Biblio
In recent decades, a significant research effort has been devoted to the development of forensic tools for retrieving information and detecting possible tampering of multimedia documents. A number of counter-forensic tools have been developed as well in order to impede a correct analysis. Such tools are often very effective due to the vulnerability of multimedia forensics tools, which are not designed to work in an adversarial environment. In this scenario, developing forensic techniques capable of granting good performance even in the presence of an adversary aiming at impeding the forensic analysis, is becoming a necessity. This turns out to be a difficult task, given the weakness of the traces the forensic analysis usually relies on. The goal of this paper is to provide an overview of the advances made over the last decade in the field of adversarial multimedia forensics. We first consider the view points of the forensic analyst and the attacker independently, then we review some of the attempts made to simultaneously take into account both perspectives by resorting to game theory. Eventually, we discuss the hottest open problems and outline possible paths for future research.
As the traffic congestion increases on the transport network, Payable on the road to slower speeds, longer falter times, as a consequence bigger vehicular queuing, it's necessary to introduce smart way to reduce traffic. We are already edging closer to ``smart city-smart travel''. Today, a large number of smart phone applications and connected sat-naves will help get you to your destination in the quickest and easiest manner possible due to real-time data and communication from a host of sources. In present situation, traffic lights are used in each phase. The other way is to use electronic sensors and magnetic coils that detect the congestion frequency and monitor traffic, but found to be more expensive. Hence we propose a traffic control system using image processing techniques like edge detection. The vehicles will be detected using images instead of sensors. The cameras are installed alongside of the road and it will capture image sequence for every 40 seconds. The digital image processing techniques will be applied to analyse and process the image and according to that the traffic signal lights will be controlled.
As drone attracts much interest, the drone industry has opened their market to ordinary people, making drones to be used in daily lives. However, as it got easier for drone to be used by more people, safety and security issues have raised as accidents are much more likely to happen: colliding into people by losing control or invading secured properties. For safety purposes, it is essential for observers and drone to be aware of an approaching drone. In this paper, we introduce a comprehensive drone detection system based on machine learning. This system is designed to be operable on drones with camera. Based on the camera images, the system deduces location on image and vendor model of drone based on machine classification. The system is actually built with OpenCV library. We collected drone imagery and information for learning process. The system's output shows about 89 percent accuracy.
An air-gapped network is a type of IT network that is separated from the Internet - physically - due to the sensitive information it stores. Even if such a network is compromised with a malware, the hermetic isolation from the Internet prevents an attacker from leaking out any data - thanks to the lack of connectivity. In this paper we show how attackers can covertly leak sensitive data from air-gapped networks via the row of status LEDs on networking equipment such as LAN switches and routers. Although it is known that some network equipment emanates optical signals correlated with the information being processed by the device (‘side-channel'), malware controlling the status LEDs to carry any type of data (‘covert-channel') has never studied before. Sensitive data can be covertly encoded over the blinking of the LEDs and received by remote cameras and optical sensors. A malicious code is executed in a compromised LAN switch or router allowing the attacker direct, low-level control of the LEDs. We provide the technical background on the internal architecture of switches and routers at both the hardware and software level which enables these attacks. We present different modulation and encoding schemas, along with a transmission protocol. We implement prototypes of the malware and discuss its design and implementation. We tested various receivers including remote cameras, security cameras, smartphone cameras, and optical sensors, and discuss detection and prevention countermeasures. Our experiments show that sensitive data can be covertly leaked via the status LEDs of switches and routers at bit rates of 1 bit/sec to more than 2000 bit/sec per LED.
Air-gap data is important for the security of computer systems. The injection of the computer virus is limited but possible, however data communication channel is necessary for the transmission of stolen data. This paper considers BFSK digital modulation applied to brightness changes of screen for unidirectional transmission of valuable data. Experimental validation and limitations of the proposed technique are provided.
Visible light communications is an emerging architecture with unlicensed and huge bandwidth resources, security, and experimental implementations and standardization efforts. Display based transmitter and camera based receiver architectures are alternatives for device-to-device (D2D) and home area networking (HAN) systems by utilizing widely available TV, tablet and mobile phone screens as transmitters while commercially available cameras as receivers. Current architectures utilizing data hiding and unobtrusive steganography methods promise data transmission without user distraction on the screen. however, current architectures have challenges with the limited capability of data hiding in translucency or color shift based methods of hiding by uniformly distributing modulation throughout the screen and keeping eye discomfort at an acceptable level. In this article, foveation property of human visual system is utilized to define a novel modulation method denoted by FoVLC which adaptively improves data hiding capability throughout the screen based on the current eye focus point of viewer. Theoretical modeling of modulation and demodulation mechanisms hiding data in color shifts of pixel blocks is provided while experiments are performed for both FoVLC method and uniform data hiding denoted as conventional method. Experimental tests for the simple design as a proof of concept decreases average bit error rate (BER) to approximately half of the value obtained with the conventional method without user distraction while promising future efforts for optimizing block sizes and utilizing error correction codes.
In context of Industry 4.0 Augmented Reality (AR) is frequently mentioned as the upcoming interface technology for human-machine communication and collaboration. Many prototypes have already arisen in both the consumer market and in the industrial sector. According to numerous experts it will take only few years until AR will reach the maturity level to be deployed in productive applications. Especially for industrial usage it is required to assess security risks and challenges this new technology implicates. Thereby we focus on plant operators, Original Equipment Manufacturers (OEMs) and component vendors as stakeholders. Starting from several industrial AR use cases and the structure of contemporary AR applications, in this paper we identify security assets worthy of protection and derive the corresponding security goals. Afterwards we elaborate the threats industrial AR applications are exposed to and develop an edge computing architecture for future AR applications which encompasses various measures to reduce security risks for our stakeholders.
We all are very much aware of IoT that is Internet of Things which is emerging technology in today's world. The new and advanced field of technology and inventions make use of IoT for better facility. The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Our project is based on IoT and other supporting techniques which can bring out required output. Security issues are everywhere now-a-days which we are trying to deal with by our project. Our security throwbot (a throwable device) will be tossed into a room after activating it and it will capture 360 degree panaromic video from a single IP camera, by using two end connectivity that is, robot end and another is user end, will bring more features to this project. Shape of the robot will be shperical so that problem of retrieving back can be solved. Easy to use and cheap to buy is one of our goal which will be helpful to police and soldiers who get stuck in situations where they have to question oneself before entering to dangerous condition/room. Our project will help them to handle and verify any area before entering by just throwing this robot and getting the sufficient results.
In this paper, we present the design of Intelligent Security Lock prototype which acts as a smart electronic/digital door locking system. The design of lock device and software system including app is discussed. The paper presents idea to control the lock using mobile app via Bluetooth. The lock satisfies comprehensive security requirements using state of the art technologies. It provides strong authentication using face recognition on app. It stores records of all lock/unlock operations with date and time. It also provides intrusion detection notification and real time camera surveillance on app. Hence, the lock is a unique combination of various aforementioned security features providing absolute solution to problem of security.
The need for security in today's world has become a mandatory issue to look after. With the increase in a number of thefts, it has become a necessity to implement a smart security system. Due to the high cost of the existing smart security systems which use conventional Bluetooth and other wireless technologies and their relatively high energy consumption, implementing a security system with low energy consumption at a low cost has become the need of the hour. The objective of the paper is to build a cost effective and low energy consumption security system using the Bluetooth Low Energy (BLE) technology. This system will help the user to monitor and manage the security of the house even when the user is outside the house with the help of webpage. This paper presents the design and implementation of a security system using PSoC 4 BLE which can automatically lock and unlock the door when the user in the vicinity and leaving the vicinity of the door respectively by establishing a wireless connection between the physical lock and the smartphone. The system also captures an image of a person arriving at the house and transmits it wirelessly to a webpage. The system also notifies the user of any intrusion by sending a message and the image of the intruder to the webpage. The user can also access the door remotely on the go from the website.
A high definition(HD) wide dynamic video surveillance system is designed and implemented based on Field Programmable Gate Array(FPGA). This system is composed of three subsystems, which are video capture, video wide dynamic processing and video display subsystem. The images in the video are captured directly through the camera that is configured in a pattern have long exposure in odd frames and short exposure in even frames. The video data stream is buffered in DDR2 SDRAM to obtain two adjacent frames. Later, the image data fusion is completed by fusing the long exposure image with the short exposure image (pixel by pixel). The video image display subsystem can display the image through a HDMI interface. The system is designed on the platform of Lattice ECP3-70EA FPGA, and camera is the Panasonic MN34229 sensor. The experimental result shows that this system can expand dynamic range of the HD video with 30 frames per second and a resolution equal to 1920*1080 pixels by real-time wide dynamic range (WDR) video processing, and has a high practical value.
Due to the transition from analog to digital format, it possible to use IP-protocol for video surveillance systems. In addition, wireless access, color systems with higher resolution, biometrics, intelligent sensors, software for performing video analytics are becoming increasingly widespread. The paper considers only the calculation of the error probability (BER — Bit Error Rate) depending on the realized value of S/N.
We address security and trust in the context of a commercial IP camera. We take a hands-on approach, as we not only define abstract vulnerabilities, but we actually implement the attacks on a real camera. We then discuss the nature of the attacks and the root cause; we propose a formal model of trust that can be used to address the vulnerabilities by explicitly constraining compositionality for trust relationships.
Mobile attack approaches can be categorized as Application Based Attacks and Frequency Based Attacks. Application based attacks are reviewed extensively in the literature. However, frequency based attacks to mobile phones are not experimented in detail. In this work, we have experimentally succeeded to attack an Android smartphone using a simple software based radio circuit. We have developed a software “Primary Mobile Hack Builder” to control Android operated cellphone as a distance. The SMS information and pictures in the cellphone can be obtained using this device. On the other hand, after launching a software into targeting cellphone, the camera of the cellphone can be controlled for taking pictures and downloading them into our computers. It was also possible to eavesdropping the conversation.
This paper introduces SONA (Spatiotemporal system Organized for Natural Analysis), a tabletop and tangible controller system for exploring geotagged information, and more specifically, CCTV. SONA's goal is to support a more natural method of interacting with data. Our new interactions are placed in the context of a physical security environment, closed circuit television (CCTV). We present a three-layered detail on demand set of view filters for CCTV feeds on a digital map. These filters are controlled with a novel tangible device for direct interaction. We validate SONA's tangible controller approach with a user study comparing SONA with the existing CCTV multi-screen method. The results of the study show that SONA's tangible interaction method is superior to the multi-screen approach, both in terms of quantitative results, and is preferred by users.
The Internet of Things (IoT) devices perform security-critical operations and deal with sensitive information in the IoT-based systems. Therefore, the increased deployment of smart devices will make them targets for cyber attacks. Adversaries can perform malicious actions, leak private information, and track devices' and their owners' location by gaining unauthorized access to IoT devices and networks. However, conventional security protocols are not primarily designed for resource constrained devices and therefore cannot be applied directly to IoT systems. In this paper, we propose Boot-IoT - a privacy-preserving, lightweight, and scalable security scheme for limited resource devices. Boot-IoT prevents a malicious device from joining an IoT network. Boot-IoT enables a device to compute a unique identity for authentication each time the device enters a network. Moreover, during device to device communication, Boot-IoT provides a lightweight mutual authentication scheme that ensures privacy-preserving identity usages. We present a detailed analysis of the security strength of BootIoT. We implemented a prototype of Boot-IoT on IoT devices powered by Contiki OS and provided an extensive comparative analysis of Boot-IoT with contemporary authentication methods. Our results show that Boot-IoT is resource efficient and provides better scalability compared to current solutions.
This paper presents a framework for privacy-preserving video delivery system to fulfill users' privacy demands. The proposed framework leverages the inference channels in sensitive behavior prediction and object tracking in a video surveillance system for the sequence privacy protection. For such a goal, we need to capture different pieces of evidence which are used to infer the identity. The temporal, spatial and context features are extracted from the surveillance video as the observations to perceive the privacy demands and their correlations. Taking advantage of quantifying various evidence and utility, we let users subscribe videos with a viewer-dependent pattern. We implement a prototype system for off-line and on-line requirements in two typical monitoring scenarios to construct extensive experiments. The evaluation results show that our system can efficiently satisfy users' privacy demands while saving over 25% more video information compared to traditional video privacy protection schemes.
Video surveillance has been widely adopted to ensure home security in recent years. Most video encoding standards such as H.264 and MPEG-4 compress the temporal redundancy in a video stream using difference coding, which only encodes the residual image between a frame and its reference frame. Difference coding can efficiently compress a video stream, but it causes side-channel information leakage even though the video stream is encrypted, as reported in this paper. Particularly, we observe that the traffic patterns of an encrypted video stream are different when a user conducts different basic activities of daily living, which must be kept private from third parties as obliged by HIPAA regulations. We also observe that by exploiting this side-channel information leakage, attackers can readily infer a user's basic activities of daily living based on only the traffic size data of an encrypted video stream. We validate such an attack using two off-the-shelf cameras, and the results indicate that the user's basic activities of daily living can be recognized with a high accuracy.
In order to enhance the supply chain security at airports, the German federal ministry of education and research has initiated the project ESECLOG (enhanced security in the air cargo chain) which has the goal to improve the threat detection accuracy using one-sided access methods. In this paper, we present a new X-ray backscatter technology for non-intrusive imaging of suspicious objects (mainly low-Z explosives) in luggage's and parcels with only a single-sided access. A key element in this technology is the X-ray backscatter camera embedded with a special twisted-slit collimator. The developed technology has efficiently resolved the problem related to the imaging of complex interior of the object by fixing source and object positions and changing only the scanning direction of the X-ray backscatter camera. Experiments were carried out on luggages and parcels packed with mock-up dangerous materials including liquid and solid explosive simulants. In addition, the quality of the X-ray backscatter image was enhanced by employing high-resolution digital detector arrays. Experimental results are discussed and the efficiency of the present technique to detect suspicious objects in luggages and parcels is demonstrated. At the end, important applications of the proposed backscatter imaging technology to the aviation security are presented.