multiple vehicles. On the other hand, anonymity of the vehicles, data confidentiality, integrity and non-repudiation are guaranteed by employing our proposed pseudonym-based cryptosystems. Simulation results have shown that our proposed pseudonym-based cryptosystems are suitable to the VANETs environment.
Care of chronic cardiac patients requires information interchange between patients' homes, clinical environments, and the electronic health record. Standards are emerging to support clinical information collection, exchange and management and to overcome information fragmentation and actors delocalization. Heterogeneity of information sources at patients' homes calls for open solutions to collect and accommodate multidomain information, including environmental data. Based on the experience gained in a European Research Program, this paper presents an integrated and open approach for clinical data interchange in cardiac telemonitoring applications. This interchange is supported by the use of standards following the indications provided by the national authorities of the countries involved. Taking into account the requirements provided by the medical staff involved in the project, the authors designed and implemented a prototypal middleware, based on a service-oriented architecture approach, to give a structured and robust tool to congestive heart failure patients for their personalized telemonitoring. The middleware is represented by a health record management service, whose interface is compliant to the healthcare services specification project Retrieve, Locate and Update Service standard (Level 0), which allows communication between the agents involved through the exchange of Clinical Document Architecture Release 2 documents. Three performance tests were carried out and showed that the prototype completely fulfilled all requirements indicated by the medical staff; however, certain aspects, such as authentication, security and scalability, should be deeply analyzed within a future engineering phase.
We propose a resilience architecture for improving the security and dependability of authentication and authorization infrastructures, in particular the ones based on RADIUS and OpenID. This architecture employs intrusion-tolerant replication, trusted components and entrusted gateways to provide survivable services ensuring compatibility with standard protocols. The architecture was instantiated in two prototypes, one implementing RADIUS and another implementing OpenID. These prototypes were evaluated in fault-free executions, under faults, under attack, and in diverse computing environments. The results show that, beyond being more secure and dependable, our prototypes are capable of achieving the performance requirements of enterprise environments, such as IT infrastructures with more than 400k users.
Electric vehicle is the automobile that powered by electrical energy stored in batteries. Due to the frequent recharging, vehicles need to be connected to the recharging infrastructure while they are parked. This may disclose drivers' privacy, such as their location that drivers may want to keep secret. In this paper, we propose a scheme to enhance the privacy of the drivers using anonymous credential technique and Trusted Platform Module(TPM). We use anonymous credential technique to achieve the anonymity of vehicles such that drivers can anonymously and unlinkably recharge their vehicles. We add some attributes to the credential such as the type of the battery in the vehicle in case that the prices of different batteries are different. We use TPM to omit a blacklist such that the company that offer the recharging service(Energy Provider Company, EPC) does not need to conduct a double spending detection.
This paper reports the results and findings of a historical analysis of open source intelligence (OSINT) information (namely Twitter data) surrounding the events of the September 11, 2012 attack on the US Diplomatic mission in Benghazi, Libya. In addition to this historical analysis, two prototype capabilities were combined for a table top exercise to explore the effectiveness of using OSINT combined with a context aware handheld situational awareness framework and application to better inform potential responders as the events unfolded. Our experience shows that the ability to model sentiment, trends, and monitor keywords in streaming social media, coupled with the ability to share that information to edge operators can increase their ability to effectively respond to contingency operations as they unfold.
Mobile and aerial robots used in urban search and rescue (USAR) operations have shown the potential for allowing us to explore, survey and assess collapsed structures effectively at a safe distance. RGB-D cameras, such as the Microsoft Kinect, allow us to capture 3D depth data in addition to RGB images, providing a significantly richer user experience than flat video, which may provide improved situational awareness for first responders. However, the richer data comes at a higher cost in terms of data throughput and computing power requirements. In this paper we consider the problem of live streaming RGB-D data over wired and wireless communication channels, using low-power, embedded computing equipment. When assessing a disaster environment, a range camera is typically mounted on a ground or aerial robot along with the onboard computer system. Ground robots can use both wireless radio and tethers for communications, whereas aerial robots can only use wireless communication. We propose a hybrid lossless and lossy streaming compression format designed specifically for RGB-D data and investigate the feasibility and usefulness of live-streaming this data in disaster situations.
Traffic from mobile wireless networks has been growing at a fast pace in recent years and is expected to surpass wired traffic very soon. Service providers face significant challenges at such scales including providing seamless mobility, efficient data delivery, security, and provisioning capacity at the wireless edge. In the Mobility First project, we have been exploring clean slate enhancements to the network protocols that can inherently provide support for at-scale mobility and trustworthiness in the Internet. An extensible data plane using pluggable compute-layer services is a key component of this architecture. We believe these extensions can be used to implement in-network services to enhance mobile end-user experience by either off-loading work and/or traffic from mobile devices, or by enabling en-route service-adaptation through context-awareness (e.g., Knowing contemporary access bandwidth). In this work we present details of the architectural support for in-network services within Mobility First, and propose protocol and service-API extensions to flexibly address these pluggable services from end-points. As a demonstrative example, we implement an in network service that does rate adaptation when delivering video streams to mobile devices that experience variable connection quality. We present details of our deployment and evaluation of the non-IP protocols along with compute-layer extensions on the GENI test bed, where we used a set of programmable nodes across 7 distributed sites to configure a Mobility First network with hosts, routers, and in-network compute services.
An identity authentication scheme is proposed combining with biometric encryption, public key cryptography of homomorphism and predicate encryption technology under the cloud computing environment. Identity authentication scheme is proposed based on the voice and homomorphism technology. The scheme is divided into four stages, register and training template stage, voice login and authentication stage, authorization stage, and audit stage. The results prove the scheme has certain advantages in four aspects.
In an attempt to support customization, many web applications allow the integration of third-party server-side plugins that offer diverse functionality, but also open an additional door for security vulnerabilities. In this paper we study the use of static code analysis tools to detect vulnerabilities in the plugins of the web application. The goal is twofold: 1) to study the effectiveness of static analysis on the detection of web application plugin vulnerabilities, and 2) to understand the potential impact of those plugins in the security of the core web application. We use two static code analyzers to evaluate a large number of plugins for a widely used Content Manage-ment System. Results show that many plugins that are current-ly deployed worldwide have dangerous Cross Site Scripting and SQL Injection vulnerabilities that can be easily exploited, and that even widely used static analysis tools may present disappointing vulnerability coverage and false positive rates.
The aim of this study is to examine the utility of physiological compliance (PC) to understand shared experience in a multiuser technological environment involving active and passive users. Common ground is critical for effective collaboration and important for multiuser technological systems that include passive users since this kind of user typically does not have control over the technology being used. An experiment was conducted with 48 participants who worked in two-person groups in a multitask environment under varied task and technology conditions. Indicators of PC were measured from participants' cardiovascular and electrodermal activities. The relationship between these PC indicators and collaboration outcomes, such as performance and subjective perception of the system, was explored. Results indicate that PC is related to group performance after controlling for task/technology conditions. PC is also correlated with shared perceptions of trust in technology among group members. PC is a useful tool for monitoring group processes and, thus, can be valuable for the design of collaborative systems. This study has implications for understanding effective collaboration.
Complexity is ever increasing within our information environment and organisations, as interdependent dynamic relationships within sociotechnical systems result in high variety and uncertainty from a lack of information or control. A net-centric approach is a strategy to improve information value, to enable stakeholders to extend their reach to additional data sources, share Situational Awareness (SA), synchronise effort and optimise resource use to deliver maximum (or proportionate) effect in support of goals. This paper takes a systems perspective to understand the dynamics within a net-centric information system. This paper presents the first stages of the Soft Systems Methodology (SSM), to develop a conceptual model of the human activity system and develop a system dynamics model to represent system behaviour, that will inform future research into a net-centric approach with information security. Our model supports the net-centric hypothesis that participation within a information sharing community extends information reach, improves organisation SA allowing proactive action to mitigate vulnerabilities and reduce overall risk within the community. The system dynamics model provides organisations with tools to better understand the value of a net-centric approach, a framework to determine their own maturity and evaluate strategic relationships with collaborative communities.
This paper presents a unified approach for the detection of network anomalies. Current state of the art methods are often able to detect one class of anomalies at the cost of others. Our approach is based on using a Linear Dynamical System (LDS) to model network traffic. An LDS is equivalent to Hidden Markov Model (HMM) for continuous-valued data and can be computed using incremental methods to manage high-throughput (volume) and velocity that characterizes Big Data. Detailed experiments on synthetic and real network traces shows a significant improvement in detection capability over competing approaches. In the process we also address the issue of robustness of network anomaly detection systems in a principled fashion.
Conventional photoacoustic microscopy (PAM) involves detection of optically induced thermo-elastic waves using ultrasound transducers. This approach requires acoustic coupling and the spatial resolution is limited by the focusing properties of the transducer. We present an all-optical PAM approach that involved detection of the photoacoustically induced surface displacements using an adaptive, two-wave mixing interferometer. The interferometer consisted of a 532-nm, CW laser and a Bismuth Silicon Oxide photorefractive crystal (PRC) that was 5×5×5 mm3. The laser beam was expanded to 3 mm and split into two paths, a reference beam that passed directly through the PRC and a signal beam that was focused at the surface through a 100-X, infinity-corrected objective and returned to the PRC. The PRC matched the wave front of the reference beam to that of the signal beam for optimal interference. The interference of the two beams produced optical-intensity modulations that were correlated with surface displacements. A GHz-bandwidth photoreceiver, a low-noise 20-dB amplifier, and a 12-bit digitizer were employed for time-resolved detection of the surface-displacement signals. In combination with a 5-ns, 532-nm pump laser, the interferometric probe was employed for imaging ink patterns, such as a fingerprint, on a glass slide. The signal beam was focused at a reflective cover slip that was separated from the fingerprint by 5 mm of acoustic-coupling gel. A 3×5 mm2 area of the coverslip was raster scanned with 100-μm steps and surface-displacement signals at each location were averaged 20 times. Image reconstruction based on time reversal of the PA-induced displacement signals produced the photoacoustic image of the ink patterns. The reconstructed image of the fingerprint was consistent with its photograph, which demonstrated the ability of our system to resolve micron-scaled features at a depth of 5 mm.
We consider the problem of designing (or augmenting) an electric power system at a minimum cost such that it satisfies the N-k-ε survivability criterion. This survivability criterion is a generalization of the well-known N-k criterion, and it requires that at least (1-εj) fraction of the steady-state demand be met after failures of j components, for j=0,1,...,k. The network design problem adds another level of complexity to the notoriously hard contingency analysis problem, since the contingency analysis is only one of the requirements for the design optimization problem. We present a mixed-integer programming formulation of this problem that takes into account both transmission and generation expansion. We propose an algorithm that can avoid combinatorial explosion in the number of contingencies, by seeking vulnerabilities in intermediary solutions and constraining the design space accordingly. Our approach is built on our ability to identify such system vulnerabilities quickly. Our empirical studies on modified instances of the IEEE 30-bus and IEEE 57-bus systems show the effectiveness of our methods. We were able to solve the transmission and generation expansion problems for k=4 in approximately 30 min, while other approaches failed to provide a solution at the end of 2 h.
Cryptographically-Curated File System (CCFS) proposed in this work supports the adoption of Information-Centric Networking. CCFS utilizes content names that span trust boundaries, verify integrity, tolerate disruption, authenticate content, and provide non-repudiation. Irrespective of the ability to reach an authoritative host, CCFS provides secure access by binding a chain of trust into the content name itself. Curators cryptographically bind content to a name, which is a path through a series of objects that map human meaningful names to cryptographically strong content identifiers. CCFS serves as a network layer for storage systems unifying currently disparate storage technologies. The power of CCFS derives from file hashes and public keys used as a name with which to retrieve content and as a method of verifying that content. We present results from our prototype implementation. Our results show that the overhead associated with CCFS is not negligible, but also is not prohibitive.
Power grids are monitored by gathering data through remote sensors and estimating the state of the grid. Bad data detection schemes detect and remove poor data. False data is a special type of data injection designed to evade typical bad data detection schemes and compromise state estimates, possibly leading to improper control of the grid. Topology perturbation is a situational awareness method that implements the use of distributed flexible AC transmission system devices to alter impedance on optimally chosen lines, updating the grid topology and exposing the presence of false data. The success of the topology perturbation for improving grid control and exposing false data in AC state estimation is demonstrated. A technique is developed for identifying the false data injection attack vector and quantifying the compromised measurements. The proposed method provides successful false data detection and identification in IEEE 14, 24, and 39-bus test systems using AC state estimation.
Techniques for network security analysis have historically focused on the actions of the network hosts. Outside of forensic analysis, little has been done to detect or predict malicious or infected nodes strictly based on their association with other known malicious nodes. This methodology is highly prevalent in the graph analytics world, however, and is referred to as community detection. In this paper, we present a method for detecting malicious and infected nodes on both monitored networks and the external Internet. We leverage prior community detection and graphical modeling work by propagating threat probabilities across network nodes, given an initial set of known malicious nodes. We enhance prior work by employing constraints that remove the adverse effect of cyclic propagation that is a byproduct of current methods. We demonstrate the effectiveness of probabilistic threat propagation on the tasks of detecting botnets and malicious web destinations.
With the advent of social networks and cloud computing, the amount of multimedia data produced and communicated within social networks is rapidly increasing. In the mean time, social networking platform based on cloud computing has made multimedia big data sharing in social network easier and more efficient. The growth of social multimedia, as demonstrated by social networking sites such as Facebook and YouTube, combined with advances in multimedia content analysis, underscores potential risks for malicious use such as illegal copying, piracy, plagiarism, and misappropriation. Therefore, secure multimedia sharing and traitor tracing issues have become critical and urgent in social network. In this paper, we propose a scheme for implementing the Tree-Structured Harr (TSH) transform in a homomorphic encrypted domain for fingerprinting using social network analysis with the purpose of protecting media distribution in social networks. The motivation is to map hierarchical community structure of social network into tree structure of TSH transform for JPEG2000 coding, encryption and fingerprinting. Firstly, the fingerprint code is produced using social network analysis. Secondly, the encrypted content is decomposed by the TSH transform. Thirdly, the content is fingerprinted in the TSH transform domain. At last, the encrypted and fingerprinted contents are delivered to users via hybrid multicast-unicast. The use of fingerprinting along with encryption can provide a double-layer of protection to media sharing in social networks. Theory analysis and experimental results show the effectiveness of the proposed scheme.