Live video programs can bring in better travel experience for subway passengers and earn abundant advertisement revenue for subway operators. However, because the train-trackside channels for video dissemination are easily accessible to anyone, the video traffic are vulnerable to attacks, which may cause deadly tragedies. This paper presents a situation-aware authenticated video broadcasting scheme in the railway network, which consists of train, on-board sensor, trackside global system for mobile communications-railway (GSM-R) device, WiFi access point (AP), and train control center. Specifically, the scheme has four modules: 1) a train uses its on-board sensors to obtain its speed, location, and received signal strength indicator of train-trackside WiFi channel; 2) the train reports these real-time measurements to the railway control center with the legacy GSM-R networks; 3) according to the measurements, the control center or its WiFi AP adaptively customizes the protected codestream bitrate and AP-train handover time; and 4) the train renders the received codestream, which passes the authenticity verification process. As shown in the performance analysis, the present scheme ensures the codestream authenticity and provides high quality of service in the lossy subway WiFi environment.

GSM-R is an important transport communication system to realize moving block control so as to maximize the transfer capacity. However, if the GSM-R system is compromised, the transport system has to downgrade to fixed block control which is of low capacity. This paper presents secure train-to-train communication schemes which enable moving block control even if the GSM-R system is under attack. Particularly, it elaborates two key management protocols to build secure channels between two adjacent trains. One is to setup an autonomous secure train-to-train channel with asymmetric cryptographic primitives and another is to provide secure quasi-autonomous train-to-train channel with symmetric cryptographic primitives. Both schemes are lightweight in terms of computation and communication overhead. In addition, the present scheme is compatible with the terrestrial transportation communication systems.

H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and integrity of received SVC codestreams, engineers and researchers have proposed several authentication schemes to protect video data. However, existing algorithms cannot simultaneously satisfy both efficiency and robustness for SVC surveillance codestreams. Hence, in this article, a highly efficient and robust authentication scheme, named TrustSSV (Trust Scalable Surveillance Video), is proposed. Based on quality/spatial scalable characteristics of SVC codestreams, TrustSSV combines cryptographic and content-based authentication techniques to authenticate the base layer and enhancement layers, respectively. Based on temporal scalable characteristics of surveillance codestreams, TrustSSV extracts, updates, and authenticates foreground features for each access unit dynamically with background model support. Using SVC test sequences, our experimental results indicate that the scheme is able to distinguish between content-preserving and content-changing manipulations and to pinpoint tampered locations. Compared with existing schemes, the proposed scheme incurs very small computation and communication costs.

Content-based authentication (CBA) schemes are used to authenticate multimedia streams while allowing content-preserving manipulations such as bit-rate transcoding. In this paper, we survey and classify existing transform-domain CBA schemes for videos into two categories, and point out that in contrary to CBA for images, there exists a common design flaw in these schemes. We present the principles (based on video coding concept) on how the flaw can be exploited to mount semantic-changing attacks in the transform domain that cannot be detected by existing CBA schemes. We show attack examples including content removal, modification and insertion attacks. Noting that these CBA schemes are designed at the macroblock level, we discuss, from the attacker’s point of view, the conditions in attacking content-based authenticated macroblocks.

Accident detection and alarm system is very important to detect possible accidents or dangers for the peoples using their mobile devices while walking, i.e., distracted walking. In this paper, we introduce an automatic accident detection and alarm system, called AutoADAS, which is fully implemented and tested on the real mobile devices. The proposed system can be activated either manually or automatically when user walks. Under the manual mode, user activates the system before distracted walking while under the automatic mode, a "user behaviour profiling" module is used to recognize (distracted) walking behaviours and an "object detection" module is activated. Using image processing and camera field of view (FOV), the distance and angle between the user and detected objects are estimated and then applied to identify whether any potential accidents can happen. The "accident analysis and prediction" module includes: temporal alarm that inputs the user's walking speed and distance with respect to the detected objects and outputs temporal accident prediction; spatial alarm that inputs the user's walking direction and angle with respect to the detected objects and outputs spatial accident prediction. Once the proposed system positively predicts a potential accident, the "alarm and suggestion" module alerts the user with text, sound or vibration.

A scalable video coding (SVC) codestream consists of one base layer and possibly several enhancement layers. The base layer, which contains the lowest quality and resolution images, is the foundation of the SVC codestream and must be delivered to recipients, whereas enhancement layers contain richer contour/texture of images in order to supplement the base layer in resolution, quality, and temporal scalabilities. This paper presents a novel hybrid authentication (HAU) scheme. The HAU employs both cryptographic authentication and content-based authentication techniques to ensure integrity and authenticity of the SVC codestreams. Our analysis and experimental results indicate that the HAU is able to detect malicious manipulations and locate the tampered image regions while is robust to content-preserving manipulations for enhancement layers. Although our focus in this paper is on authenticating H.264/SVC codestreams, the proposed technique is also applicable to authenticate other scalable multimedia contents such as MPEG-4 fine grain scalability and JPEG2000 codestreams.

This paper presents a novel Multi-message Ciphertext Policy Attribute-Based Encryption (MCP-ABE) technique, and employs the MCP-ABE to design an access control scheme for sharing scalable media based on data consumers' attributes (e.g., age, nationality, or gender) rather than an explicit list of the consumers' names. The scheme is efficient and flexible because MCP-ABE allows a content provider to specify an access policy and encrypt multiple messages within one ciphertext such that only the users whose attributes satisfy the access policy can decrypt the ciphertext. Moreover, the paper shows how to support resource-limited mobile devices by offloading computational intensive operations to cloud servers while without compromising data privacy.

A real-time obstacle detection system with vision sensors has been developed for Unmanned Surface Vehicle (USV). The system enables the detection and localization of multiple obstacles in the range from 30 to 300 meters on the sea surface. Field tests have proven the performance and reliability of the system to be satisfactory. This paper focuses on the improvement made in the real-time obstacle detection system during the last year.