74 research outputs found
Deep Content: Unveiling video streaming content from encrypted WiFi Traffic
© 2018 IEEE. The proliferation of smart devices has led to an exponential growth in digital media consumption, especially mobile video for content marketing. The vast majority of the associated Internet traffic is now end-to-end encrypted, and while encryption provides better user privacy and security, it has made network surveillance an impossible task. The result is an unchecked environment for exploiters and attackers to distribute content such as fake, radical and propaganda videos. Recent advances in machine learning techniques have shown great promise in characterising encrypted traffic captured at the end points. However, video fingerprinting from passively listening to encrypted traffic, especially wireless traffic, has been reported as a challenging task due to the difficulty in distinguishing retransmissions and multiple flows on the same link. We show the potential of fingerprinting videos by passively sniffing WiFi frames in air, even without connecting to the WiFi network. We have developed Multi-Layer Perceptron (MLP) and Recurrent Neural Networks (RNNs) that are able to identify streamed YouTube videos from a closed set, by sniffing WiFi traffic encrypted at both Media Access Control (MAC) and Network layers. We compare these models to the state-of-the-art wired traffic classifier based on Convolutional Neural Networks (CNNs), and show that our models obtain similar results while requiring significantly less computational power and time (approximately a threefold reduction)
Dendrophthoe pentandra (L.) Miq extract effectively inhibits inflammation, proliferation and induces p53 expression on colitis-associated colon cancer
Background: Indonesian mistletoe grows on various trees. Mango Mistletoes (Dendrophthoe pentandra) is one type of mistletoe that grown on mango tree (.benalu mangga in bahasa Indonesia). Our study used mistletoe as a parasitic plant that has been used for traditional medicine. It has been known that Dendrophtoe pentandra extract (DPE) anti-inflammatory and anticancer. Furthermore, it is necessary to follow-up study in vivo to evaluate the response to treatment of new cancer therapeutic agents. This research aimed to determine the levels of IL-22, myeloperoxide (MPO), proliferation and wild-type p53 expression after the administration of DPE to murine models of CAC.
Methods: Mouse colitis associated colon cancer (CAC) was induced firstly by azoxymethane (AOM) and followed by administration of drinking water containing 5 % dextran sodium sulfate (DSS) in a cycle protocol, each cycle consisted of seven days of 5 % DSS in the drinking water and followed by seven days of regular water. This study consists of five treatment groups: I was treated water only (control), II was administrated by (DSS only, without DPE), (III-V) were administrated by DPE (125 mg/kg BW, 250 mg/kg BW and 500 mg/kg BW) respectively. The administrated of DPE were started from the 8th weeks, were continued until 21 weeks. At the end of 21 weeks of the experiment, mice were sacrificed, colon tissue was removed, and then subjected to ELISA, flow cytometry, real-time PCR and histology examination.
Results: Administration of DPE 250 mg/kgBW significantly reduce the levels of IL-22 and MPO compared with DSS only group (p < 0.001; p < 0.001). Colonic epithelial cells proliferation of group IV (DPE 250 mg/kgBW) were significantly lower than III and V groups. There was no significant change in the S phase in mice were treated DPE 125 mg/kg BW and 500 mg/kg BW, while administration of DPE 250 mg/kg BW was able to increase the percentage of cells in S phase. The expression of mRNA p53 was up regulated in mice received DPE 125 mg/kg BW.
Conclusion: These findings indicate that the DPE could inhibit colonic epithelial cells proliferation through p53 pathway independently. This study also showed that DPE could be potential sources of new therapy
Root-hair endophyte stacking in finger millet creates a physicochemical barrier to trap the fungal pathogen Fusarium graminearum
The ancient African crop, finger millet, has broad resistance to pathogens including the toxigenic fungus Fusarium graminearum. Here, we report the discovery of a novel plant defence mechanism resulting from an unusual symbiosis between finger millet and a root-inhabiting bacterial endophyte, M6 (Enterobacter sp.). Seed-coated M6 swarms towards root-invading Fusarium and is associated with the growth of root hairs, which then bend parallel to the root axis, subsequently forming biofilm-mediated microcolonies, resulting in a remarkable, multilayer root-hair endophyte stack (RHESt). The RHESt results in a physical barrier that prevents entry and/or traps F. graminearum, which is then killed. M6 thus creates its own specialized killing microhabitat. Tn5-mutagenesis shows that M6 killing requires c-di-GMP-dependent signalling, diverse fungicides and resistance to a Fusarium-derived antibiotic. Further molecular evidence suggests long-term host-endophyte-pathogen co-evolution. The end result of this remarkable symbiosis is reduced deoxynivalenol mycotoxin, potentially benefiting millions of subsistence farmers and livestock. Further results suggest that the anti-Fusarium activity of M6 may be transferable to maize and wheat. RHESt demonstrates the value of exploring ancient, orphan crop microbiomes
uStash: a Novel Mobile Content Delivery System for Improving User QoE in Public Transport
IEEE Mobile data traffic is growing exponentially and it is even more challenging to distribute content efficiently while users are "on the move" such as in public transport. The use of mobile devices for accessing content (e.g. videos) while commuting are both expensive and unreliable, although it is becoming common practice worldwide. Leveraging on the spatial and temporal correlation of content popularity and users' diverse network connectivity, we propose a novel content distribution system, uStash, which guarantees better QoE with regards to access delays and cost of usage. The proposed collaborative download and content stashing schemes provide the uStash provider the flexibility to control the cost of content access via cellular networks. We model the uStash system in a probabilistic framework and thereby analytically derive the optimal portions for collaborative downloading. Then, we validate the proposed models using real-life trace driven simulations. In particular, we use dataset from 22 inter-city buses running on 6 different routes and from a mobile VoD service provider to show that uStash reduces the cost of monthly cellular data by approximately 50% and the expected delay for content access by 60% compared to content downloaded via users' cellular network connections
Security and privacy approaches in mixed reality: A literature survey
Mixed reality (MR) technology development is now gaining momentum due to advances in computer vision, sensor fusion, and realistic display technologies. With most of the research and development focused on delivering the promise of MR, the privacy and security implications of this technology are yet to be thoroughly investigated. This survey article aims to put in to light these risks and to look into the latest security and privacy work on MR. Specifically, we list and review the different protection approaches that have been proposed to ensure user and data security and privacy in MR. We extend the scope to include work on related technologies such as augmented reality, virtual reality, and human-computer interaction as crucial components, if not the origins, of MR, as well as numerous related work from the larger area of mobile devices, wearables, and Internet-of-Things. We highlight the lack of investigation, implementation, and evaluation of data protection approaches in MR. Further challenges and directions on MR security and privacy are also discussed
Proceedings - Conference on Local Computer Networks, LCN
The smart devices usage is growing rapidly driven by innovative new smart wearables and service offerings. This has led to applications that utilize multiple devices around the body to provide immersive environments such as mixed reality that rely on a number of different types of functions and require considerable resources. Thus one of the major challenges in supporting these applications is dependent on the battery lifetime of devices that provide the necessary functionality. The focus of this paper is to improve the battery efficiency through intelligent resources utilization. We show that, when the same resource is available on multiple devices that form part of the wearable system, it is possible to consider them as a resource pool and further utilize them intelligently to improve the system lifetime via function virtualization. We formulate the intelligent function allocation algorithm as a Mixed Integer Linear Programming (MILP) optimization problem and propose an efficient heuristic solution. Next, we demonstrate the orchestration of the virtualized functions in order to achieve specific functionalities. The experimental data driven simulation results show that approximately 40-50% system battery life improvement can be achieved with proper function allocation and orchestration
Proceedings - Conference on Local Computer Networks, LCN
Mobile vision technologies have paved the way for augmented (AR) and mixed reality (MR) applications to be realizable on mobile devices. Mobile platforms such as Android and iOS have recently demonstrated the early opportunities for AR/MR applications using their devices. Now, while these technologies can still be considered in its infancy, it is opportune to start thinking about privacy and security while their functionalities are slowly being revealed to us. In this work, we present a visual access control mechanism in the form of object-level abstraction. Using readily-available object detection algorithms, we are able to demonstrate a proof-of-concept object-level abstraction for fine-grained access control in a mobile device. Furthermore, aside from the inherent confidentiality and content awareness guarantee of abstraction, reduction in execution times from visual processing resource sharing is another consequential benefit of abstraction without any energy consumption impact
2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)
Content sharing and online collaboration have become extremely popular in recent years, in particular with the pervasiveness of cloud storage services such as Dropbox. However, these popular cloud services are not accessible when users are offline and do not take the geographical location of the users into account when distributing content. Despite years of research in opportunistic content dissemination, real users are yet to fully experience the advantages of content sharing in proximity. To this end, we propose uDrop which literally pushes the cloud storage services to the edge of the network whenever interested users are in proximity of each other. uDrop enables content sharing among users in the vicinity without relying on networking infrastructure while improving the user quality of experience and reducing the cost of bandwidth. In this demonstration, we show the practical feasibility of uDrop service on Android smartphones
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