Edge Detection and Security 2015

	Edge Detection and Security 2015

Edge detection is an important issue in image and signal processing. The works cited here look at the development of various security methods and approaches. These works were presented or published in 2015.

Yassin, A.A.; Hussain, A.A.; Mutlaq, K.A.-A., “Cloud Authentication Based on Encryption of Digital Image Using Edge Detection,” in Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on, vol., no., pp. 1–6, 3–5 March 2015. doi:10.1109/AISP.2015.7123517
Abstract: The security of cloud computing is the most important concerns that may delay its well-known adoption. Authentication is the central part of cloud security, targeting to gain valid users for accessing to stored data in cloud computing. There are several authentication schemes that based on username/password, but they are considered weak methods of cloud authentication. In the other side, image’s digitization becomes highly vulnerable to malicious attacks over cloud computing. Our proposed scheme focuses on two-factor authentication that used image partial encryption to overcome above aforementioned issues and drawbacks of authentication schemes. Additionally, we use a fast partial image encryption scheme using Canny’s edge detection with symmetric encryption is done as a second factor. In this scheme, the edge pixels of image are encrypted using the stream cipher as it holds most of the image’s data and then we applied this way to authenticate valid users. The results of security analysis and experimental results view that our work supports a good balance between security and performance for image encryption in cloud computing environment.
Keywords: cloud computing; cryptography; edge detection; Canny edge detection; cloud authentication; cloud computing security; digital image partial encryption; image digitization; stream cipher; symmetric encryption; two-factor authentication; Authentication; Cloud computing; Digital images; Encryption; Image edge detection; Cloud Computing; Edge Detection; Image encryption; Password; Service Provider (ID#: 15-7108)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7123517&isnumber=7123478

Al-Dmour, H.; Al-Ani, A., “Quality Optimized Medical Image Steganography Based on Edge Detection and Hamming Code,” in Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, vol., no., pp. 1486–1489, 16–19 April 2015. doi:10.1109/ISBI.2015.7164158
Abstract: A Picture Archiving and Communication System (PACS) is a technology designed to store and transmit digitized medical images over a public network for certain uses. One of the main concerns relating to most of the existing systems is that little attention has been paid to the security and protection of patients’ information. Accordingly, there has been an increased interest in recent years to enhance the confidentiality of patients’ information. This paper introduces a high imperceptibility digital steganography method that hides Electronic Patient Records (EPR) into a medical image without modifying its important part. This method utilizes edge detection to identify and embed secret data in sharp regions of the image, as the human visual system (HVS) is less sensitive to changes in high contrast areas of images, compared to their smooth areas. Moreover, a Hamming code that embeds 3 secret message bits into 4 bits of the cover image is utilized as this will help in enhancing the quality of the produced images. We hide EPR into the Region of Non-Interest (RONI) to protect the decision area i.e., Region of Interest (ROI), which is essential for the diagnosis. The effectiveness of the proposed scheme is proven through the well-known of imperceptibility measure of Peak Signal-to-Noise Ratio (PSNR) when considering different message length.
Keywords: Hamming codes; PACS; data protection; edge detection; electronic health records; image coding; image enhancement; medical image processing; security of data; steganography; EPR; Electronic Patient Records; HVS; Hamming code; PACS; PSNR; Peak Signal-to-Noise Ratio; Picture Archiving and Communication System; ROI; RONI; Region of Interest; Region of NonInterest; cover image; decision area; digitized medical images; edge detection; high contrast areas; high imperceptibility digital steganography method; human visual system; image quality enhancement; imperceptibility measure; message length; patient information confidentiality; patient information protection; patient information security; public network; quality optimized medical image steganography; secret data; secret message; smooth areas; Cryptography; Image edge detection; Medical diagnostic imaging; Picture archiving and communication systems; Watermarking; EPR; HVS; Hamming code; MSE; PACS; PSNR; RONI and ROI; cost function; digital steganography; edge detection (ID#: 15-7079)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7164158&isnumber=7163789

Rad, R.M.; KokSheik Wong, “Digital Image Forgery Detection by Edge Analysis,” in Consumer Electronics - Taiwan (ICCE-TW), 2015 IEEE International Conference on, vol., no., pp. 19–20, 6–8 June 2015. doi:10.1109/ICCE-TW.2015.7216848
Abstract: The advent of user-friendly yet powerful editing softwares has cast doubt on the authenticity of digital images. Therefore, developing reliable detection techniques is of great importance to verify the originality of a given image. In this work, a forgery detection technique based on the analysis of edge information is proposed. Unlike the conventional methods, the proposed technique is not restricted to the traces left by the act of double compression, but instead it allows the input image to be singly compressed or uncompressed. Experimental results confirmed that proposed method is able to localize forged area when the forged image is not double compressed.
Keywords: data compression; fraud; image coding; digital image authenticity; digital image forgery detection; double image compression; user-friendly editing softwares; Digital images; Discrete cosine transforms; Forgery; Image coding; Image edge detection; Security; Splicing (ID#: 15-7080)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7216848&isnumber=7216784

Chopade, P.; Zhan, J.; Bikdash, M., “Node Attributes and Edge Structure for Large-Scale Big Data Network Analytics and Community Detection,” in Technologies for Homeland Security (HST), 2015 IEEE International Symposium on, vol., no., pp. 1–8, 14–16 April 2015. doi:10.1109/THS.2015.7225331
Abstract: Identifying network communities is one of the most important tasks when analyzing complex networks. Most of these networks possess a certain community structure that has substantial importance in building an understanding regarding the dynamics of the large-scale network. Intriguingly, such communities appear to be connected with unique spectral property of the graph Laplacian of the adjacency matrix and we exploit this connection by using modified relationship between Laplacian and adjacency matrix. We propose modularity optimization based on a greedy agglomerative method, coupled with fast unfolding of communities in large-scale networks using Louvain community finding method. Our proposed modified algorithm is linearly scalable for efficient identification of communities in huge directed/undirected networks. The proposed algorithm shows great performance and scalability on benchmark networks in simulations and successfully recovers communities in real network applications. In this paper, we develop communities from node attributes and edge structure. New modified algorithm statistically models the interaction between the network structure and the node attributes which leads to more accurate community detection as well as helps for identifying robustness of the network structure. We also show that any community must contain a dense Erdos-Renyi (ER) subgraph. We carried out comparisons of the Chung and Lu (CL) and Block Two-Level Erdos-Renyi (BTER) models with four real-world data sets. Results demonstrate that it accurately captures the observable properties of many real-world networks.
Keywords: Big Data; complex networks; graph theory; large-scale systems; matrix algebra; optimisation; BTER models; adjacency matrix; block two-level Erdos-Renyi models; community detection; complex networks; dense Erdos-Renyi subgraph; edge structure; graph Laplacian; greedy agglomerative method; large-scale big data network analytics; large-scale network; modularity optimization; network communities; node attributes; unique spectral property; Clustering algorithms; Computer science; Eigenvalues and eigenfunctions; Erbium; Image edge detection; Laplace equations; Optimization; Big data; Community detection; Large-scale network; Statistical analysis (ID#: 15-7081)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7225331&isnumber=7190491

Abbas, W.; Bhatia, S.; Koutsoukos, X., “Guarding Networks Through Heterogeneous Mobile Guards,” in American Control Conference (ACC), 2015, vol., no., pp. 3428–3433, 1–3 July 2015. doi:10.1109/ACC.2015.7171861
Abstract: In this article, the issue of guarding multi-agent systems against a sequence of intruder attacks through mobile heterogeneous guards (guards with different ranges) is discussed. The article makes use of graph theoretic abstractions of such systems in which agents are the nodes of a graph and edges represent interconnections between agents. Guards represent specialized mobile agents on specific nodes with capabilities to successfully detect and respond to an attack within their guarding range. Using this abstraction, the article addresses the problem in the context of eternal security problem in graphs. Eternal security refers to securing all the nodes in a graph against an infinite sequence of intruder attacks by a certain minimum number of guards. This paper makes use of heterogeneous guards and addresses all the components of the eternal security problem including the number of guards, their deployment and movement strategies. In the proposed solution, a graph is decomposed into clusters and a guard with appropriate range is then assigned to each cluster. These guards ensure that all nodes within their corresponding cluster are being protected at all times, thereby achieving the eternal security in the graph.
Keywords: graph theory; mobile agents; multi-agent systems; network theory (graphs); eternal security problem; graph theoretic abstractions; guarding multiagent systems; guarding networks; heterogeneous mobile guards; intruder attacks; mobile agents; mobile heterogeneous guards; movement strategies; Clustering algorithms; Image edge detection; Mobile communication; Partitioning algorithms; Radiation detectors; Robot sensing systems; Security (ID#: 15-7082)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7171861&isnumber=7170700

Huiling Zhang; Alim, M.A.; Thai, M.T.; Nguyen, H.T., “Monitor Placement to Timely Detect Misinformation in Online Social Networks,” in Communications (ICC), 2015 IEEE International Conference on, vol., no., pp. 1152–1157, 8–12 June 2015. doi:10.1109/ICC.2015.7248478
Abstract: Online Social Networks (OSNs), such as Facebook, Twitter and Google+, facilitate the interactions and communications among people. However, they also make it a fertile land for misinformation to rapidly spread out, which may lead to detrimental consequences. Thus it is imperative to detect the misinformation propagating through OSNs by placing monitors. In this paper, we first study a general misinformation detection problem and show its equivalence to the influence maximization problem. Moreover, in order to prevent misinformation from reaching specific users, we define a τ-Monitor Placement problem for cases where the partial knowledge of misinformation sources is available. We prove the #P complexity of this problem and additionally propose an efficient algorithm to solve it. Extensive experiments on real-world data show the effectiveness of our proposed algorithm with respect to minimizing the number of monitors.
Keywords: computational complexity; optimisation; security of data; social networking (online); #P complexity; τ-monitor placement problem; Facebook; Google+; OSN; Twitter; general misinformation detection problem; maximization problem; online social networks; Complexity theory; Image edge detection; Integrated circuit modeling; Monitoring; Polynomials; Twitter (ID#: 15-7083)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7248478&isnumber=7248285

Kulchandani, J.S.; Dangarwala, K.J., “Moving Object Detection: Review of Recent Research Trends,” in Pervasive Computing (ICPC), 2015 International Conference on, vol., no., pp. 1–5, 8–10 Jan. 2015. doi:10.1109/PERVASIVE.2015.7087138
Abstract: Moving object detection is the task of identifying the physical movement of an object in a given region or area. Over last few years, moving object detection has received much of attraction due to its wide range of applications like video surveillance, human motion analysis, robot navigation, event detection, anomaly detection, video conferencing, traffic analysis and security. In addition, moving object detection is very consequential and efficacious research topic in field of computer vision and video processing since it forms a critical step for many complex processes like video object classification and video tracking activity. Consequently, identification of actual shape of moving object from a given sequence of video frames becomes pertinent. However, task of detecting actual shape of object in motion becomes tricky due to various challenges like dynamic scene changes, illumination variations, presence of shadow, camouflage and bootstrapping problem. To reduce the effect of these problems, researchers have proposed number of new approaches. This paper provides a brief classification of the classical approaches for moving object detection. Further, paper reviews recent research trends to detect moving object for single stationary camera along with discussion of key points and limitations of each approach.
Keywords: cameras; computer vision; image motion analysis; image sequences; object detection; video signal processing; computer vision; moving object detection; single stationary camera; video frame sequence; video object classification; video processing; video tracking activity; Computer vision; Heuristic algorithms; Image edge detection; Lighting; Object detection; Object recognition; Optical filters; Human Motion Analysis; Moving Object Detection; Object Classification; Tracking; Video Surveillance (ID#: 15-7084)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7087138&isnumber=7086957

Akay, F.; Akbulut, A.; Telatar, Z., “3-D Video Reconstruction from 2-D Video,” in Signal Processing and Communications Applications Conference (SIU), 2015 23th, vol., no., pp. 2434–2437, 16–19 May 2015. doi:10.1109/SIU.2015.7130374
Abstract: Today, in general, imaging devices used extensively record the images in 2 dimension (2-D). 3 dimensional (3-D) recording is also obtained by using two or more cameras with heavy computational complexity for image registration. Moreover, according to the advancements in technology, in some areas like medical imaging, security imaging systems etc., (images are in 2-D) 3-D images are required for the expert evaluations. In this study, 3-D image sequences are constructed from 2-D image recordings. Edge and color information of 2-D sequence are used in order to obtain depth map for 3-D reconstruction process. The results obtained show the robustnes of the method presented.
Keywords: computational complexity; image colour analysis; image reconstruction; image registration; image sequences; 2 dimension image recording; 2D image recording; 2D image sequence; 2D video reconstruction; 3 dimensional image recording; 3D image recording; 3D image sequence; 3D video reconstruction; camera; color information; computational complexity; edge information; image registration; medical imaging; security imaging system; DH-HEMTs; Image edge detection; Imaging; Information filters; Rendering (computer graphics); Three-dimensional displays; 2-D; 3-D video; 3-D video conversion; bilateral filter; depth image based rendering; linear depth map (ID#: 15-7085)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7130374&isnumber=7129794

Takai, M., “Measurement of Complex Quantity of Monitoring Area and Detection of High Active Part of Invading Object in Complex Background for Surveillance Camera System,” in Mechatronics (ICM), 2015 IEEE International Conference on, vol., no., pp. 522–528, 6–8 March 2015. doi:10.1109/ICMECH.2015.7084031
Abstract: Surveillance camera system is one of security system. And, general surveillance camera system consists of surveillance camera installed in the monitoring area, and video monitor in the administrative room, and connects each device with communication line. An observer can always watch the monitoring area in the distant place by the networking of the surveillance camera system. Therefore, the observer needs to always watch large amount of image data surveillance camera photographed. It is necessary for it to spend much time and labor that an observer confirms only by naked eyes. This study measures how complex an image is with numerical value from 0.0 to 1.0 using Complex Quantity. The proposal method detects complex background from the image which surveillance camera photographed, and shows enlarges complex background so that an observer can find suspicious individual or unidentified object hiding in complex background easily. And, we measure livingness of the movement of object invading the complex background with Active Quantity so that an observer is able to watch the movement of the subject in monitoring area efficiently. Active Quantity measures how active the movement of the object is with numerical value from 0.0 to 1.0 quantity. And, the proposal surveillance camera system detects high active part consisting of high Active Quantity from the movement of the object in complex background. The observer is possible to watch the quick movement of objects hiding in the complex background in the monitoring area using the proposal surveillance camera system.
Keywords: cameras; image sensors; numerical analysis; optical variables measurement; photography; video surveillance; active quantity; communication line; complex quantity measurement; image data surveillance camera system; object movement measurement; photography; security system; video monitoring; Area measurement; Cameras; Image edge detection; Observers; Proposals; Surveillance (ID#: 15-7086)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7084031&isnumber=7083935

Gaofeng, Zhan; Yong, Jiang, “Research of Information System Based on Intranet Security Algorithm,” in Measuring Technology and Mechatronics Automation (ICMTMA), 2015 Seventh International Conference on, vol., no., pp. 827–830, 13–14 June 2015. doi:10.1109/ICMTMA.2015.203
Abstract: The rapid development of science and technology, rapid progress in computer technology, global Intranet information system. How to protect information security, security elite network become one of the research problem. I was just on the basis of predecessors’ research, aiming at specific problems, this paper proposes a multi structure elements, the superposition of morphological filtering algorithm.
Keywords: Filtering algorithms; Frequency-domain analysis; Image edge detection; Information systems; Noise; Security; Servers; Client/Server; Filtering algorithm; Intranet; Morphology (ID#: 15-7087)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7263697&isnumber=7263490

Mammeri, Abdelhamid; Lu, Guangqian; Boukerche, Azzedine, “Design of Lane Keeping Assist System for Autonomous Vehicles,” in New Technologies, Mobility and Security (NTMS), 2015 7th International Conference on, vol., no., pp. 1–5, 27–29 July 2015. doi:10.1109/NTMS.2015.7266483
Abstract: Lane detection and tracking and departure warning systems are important components of Intelligent Transportation Systems. They have particularly attracted great interest from industry and academia. Many architectures and commercial systems have been proposed in the literature. In this paper, we discuss the design of such systems regarding the following stages: pre-processing, detection, and tracking. For each stage, a short description of its working principle as well as their advantages and shortcomings are introduced. Our paper may possibly help in designing new systems that overcome and improve the shortcomings of current architectures.
Keywords: Feature extraction; Image color analysis; Image edge detection; Kalman filters; Roads; Transforms; Vehicles (ID#: 15-7088)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7266483&isnumber=7266450

Eberle, W.; Holder, L., “Streaming Data Analytics for Anomalies in Graphs,” in Technologies for Homeland Security (HST), 2015 IEEE International Symposium on, vol., no., pp. 1–6, 14–16 April 2015. doi:10.1109/THS.2015.7225259
Abstract: Protecting our nation’s infrastructure and securing sensitive information are critical challenges for both industry and government. Due to the complex and diverse nature of the environments which can expose attacks or terrorism activity, one must not only be able to deal with attacks that are dynamic, or constantly changing, but also take into account the structural aspects of the networks and the relationships among communication events. However, analyzing a massive, ever-growing graph will quickly overwhelm currently-available computing resources. One potential solution to the issue of handling very large graphs is to handle data as a “stream”. In this work, we present an approach to processing a stream of changes to the graph in order to efficiently identify any changes in the normative patterns and any changes in the anomalies to these normative patterns without processing all previous data. The overall framework of our approach is called PLADS for Pattern Learning and Anomaly Detection in Streams. We evaluate our approach on a dataset that represents people movements and actions, as well as a scalable, streaming data generator that represents social network behaviors, in order to assess the ability to efficiently detect known anomalies.
Keywords: data analysis; graph theory; learning (artificial intelligence); security of data; PLADS; data handling; graph-based anomaly detection; information security; normative pattern; pattern learning and anomaly detection in streams; streaming data analytics; Accuracy; Browsers; Generators; Image edge detection; Partitioning algorithms; Social network services; Topology; Graph-based; anomaly detection; knowledge discovery; streaming data (ID#: 15-7089)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7225259&isnumber=7190491

Nguyen, T.D.; Arch-int, S.; Arch-int, N., “A Novel Secure Channel Selection Rule for Spatial Image Steganography,” in Computer Science and Software Engineering (JCSSE), 2015 12th International Joint Conference on, vol., no., pp. 230–235, 22–24 July 2015. doi:10.1109/JCSSE.2015.7219801
Abstract: This paper introduces a novel secure channel selection rule for spatial image steganography. In this scheme, there are two factors considered to identify a pixel, which causes less distortion to cover image, to be modified in data hiding. The first one is an average difference between considered pixel and its neighbors. The value of the considered pixel is the second employed factor. Obtained experimental results reported on 10,000 natural images indicate the higher visual quality and security of our new channel selection rule for spatial image steganography when compared with the previous approaches.
Keywords: image processing; steganography; data hiding; natural images; secure channel selection rule; spatial image steganography; visual quality; Degradation; Distortion; Image edge detection; Noise; Payloads; Security; Visualization; channel selection rule; secure; spatial image (ID#: 15-7090)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7219801&isnumber=7219755

Chieh-Hsun Huang; Han-Sheng Hsu; Hong-Ren Wang; Ting-Yi Yang; Cheng-Ming Huang, “Design and Management of an Intelligent Parking Lot System by Multiple Camera Platforms,” in Networking, Sensing and Control (ICNSC), 2015 IEEE 12th International Conference on, vol., no., pp. 354–359, 9–11 April 2015. doi:10.1109/ICNSC.2015.7116062
Abstract: Parking in the city has been a major problem in modern days. An efficient way to manage the parking lot and to improve the safety of the driver is very important. Traditional parking lots commonly use security camera, ultrasonic sensors or infrared ray sensors to manage the parking lots. However, these systems are not only expensive but time consuming. Therefore, we present a hybrid intelligent parking system, which is able to inform the drivers where is the empty parking space, lend the drivers to easily record where they parking, provide remote monitoring, and offer the parking spot leading service when drivers forget where they parked. In addition, the security guard of the parking lot could provide the functions of remote monitoring, detection and monitoring of parking in the personal sites, and fire detection. This system also employs the micro aerial vehicle (MAV) as mobile monitoring in the indoor environments instead of monitoring by fixed cameras. Through this paper, we demonstrate our system from both driver’s view and security guard’s view.
Keywords: autonomous aerial vehicles; computerised monitoring; image sensors; microrobots; robot vision; traffic engineering computing; MAV; empty parking space; hybrid intelligent parking system; infrared ray sensors; intelligent parking lot system; microaerial vehicle; multiple camera platforms; parking spot leading service; remote monitoring; security camera; security guard; ultrasonic sensors; Cameras; Fires; Image edge detection; Licenses; Monitoring; Sensors; Vehicles; Arduino; Micro aerial vehicle; NFC tag; Parking lot; QR Code; Raspberry Pi (ID#: 15-7091)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7116062&isnumber=7115994

Ahmed Biyabani, A.; Al-Salman, S.A.; Alkhalaf, K.S., “Embedded Real-Time Bilingual ALPR,” in Communications, Signal Processing, and their Applications (ICCSPA), 2015 International Conference on, vol., no., pp. 1–6, 17–19 Feb. 2015. doi:10.1109/ICCSPA.2015.7081311
Abstract: Automatic License Plate Recognition (ALPR) systems are useful for various surveillance and security purposes. While ALPR is a mature technology, customization for individual countries plates is ongoing. The utility of such systems may be increased if they provide real-time information and if they can be deployed easily using low-cost embedded hardware. In this paper we describe a FPGA-based real-time ALPR system which may be embedded and which is geared towards plates with either Roman or Arabic characters. We believe it is the first system with this combination of features. We report a modest 84% success rate for our OCR algorithm in field tests and a corresponding hardware response time of 1.3ms reflecting a 200x improvement over software only techniques.
Keywords: embedded systems; field programmable gate arrays; natural language processing; optical character recognition; traffic engineering computing; ALPR systems; Arabic characters; FPGA-based real-time ALPR system; OCR algorithm; Roman characters; automatic license plate recognition systems; embedded real-time bilingual ALPR; hardware response time; individual countries plates customization; low-cost embedded hardware; security purposes; surveillance purposes; Field programmable gate arrays; Hardware; Image edge detection; Image segmentation; Licenses; Optical character recognition software; Real-time systems; Embedded; Image-processing; Real-time (ID#: 15-7092)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7081311&isnumber=7081264

Sathisha, N.; Babu, K.S.; Raja, K.B.; Venugopal, K.R., “Mantissa Replacement Steganography Using LWT,” in Signal Processing, Communication and Networking (ICSCN), 2015 3rd International Conference on, vol., no., pp. 1–7, 26–28 March 2015. doi:10.1109/ICSCN.2015.7219862
Abstract: Steganography is an authenticated technique for maintaining secrecy of embedded data. The novel concept of replacing mantissa part of cover image by the generated mantissa part of payload is proposed for higher capacity and security. The Lifting wavelet Transform (LWT) is applied on both cover image and payload of sizes a * a and 3a * 2a respectively. The mantissa values of Vertical band (CV), Horizontal band (CH) and diagonal band (CD) of cover image are removed to convert into real values. The approximation band of payload is considered and the odd column element values and even column element values are divided by 300 and 30000 respectively to generate only mantissa part of payload. The modified odd and even column vector pairs are added element by element to form one resultant vector. The column vector elements of cover image and resultant column vector elements of payload are added to generate stego object column vector elements corresponding to vertical, horizontal and diagonal elements. The inverse LWT is applied to generate stego image.
Keywords: approximation theory; image processing; steganography; vectors; wavelet transforms; cover image; embedded data secrecy; even column vector pairs; inverse LWT; lifting wavelet transform; mantissa replacement; mantissa values; modified odd column vector pairs; payload approximation band; resultant column vector elements; steganography; stego image; stego object column vector elements; Barium; Cryptography; Image coding; Image edge detection; Image segmentation; Lead; Noise; LWT; Mantissa; Payload; Steganography; Stego image (ID#: 15-7093)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7219862&isnumber=7219823

Kaur, R.; Kaur, J., “Cloud Computing Security Issues and Its Solution: A Review,” in Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on, vol., no., pp. 1198–1200, 11–13 March 2015. doi: (not provided)
Abstract: Cloud Computing is a way to increase the capacity or add capabilities dynamically without investing in new infrastructure, training new personnel, or licensing new software. As information exchange plays an important role in today’s life, information security becomes more important. This paper is focused on the security issues of cloud computing and techniques to overcome the data privacy issue. Before analyzing the security issues, the definition of cloud computing and brief discussion to under cloud computing is presented, then it explores the cloud security issues and problem faced by cloud service provider. Thus, defining the Pixel key pattern and Image Steganography techniques that will be used to overcome the problem of data security.
Keywords: cloud computing; data privacy; image coding; security of data; steganography; cloud computing security; cloud service provider; data privacy; image steganography technique; information exchange; information security; pixel key pattern; Cloud computing; Clouds; Computational modeling; Computers; Image edge detection; Security; Servers; Cloud Computing; Cloud Security; Image steganography; Pixel key pattern; Security issues (ID#: 15-7094)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7100438&isnumber=7100186

Sariga, N.P.; Sajitha, A.S., “Steganographic Data Hiding in Automatic Converted 3D Image from 2D and 2D to 3D Video Conversion,” in Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on, vol., no., pp. 1–6, 19–20 March 2015. doi:10.1109/ICIIECS.2015.7193097
Abstract: We can implement data hiding in 3D image by using steganography, So as to achieve more efficiency and security than usual 2D image data hiding. Despite a significant growth during last couple of years, the availability of 3D content is still dwarfed by that of the 2D counterpart. In order to close this gap, a number of 2D-to-3D image and video conversion methods have been proposed. The results demonstrate that repositories of 3D content can be used for effective 2D-to-3D image conversion. Steganography is one of the best and most challenging methods for securing data. It is a branch of secret communication or security system used in hiding secret data inside digital mediums. An extension to video is immediate by enforcing temporal continuity of computed depth maps.
Keywords: image sequences; steganography; 2D image data hiding; 3D video conversion; automatic converted 3D image; computed depth maps; optical flow; steganographic data hiding; temporal continuity; Cameras; Communication systems; Estimation; Image edge detection; Rendering (computer graphics) Smoothing methods; Three-dimensional displays; 3D images; cross-bilateral filtering; image conversion; nearest neighbor classification; stereoscopic images (ID#: 15-7095)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7193097&isnumber=7192777

Mishra, R.; Bhanodiya, P., “A Review on Steganography and Cryptography,” in Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in, vol., no., pp. 119–122, 19–20 March 2015. doi:10.1109/ICACEA.2015.7164679
Abstract: Today’s information world is a digital world. Data transmission over an unsecure channel is becoming a major issue of concern nowadays. And at the same time intruders are spreading over the internet and being very active. So to protect the secret data from theft some security measures need to be taken. In order to keep the data secret various techniques have been implemented to encrypt and decrypt the secret data. Cryptography and Steganography are the two most prominent techniques from them. But these two techniques alone can’t do work as much efficiently as they do together. Steganography is a Greek word which is made up of two words Stegano and graphy. Stegano means hidden and graphy means writing i.e. Steganography means hidden writing. Steganography is a way to hide the fact that data communication is taking place. While cryptography converts the secret message in other than human readable form but this technique is having a limitation that the encrypted message is visible to everyone. In this way over the internet, intruders may try to apply heat and trial method to get the secret message. Steganography overcome the limitation of cryptography by hiding the fact that some transmission is taking place. In steganography the secret message is hidden in other than original media such as Text, Image, video and audio form. These two techniques are different and having their own significance. So in this paper we are going to discuss various cryptographic and steganographic techniques used in order the keep the message secret.
Keywords: cryptography; data communication; steganography; Internet; cryptographic techniques; data communication; data transmission; digital world; hidden writing; secret data decryption; secret data encryption; secret data protection; security measures; steganographic techniques; Computers; Encryption; Image color analysis; Image edge detection; Media; Cipher Text; Cryptanalysis; Cryptograph; LSB; Steganalysis; Steganography (ID#: 15-7096)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7164679&isnumber=7164643

Kulkarni, N.; Mane, V., “Source Camera Identification Using GLCM,” in Advance Computing Conference (IACC), 2015 IEEE International, vol., no., pp. 1242–1246, 12–13 June 2015. doi:10.1109/IADCC.2015.7154900
Abstract: Digital images are becoming main focus of work for the researchers. Digital image forensics (DIF) is at the forefront of security techniques, aiming to restore the lost trust in digital imagery by uncovering digital counterfeiting techniques. Source camera identification provides different ways to identify the characteristics of the digital devices used. Study of these techniques has been done as literature survey work; from this sensor imperfection based technique is chosen. Sensor pattern noise (SPN), carries abundance of information along with wide frequency range allows for reliable identification in the presence of many imaging sensors. Our proposed system consists of a novel technique used for extracting sensor noise from the database images, and then the feature extraction method is applied to extract the features. The model used for extracting sensor noise consists of use of Gradient based operators and Laplacian operators, a hybrid system consisting of best results from the above two operators obtain a third image giving the edges and noise present in it. The edges are removed by applying threshold to get the noise present in the image. This noisy image is then provided to the feature extraction module consisting of Gray level Co-occurrence Matrix (GLCM). It is used to extract various features based on its properties such as Homogeneity, Contrast, Correlation, and Entropy. The extracted features are used to do the performance evaluation based on various parameters. The accuracy parameter will give the matching rate for the entire dataset. The Sensor Pattern Noise (SPN) is extracted in the GLCM features and used for matching with the test set to get the exact match. The hybrid system used for SPN extraction along with the GLCM feature extraction yields better results.
Keywords: Laplace equations; digital forensics; edge detection; feature extraction; image sensors; matrix algebra; DIF; GLCM feature extraction; Laplacian operators; SPN extraction; digital counterfeiting techniques; digital image forensics; edge removal; gradient based operators; gray level co-occurrence matrix; hybrid system; imaging sensors; performance evaluation; security techniques; sensor noise extraction; sensor pattern noise; source camera identification; Cameras; Conferences; Digital images; Feature extraction; Forensics; Noise; Object recognition; Digital Evidence; Image Forensics; Sensor Pattern noise (ID#: 15-7097)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7154900&isnumber=7154658

Khare, S., “Finger Gesture and Pattern Recognition Based Device Security System,” in Signal Processing and Communication (ICSC), 2015 International Conference on, vol., no., pp. 443–447, 16–18 March 2015. doi:10.1109/ICSPCom.2015.7150694
Abstract: This research aims at introduction of a hand gesture recognition based system to recognize real time gestures in natural environment and compare patterns with image database for matching of image pairs to trigger unlocking of mobile devices. The efforts made in this direction during past relating to security systems for mobile devices has been a major concern and methods like draw pattern unlock, passcodes, facial and voice recognition technologies have already been employed to a fair level of extent, but these are quiet susceptible to hacks and greater ratio of recognition failure errors (especially in cases of voice and facial). A next step in HMI would be use of fingertip tracking based unlocking mechanism, which would employ minimalistic hardware like webcam or smartphone front camera. Image acquisition through MATLAB is followed up by conversion to grayscale and application of optimal filter for edge detection utilized in different conditions for optimal results in recognizing fingertips up to a precise level of accuracy. Pattern is traced at 60 fps for tracking and tracing and therefore cross referenced with the training image by deployment of neural networks for improved recognition efficiency. Data is registered in real time and device is unlocked at instance when SSIM takes a value above predefined threshold percentage or number. The aforementioned mechanism is employed in applications via user friendly GUI frontend and computational modelling through MATLAB for backend.
Keywords: gesture recognition; image motion analysis; mobile handsets; neural nets; security; GUI frontend; MATLAB; SSIM; computational modelling; device security system; draw pattern unlock; edge detection; facial recognition technologies; failure error recognition; finger gesture; fingertip tracking; hand gesture recognition; image acquisition; image database; image pair matching; mobile devices security systems; mobile devices unlocking; neural networks deployment; optimal filter; passcodes; pattern recognition; smartphone front camera; unlocking mechanism; voice recognition technologies; webcam; Biological neural networks; MATLAB; Pattern matching; Security; Training; Computer vision; HMI (Human Machine Interface); MATLAB; ORB; SIFT (Scale Invariant Feature Transform); SSIM (Structural Similarity Index Measure); SURF (Speed Up Robust Features) (ID#: 15-7098)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7150694&isnumber=7150604

Kashyap, A.; Suresh, B.; Agrawal, M.; Gupta, H.; Joshi, S.D., “Detection of Splicing Forgery Using Wavelet Decomposition,” in Computing, Communication & Automation (ICCCA), 2015 International Conference on, vol., no., pp. 843–848, 15–16 May 2015. doi:10.1109/CCAA.2015.7148492
Abstract: Authenticity of an image is an important issue in many social areas such as Journalism, Forensic investigation, Criminal investigation and Security services etc. and digital images can be easily manipulated with the help of sophisticated photo editing software and high-resolution digital cameras. So there is a requirement for the implementation of new powerful and efficient algorithms for forgery detection of a tampered images. The splicing is the common forgery in which two images are combine and make a single composite and the duplicated region is retouched by performing operations like edge blurring to get the appearance of the authentic image. In this paper, we have proposed a new computationally efficient algorithm for splicing (copy-create) forgery detection of an image using block matching method. The proposed method achieve an accuracy of 87.75% within a small processing time by modeling the threshold.
Keywords: image processing; wavelet transforms; authentic image; block matching method; high-resolution digital cameras; photo editing software; splicing forgery detection; wavelet decomposition; Accuracy; Automation; Digital images; Forgery; Splicing; Wavelet transforms; BMP; JPEG; PNG; TIFF; Wavelet decomposition; block matching (ID#: 15-7099)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7148492&isnumber=7148334

Namayanja, J.M.; Janeja, V.P., “Change Detection in Evolving Computer Networks: Changes in Densification and Diameter over Time,” in Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on, vol., no., pp. 185–187, 27–29 May 2015. doi:10.1109/ISI.2015.7165969
Abstract: Large-scale attacks on computer networks usually cause abrupt changes in network traffic, which makes change detection an integral part of attack detection especially in large communication networks. Such changes in traffic can be defined in terms of sudden absence of key nodes or edges, or the addition of new nodes and edges to the network. These are micro level changes. This on the other hand may lead to changes at the macro level of the network such as changes in the density and diameter of the network that describe connectivity between nodes as well as flow of information within the network. Our assumption is that, changes in the behavior of such key nodes in a network translates into changes in the overall structure of the network since these key nodes represent the major chunk of communication in the network. In this study, we focus on detecting changes at the network-level where we sample the network and select key subgraphs associated to central nodes. Our objective is to study selected network-level properties because they provide a bigger picture of underlying events in the network.
Keywords: computer network security; network theory (graphs); attack detection; change detection; communication networks; computer networks; network density; network diameter; network edges; network nodes; network traffic; network-level properties; Decision support systems; Frequency modulation; Central Nodes; Change Point Detection; Network Evolution; Network Properties; Subgraphs (ID#: 15-7100)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7165969&isnumber=7165923

Lomotey, R.K.; Deters, R.; Kaletsch, K., “Mobile Hosting and Sensor Eco-System for Radiation Detection,” in Systems Conference (SysCon), 2015 9th Annual IEEE International, vol., no., pp. 740–746, 13–16 April 2015. doi:10.1109/SYSCON.2015.7116839
Abstract: Gamma ray is an electromagnetic radiation with a very high frequency that can be biologically hazardous. Most workers in the mining, manufacturing, security, and other industries find themselves in such hazardous environments and governments are trying to contain this issue. While traditionally, high gamma radiation detection sensors have been manufactured to be carried along by users, they are not good access point for actual dosage readings. With the recent advancement in mobile technology, this paper proposes a mobile hosting architecture to enable mobile-to-sensor communication following the edge-based technique. This means the sensor can detect the radiation and send readings to a smartphone device of the user. All other near-by mobile devices (which are authorized) will receive the notification to alert the people in the hazard zone. In this paper, the notification dissemination is developed based on the sequential flow pattern. The proposed work is tested and the results show that detected radiations are sent in soft real-time to the mobile devices.
Keywords: electromagnetic waves; gamma-ray detection; smart phones; dosage readings; electromagnetic radiation; gamma radiation detection sensors; gamma ray; mobile hosting architecture; mobile-to-sensor communication; notification dissemination; sensor eco-system; sequential flow pattern; smartphone device; Bluetooth; Computer architecture; Mobile communication; Mobile handsets; Real-time systems; Software; Synchronization; Cloud computing; Gamma Radiation; Latency; Mobile hosting; Optimal Path; Process flow (ID#: 15-7101)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7116839&isnumber=7116715

Sengupta, A.; Bhadauria, S., “User Power-Delay Budget Driven PSO Based Design Space Exploration of Optimal K-Cycle Transient Fault Secured Datapath During High Level Synthesis,” in Quality Electronic Design (ISQED), 2015 16th International Symposium on, vol., no., pp. 289–292, 2–4 March 2015. doi:10.1109/ISQED.2015.7085441
Abstract: Fault security indicates ability to provide error detection or fetching the correct output. Generation (design space exploration (DSE)) of an optimal fault secured datapath structure based on user power-delay budget during high level synthesis (HLS) in the context k-cycle transient fault is considered an intractable problem. This is due to the fact that for every type of candidate design solution produced during exploration, a feasible k-cycle fault secured datapath may not exist satisfying the conflicting user constraints/budget. Secondly, insertion of random cut to optimize delay overhead associated with fault security in most cases may not yield optimal solutions in the context of user constraints/budgets. The solutions to the above problems have not been addressed in the literature so far. The paper solves the problem by presenting: (a) a novel algorithm for fault secured particle swarm optimization driven DSE (b) novel technique for handling k-cycle transient faults (c) novel schemes for selecting appropriate edges for inserting cuts in the scheduled Control Data Flow Graph (CDFG) minimizing delay overhead associated with fault security. The proposed approach yielded optimal results which minimizes hybrid cost as well as satisfies user constraints. Further, results of comparison with recent approaches indicated significant reduction of final cost.
Keywords: circuit optimisation; data flow graphs; error detection; high level synthesis; integrated circuit design; particle swarm optimisation; synchronisation; CDFG; DSE; HLS; PSO; context k-cycle transient fault; control data flow graph; delay overhead; design space exploration; error detection; fault security; high level synthesis; optimal k-cycle transient fault secured datapath; particle swarm optimization; user constraints; user power-delay budget; Algorithm design and analysis; Circuit faults; Delays; Hardware; Security; Space exploration; Transient analysis; Fault; delay; k-cycle; power; transient (ID#: 15-7102)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7085441&isnumber=7085355

Agarwal, S.; Sureka, A., “Using Common-Sense Knowledge-Base for Detecting Word Obfuscation in Adversarial Communication,” in Communication Systems and Networks (COMSNETS), 2015 7th International Conference on, vol., no.,
pp. 1–6, 6–10 Jan. 2015. doi:10.1109/COMSNETS.2015.7098738
Abstract: Word obfuscation or substitution means replacing one word with another word in a sentence to conceal the textual content or communication. Word obfuscation is used in adversarial communication by terrorist or criminals for conveying their messages without getting red-flagged by security and intelligence agencies intercepting or scanning messages (such as emails and telephone conversations). ConceptNet is a freely available semantic network represented as a directed graph consisting of nodes as concepts and edges as assertions of common sense about these concepts. We present a solution approach exploiting vast amount of semantic knowledge in ConceptNet for addressing the technically challenging problem of word substitution in adversarial communication. We frame the given problem as a textual reasoning and context inference task and utilize ConceptNet’s natural-language-processing tool-kit for determining word substitution. We use ConceptNet to compute the conceptual similarity between any two given terms and define a Mean Average Conceptual Similarity (MACS) metric to identify out-of-context terms. The test-bed to evaluate our proposed approach consists of Enron email dataset (having over 600000 emails generated by 158 employees of Enron Corporation) and Brown corpus (totaling about a million words drawn from a wide variety of sources). We implement word substitution techniques used by previous researches to generate a test dataset.We conduct a series of experiments consisting of word substitution methods used in the past to evaluate our approach. Experimental results reveal that the proposed approach is effective.
Keywords: directed graphs; electronic mail; inference mechanisms; national security; natural language processing; semantic networks; terrorism; text analysis; word processing; Brown corpus; ConceptNet; ConceptNet natural-language-processing tool-kit; Enron Corporation; Enron email dataset; MACS metric; adversarial communication; common-sense knowledge-base; context inference task; criminals; directed graph; intelligence agencies; mean average conceptual similarity metric; message scanning; security agencies; semantic knowledge; semantic network; terrorist; textual communication; textual content; textual reasoning; word obfuscation detection; word substitution techniques; Bismuth; Postal services; ConceptNet; Intelligence and Security Informatics; Natural Language Processing; Semantic Similarity; Word Substitution (ID#: 15-7103)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7098738&isnumber=7098633

Milling, C.; Caramanis, C.; Mannor, S.; Shakkottai, S., “Local Detection of Infections in Heterogeneous Networks,” in Computer Communications (INFOCOM), 2015 IEEE Conference on, vol., no., pp. 1517–1525, April 26 2015–May 1 2015. doi:10.1109/INFOCOM.2015.7218530
Abstract: In many networks the operator is faced with nodes that report a potentially important phenomenon such as failures, illnesses, and viruses. The operator is faced with the question: Is it spreading over the network, or simply occurring at random? We seek to answer this question from highly noisy and incomplete data, where at a single point in time we are given a possibly very noisy subset of the infected population (including false positives and negatives). While previous work has focused on uniform spreading rates for the infection, heterogeneous graphs with unequal edge weights are more faithful models of reality. Critically, the network structure may not be fully known and modeling epidemic spread on unknown graphs relies on non-homogeneous edge (spreading) weights. Such heterogeneous graphs pose considerable challenges, requiring both algorithmic and analytical development. We develop an algorithm that can distinguish between a spreading phenomenon and a randomly occurring phenomenon while using only local information and not knowing the complete network topology and the weights. Further, we show that this algorithm can succeed even in the presence of noise, false positives and unknown graph edges.
Keywords: computer network security; computer viruses; graph theory; critical network structure; false negatives; false positives; graph edge; heterogeneous graph; heterogeneous networks; infected population; infection local detection; local information; Analytical models; Approximation algorithms; Computers; Conferences; Electronic mail; Noise measurement; Probabilistic logic (ID#: 15-7104)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7218530&isnumber=7218353 
 

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