{"title":"Video steganography techniques: Taxonomy, challenges, and future directions","authors":"Ramadhan J. Mstafa, K. Elleithy, Eman Abdelfattah","doi":"10.1109/LISAT.2017.8001965","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001965","url":null,"abstract":"Nowadays, video steganography has become important in many security applications. The performance of any steganographic method ultimately relies on the imperceptibility, hiding capacity, and robustness. In the past decade, many video steganography methods have been proposed; however, the literature lacks of sufficient survey articles that discuss all techniques. This paper presents a comprehensive study and analysis of numerous cutting edge video steganography methods and their performance evaluations from literature. Both compressed and raw video steganographic methods are surveyed. In the compressed domain, video steganographic techniques are categorized according to the video compression stages as venues for data hiding such as intra frame prediction, inter frame prediction, motion vectors, transformed and quantized coefficients, and entropy coding. On the other hand, raw video steganographic methods are classified into spatial and transform domains. This survey suggests current research directions and recommendations to improve on existing video steganographic techniques.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130738389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quantum min / max algorithms based on qubits {00, 11}","authors":"A. Odeh, Eman Abdelfattah","doi":"10.1109/LISAT.2017.8001972","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001972","url":null,"abstract":"Quantum algorithms have gained a lot of consideration especially for the need to find out the extreme values like minimum or maximum. This paper introduces novel quantum algorithms to figure out the minimum and the maximum numbers among a set of positive integer numbers by employing some of the quantum features such as superposition, entanglement, and probability. The proposed algorithms utilize qubits properties to accelerate the searching process.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Malicious behavior monitoring of embedded medical devices","authors":"Razan Abdulhammed, M. Faezipour, K. Elleithy","doi":"10.1109/LISAT.2017.8001952","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001952","url":null,"abstract":"This research paper proposes and analyzes a hardware based specification rules approach for detecting malicious behaviors of sensors and actuators embedded in medical devices in which the safety of the patient is critical and of utmost importance. The study includes four types of medical devices, namely the Vital Sign Monitor (VSM), Patient Analgesic Control (PCA), Cardiac Device (CD), and Continuous Glucose Monitor (CGM) devices. The research is based on a methodology that transforms a device's behavior rules into a state machine. We design a Finite State Machine (FSM) model out of transformed behavior rules to build a Behavior Specification Rules Monitoring (BSRM) tool for each device. Mentor Graphics Altera ModelSim and Quartus II software packages are used to check the validity of the transformed states machines. Through our simulation and synthesis, we demonstrate that the BSRM tool can effectively identify the expected normal behavior of the device and detect any deviation from its normal behavior. Furthermore, the model is consistent with the requirements for lower power consumption and higher bandwidth applications. The FPGA module of the BSRM can be embedded in the medical devices so that any deviation from the behavior specification can be detected. Moreover, the reconfigurable nature of the FPGA chip adds an extra advantage to the designed model in which the behavior rule can be easily updated and tailored according to the requirements of the device, patient, treatment algorithm, and/or pervasive healthcare applications.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121728223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep learning for sentence classification","authors":"Abdalraouf Hassan, A. Mahmood","doi":"10.1109/LISAT.2017.8001979","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001979","url":null,"abstract":"Most of the machine learning algorithms requires the input to be denoted as a fixed-length feature vector. In text classifications (bag-of-words) is a popular fixed-length features. Despite their simplicity, they are limited in many tasks; they ignore semantics of words and loss ordering of words. In this paper, we propose a simple and efficient neural language model for sentence-level classification task. Our model employs Recurrent Neural Network Language Model (RNN-LM). Particularly, Long Short-Term Memory (LSTM) over pre-trained word vectors obtained from unsupervised neural language model to capture semantics and syntactic information in a short sentence. We achieved outstanding empirical results on multiple benchmark datasets, IMDB Sentiment analysis dataset, and Stanford Sentiment Treebank (SSTb) dataset. The empirical results show that our model is comparable with neural methods and outperforms traditional methods in sentiment analysis task.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116831010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Heartbleed attacks implementation and vulnerability","authors":"Shashank Kyatam, Abdullah Alhayajneh, T. Hayajneh","doi":"10.1109/LISAT.2017.8001980","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001980","url":null,"abstract":"Several vulnerabilities were detected in the open SSL connection versions 1.0.1 and 1.0.1f. Usually, in the previous versions of SSL/TLS, once an SSL connection is established between a client and a server, the connection will stay until the client or server is idle for a certain amount of time, after which the connection will be dropped. The idea of keeping the session connected was proposed in 2012. The initial idea introduced Heartbeat Messages that are indirectly called “keep alive packets”. These “keep alive packets” or “heartbeat packets” are transmitted in between client and server when the SSL session is ideal for a certain amount of time. Regarding “keep alive packets” or “heartbeat packets” mechanisms, these packets are stored in the same memory in which most sensitive information of the client and server is stored. When it is one of the peer's turn to return the heartbeat message, that peer takes the heartbeat packet saved in its random memory location, which is sent by the other peer, and returns it to the other peer to acknowledge the live session. However, the hackers are able to craft a similar Heartbeat Message in a way that makes the peers store it in the same memory location where the sensitive data is stored. Then it returns back the sensitive data along with the crafted heartbeat message sent by the hackers. In this paper, we studied and implemented the heartbleed attack. We also discussed mitigation solutions for this vulnerability.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128725083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of a broadband finline filter","authors":"U. Balaji","doi":"10.1109/LISAT.2017.8001968","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001968","url":null,"abstract":"The design and optimization of low insertion loss finline filters is described in this paper. Finline filter with a large pass band has been designed using equivalent circuit approach. Mode matching method has been used for the analysis of discontinuities in the filter. The performance of the filter obtained through this method is further optimized to achieve improved pass band and stop-band performance. A practical Quasi-Newton algorithm has been used for this purpose.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131506890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust kernel-based machine learning localization using NLOS TOAs or TDOAs","authors":"Jun Li, I. Lu, Jonathan S. Lu, Lingwen Zhang","doi":"10.1109/LISAT.2017.8001981","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001981","url":null,"abstract":"A robust kernel-based machine learning localization scheme using time of arrival (TOA) or time difference of arrival (TDOA) in none-line-of-sight (NLOS) environments is proposed. The scheme can provide accurate position estimation while the reference nodes are coarsely and randomly distributed in the area of interests. Moreover, the scheme is insensitive with respect to random TOA synchronization and measurement errors.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"357 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122809008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Surgeon specific ergonomically enhanced microforceps for micro-neurosurgery","authors":"Ramandeep Singh, A. Suri, Britty Baby, S. Anand","doi":"10.1109/LISAT.2017.8001985","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001985","url":null,"abstract":"Operating microscopes are integral components of modern neurosurgery. Despite the fact that there has been a significant technological progression in optics, many neurosurgeons are not satisfied with the present day neurosurgical instruments. With many instruments having dexterity limitations, constrained degrees of freedom and deprived ergonomics, the need for creating enhanced and better instruments is felt by neurosurgeons. The present work is related to surgeon specific ergonomic improvements in the fine microsurgical instrument called micro-forceps. This instrument is used to perform fine micro-suturing task under high magnification. The larger inter-tip distance gets amplified at this magnification and hence results in difficulty to perform suturing. Other factors related to ergonomics of this instrument are optimal applied force and surface roughness. Considering these design factors a new prototype of micro-forceps was designed, developed and validated. Subjective and objective analysis of the DMLS control and study instrument shows several ergonomic benefits. These include reduced inter-tip distance, reduced applied force of operation and optimal surface roughness.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127323740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"LIDAR for Scribbler 2","authors":"Kevin S. Miller, S. Robila","doi":"10.1109/LISAT.2017.8001957","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001957","url":null,"abstract":"This paper describes a project to enhance a commonly used educational robot, the Parallax Scribbler 2 (S2), by adding more sensor capabilities and making it truly autonomous. The S2 is a popular platform in high school and college robotics courses yet it lacks significant capacity that is compensated by often pairing it with Fluke 2, an interface/controller card developed by a third party group. However, while improving the robot's capability the Fluke card provides limited support for truly autonomous navigation, mainly due to the simplicity of some of the sensors as well as the technology used. In this project, the Fluke is replaced by a LIDAR (LIght Detection And Ranging) sensor with communication supported by a IOIO-OTG (pronounced “yo-yo-O-T-G”) developer board and an inexpensive Android device. The resulting platform will allow for more reliable mapping capabilities as well as open the door for S2 based autonomous navigation to be studied and developed as part of robotics education.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128470750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of fractional order integrator using IE3d for microwave frequencies","authors":"Gurmeet Singh, Vaneet Singh","doi":"10.1109/LISAT.2017.8001988","DOIUrl":"https://doi.org/10.1109/LISAT.2017.8001988","url":null,"abstract":"In this paper, fractional order Integrator for microwave frequencies is proposed. The fractional order Integrator is designed using microstrip and the operating frequency range of that Integrator is in the microwave range. The frequency response of the proposed fractional order microwave Integrator matches with that of an ideal Integrator. The bandwidth of the proposed circuit is 0.6 MHZ. A comparison of the MATLAB and IE3D simulated results for fractional order microwave Integrator is presented in this paper. The experiment results lie within the range of theoretical values.","PeriodicalId":370931,"journal":{"name":"2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":" 40","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132074876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}