Visible to the public Biblio

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2021-06-01
Plager, Trenton, Zhu, Ying, Blackmon, Douglas A..  2020.  Creating a VR Experience of Solitary Confinement. 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). :692—693.
The goal of this project is to create a realistic VR experience of solitary confinement and study its impact on users. Although there have been active debates and studies on this subject, very few people have personal experience of solitary confinement. Our first aim is to create such an experience in VR to raise the awareness of solitary confinement. We also want to conduct user studies to compare the VR solitary confinement experience with other types of media experiences, such as films or personal narrations. Finally, we want to study people’s sense of time in such a VR environment.
2021-04-28
Shere, A. R. K., Nurse, J. R. C., Flechais, I..  2020.  "Security should be there by default": Investigating how journalists perceive and respond to risks from the Internet of Things. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :240—249.
Journalists have long been the targets of both physical and cyber-attacks from well-resourced adversaries. Internet of Things (IoT) devices are arguably a new avenue of threat towards journalists through both targeted and generalised cyber-physical exploitation. This study comprises three parts: First, we interviewed 11 journalists and surveyed 5 further journalists, to determine the extent to which journalists perceive threats through the IoT, particularly via consumer IoT devices. Second, we surveyed 34 cyber security experts to establish if and how lay-people can combat IoT threats. Third, we compared these findings to assess journalists' knowledge of threats, and whether their protective mechanisms would be effective against experts' depictions and predictions of IoT threats. Our results indicate that journalists generally are unaware of IoT-related risks and are not adequately protecting themselves; this considers cases where they possess IoT devices, or where they enter IoT-enabled environments (e.g., at work or home). Expert recommendations spanned both immediate and longterm mitigation methods, including practical actions that are technical and socio-political in nature. However, all proposed individual mitigation methods are likely to be short-term solutions, with 26 of 34 (76.5%) of cyber security experts responding that within the next five years it will not be possible for the public to opt-out of interaction with the IoT.
2021-04-08
Verdoliva, L..  2020.  Media Forensics and DeepFakes: An Overview. IEEE Journal of Selected Topics in Signal Processing. 14:910—932.
With the rapid progress in recent years, techniques that generate and manipulate multimedia content can now provide a very advanced level of realism. The boundary between real and synthetic media has become very thin. On the one hand, this opens the door to a series of exciting applications in different fields such as creative arts, advertising, film production, and video games. On the other hand, it poses enormous security threats. Software packages freely available on the web allow any individual, without special skills, to create very realistic fake images and videos. These can be used to manipulate public opinion during elections, commit fraud, discredit or blackmail people. Therefore, there is an urgent need for automated tools capable of detecting false multimedia content and avoiding the spread of dangerous false information. This review paper aims to present an analysis of the methods for visual media integrity verification, that is, the detection of manipulated images and videos. Special emphasis will be placed on the emerging phenomenon of deepfakes, fake media created through deep learning tools, and on modern data-driven forensic methods to fight them. The analysis will help highlight the limits of current forensic tools, the most relevant issues, the upcoming challenges, and suggest future directions for research.
2021-02-16
Shukla, M. K., Dubey, A. K., Upadhyay, D., Novikov, B..  2020.  Group Key Management in Cloud for Shared Media Sanitization. 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC). :117—120.
Cloud provides a low maintenance and affordable storage to various applications and users. The data owner allows the cloud users to access the documents placed in the cloud service provider based on the user's access control vector provided to the cloud users by the data owners. In such type of scenarios, the confidentiality of the documents exchanged between the cloud service provider and the users should be maintained. The existing approaches used to provide this facility are not computation and communication efficient for performing key updating in the data owner side and the key recovery in the user side. This paper discusses the key management services provided to the cloud users. Remote key management and client-side key management are two approaches used by cloud servers. This paper also aims to discuss the method for destroying the encryption/decryption group keys for shared data to securing the data after deletion. Crypto Shredding or Crypto Throw technique is deployed for the same.
2021-02-03
Aliman, N.-M., Kester, L..  2020.  Malicious Design in AIVR, Falsehood and Cybersecurity-oriented Immersive Defenses. 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). :130—137.

Advancements in the AI field unfold tremendous opportunities for society. Simultaneously, it becomes increasingly important to address emerging ramifications. Thereby, the focus is often set on ethical and safe design forestalling unintentional failures. However, cybersecurity-oriented approaches to AI safety additionally consider instantiations of intentional malice – including unethical malevolent AI design. Recently, an analogous emphasis on malicious actors has been expressed regarding security and safety for virtual reality (VR). In this vein, while the intersection of AI and VR (AIVR) offers a wide array of beneficial cross-fertilization possibilities, it is responsible to anticipate future malicious AIVR design from the onset on given the potential socio-psycho-technological impacts. For a simplified illustration, this paper analyzes the conceivable use case of Generative AI (here deepfake techniques) utilized for disinformation in immersive journalism. In our view, defenses against such future AIVR safety risks related to falsehood in immersive settings should be transdisciplinarily conceived from an immersive co-creation stance. As a first step, we motivate a cybersecurity-oriented procedure to generate defenses via immersive design fictions. Overall, there may be no panacea but updatable transdisciplinary tools including AIVR itself could be used to incrementally defend against malicious actors in AIVR.

2021-01-22
Golushko, A. P., Zhukov, V. G..  2020.  Application of Advanced Persistent Threat Actors` Techniques aor Evaluating Defensive Countermeasures. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). :312—317.
This paper describes research results of the possibility of developing a methodology to implement systematic knowledge about adversaries` tactics and techniques into the process of determining requirements for information security system and evaluating defensive countermeasures.
2021-01-20
Li, M., Chang, H., Xiang, Y., An, D..  2020.  A Novel Anti-Collusion Audio Fingerprinting Scheme Based on Fourier Coefficients Reversing. IEEE Signal Processing Letters. 27:1794—1798.

Most anti-collusion audio fingerprinting schemes are aiming at finding colluders from the illegal redistributed audio copies. However, the loss caused by the redistributed versions is inevitable. In this letter, a novel fingerprinting scheme is proposed to eliminate the motivation of collusion attack. The audio signal is transformed to the frequency domain by the Fourier transform, and the coefficients in frequency domain are reversed in different degrees according to the fingerprint sequence. Different from other fingerprinting schemes, the coefficients of the host media are excessively modified by the proposed method in order to reduce the quality of the colluded version significantly, but the imperceptibility is well preserved. Experiments show that the colluded audio cannot be reused because of the poor quality. In addition, the proposed method can also resist other common attacks. Various kinds of copyright risks and losses caused by the illegal redistribution are effectively avoided, which is significant for protecting the copyright of audio.

2021-01-15
Amerini, I., Galteri, L., Caldelli, R., Bimbo, A. Del.  2019.  Deepfake Video Detection through Optical Flow Based CNN. 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). :1205—1207.
Recent advances in visual media technology have led to new tools for processing and, above all, generating multimedia contents. In particular, modern AI-based technologies have provided easy-to-use tools to create extremely realistic manipulated videos. Such synthetic videos, named Deep Fakes, may constitute a serious threat to attack the reputation of public subjects or to address the general opinion on a certain event. According to this, being able to individuate this kind of fake information becomes fundamental. In this work, a new forensic technique able to discern between fake and original video sequences is given; unlike other state-of-the-art methods which resorts at single video frames, we propose the adoption of optical flow fields to exploit possible inter-frame dissimilarities. Such a clue is then used as feature to be learned by CNN classifiers. Preliminary results obtained on FaceForensics++ dataset highlight very promising performances.
2020-12-21
Han, K., Zhang, W., Liu, C..  2020.  Numerical Study of Acoustic Propagation Characteristics in the Multi-scale Seafloor Random Media. 2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP). :135–138.
There is some uncertainty as to the applicability or accuracy of current theories for wave propagation in sediments. Numerical modelling of acoustic data has long been recognized to be a powerful method of understanding of complicated wave propagation and interaction. In this paper, we used the coupled two-dimensional PSM-BEM program to simulate the process of acoustic wave propagation in the seafloor with distributed multi-scale random media. The effects of fluid flow between the pores and the grains with multi-scale distribution were considered. The results show that the coupled PSM-BEM program can be directly applied to both high and low frequency seafloor acoustics. A given porous frame with the pore space saturated with fluid can greatly increase the magnitude of acoustic anisotropy. acoustic wave velocity dispersion and attenuation are significant over a frequency range which spans at least two orders of magnitude.
2020-12-07
Qian, Y..  2019.  Research on Trusted Authentication Model and Mechanism of Data Fusion. 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS). :479–482.
Firstly, this paper analyses the technical foundation of single sign-on solution of unified authentication platform, and analyses the advantages and disadvantages of each solution. Secondly, from the point of view of software engineering, such as function requirement, performance requirement, development mode, architecture scheme, technology development framework and system configuration environment of the unified authentication platform, the unified authentication platform is analyzed and designed, and the database design and system design framework of the system are put forward according to the system requirements. Thirdly, the idea and technology of unified authentication platform based on JA-SIG CAS are discussed, and the design and implementation of each module of unified authentication platform based on JA-SIG CAS are analyzed, which has been applied in ship cluster platform.
2020-12-02
Islam, S., Welzl, M., Gjessing, S..  2018.  Lightweight and flexible single-path congestion control coupling. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. :1—6.

Communication between two Internet hosts using parallel connections may result in unwanted interference between the connections. In this dissertation, we propose a sender-side solution to address this problem by letting the congestion controllers of the different connections collaborate, correctly taking congestion control logic into account. Real-life experiments and simulations show that our solution works for a wide variety of congestion control mechanisms, provides great flexibility when allocating application traffic to the connections, and results in lower queuing delay and less packet loss.

2020-11-30
Hsu, W., Victora, R. H..  2019.  Micromagnetic Study of Media Noise Plateau in Heat-Assisted Magnetic Recording. IEEE Transactions on Magnetics. 55:1–4.
The relationship between integrated media noise power and linear density in heat-assisted magnetic recording (HAMR) is discussed. A noise plateau for intermediate recording density has been observed in HAMR, similar to that found in perpendicular magnetic recording (PMR). Here, we show, by changing the temperature profile of the heat spot in HAMR, that we can tune the noise plateau regions to different recording densities. The heat spot with sharp temperature gradient favors a plateau at high recording density, while the heat spot with gradual temperature gradient favors a plateau at low recording density. This effect is argued to be a consequence of the competition between transition noise and remanence noise in HAMR.
2020-11-02
Xiong, Wenjie, Shan, Chun, Sun, Zhaoliang, Meng, Qinglei.  2018.  Real-time Processing and Storage of Multimedia Data with Content Delivery Network in Vehicle Monitoring System. 2018 6th International Conference on Wireless Networks and Mobile Communications (WINCOM). :1—4.

With the rapid development of the Internet of vehicles, there is a huge amount of multimedia data becoming a hidden trouble in the Internet of Things. Therefore, it is necessary to process and store them in real time as a way of big data curation. In this paper, a method of real-time processing and storage based on CDN in vehicle monitoring system is proposed. The MPEG-DASH standard is used to process the multimedia data by dividing them into MPD files and media segments. A real-time monitoring system of vehicle on the basis of the method introduced is designed and implemented.

2020-08-28
Brinkman, Bo.  2012.  Willing to be fooled: Security and autoamputation in augmented reality. 2012 IEEE International Symposium on Mixed and Augmented Reality - Arts, Media, and Humanities (ISMAR-AMH). :89—90.

What does it mean to trust, or not trust, an augmented reality system? Froma computer security point of view, trust in augmented reality represents a real threat to real people. The fact that augmented reality allows the programmer to tinker with the user's senses creates many opportunities for malfeasance. It might be natural to think that if we warn users to be careful it will lower their trust in the system, greatly reducing risk.

Traylor, Terry, Straub, Jeremy, Gurmeet, Snell, Nicholas.  2019.  Classifying Fake News Articles Using Natural Language Processing to Identify In-Article Attribution as a Supervised Learning Estimator. 2019 IEEE 13th International Conference on Semantic Computing (ICSC). :445—449.

Intentionally deceptive content presented under the guise of legitimate journalism is a worldwide information accuracy and integrity problem that affects opinion forming, decision making, and voting patterns. Most so-called `fake news' is initially distributed over social media conduits like Facebook and Twitter and later finds its way onto mainstream media platforms such as traditional television and radio news. The fake news stories that are initially seeded over social media platforms share key linguistic characteristics such as making excessive use of unsubstantiated hyperbole and non-attributed quoted content. In this paper, the results of a fake news identification study that documents the performance of a fake news classifier are presented. The Textblob, Natural Language, and SciPy Toolkits were used to develop a novel fake news detector that uses quoted attribution in a Bayesian machine learning system as a key feature to estimate the likelihood that a news article is fake. The resultant process precision is 63.333% effective at assessing the likelihood that an article with quotes is fake. This process is called influence mining and this novel technique is presented as a method that can be used to enable fake news and even propaganda detection. In this paper, the research process, technical analysis, technical linguistics work, and classifier performance and results are presented. The paper concludes with a discussion of how the current system will evolve into an influence mining system.

2020-08-07
Davenport, Amanda, Shetty, Sachin.  2019.  Modeling Threat of Leaking Private Keys from Air-Gapped Blockchain Wallets. 2019 IEEE International Smart Cities Conference (ISC2). :9—13.

In this paper we consider the threat surface and security of air gapped wallet schemes for permissioned blockchains as preparation for a Markov based mathematical model, and quantify the risk associated with private key leakage. We identify existing threats to the wallet scheme and existing work done to both attack and secure the scheme. We provide an overview the proposed model and outline justification for our methods. We follow with next steps in our remaining work and the overarching goals and motivation for our methods.

Davenport, Amanda, Shetty, Sachin.  2019.  Air Gapped Wallet Schemes and Private Key Leakage in Permissioned Blockchain Platforms. 2019 IEEE International Conference on Blockchain (Blockchain). :541—545.

In this paper we consider the threat surface and security of air gapped wallet schemes for permissioned blockchains as preparation for a Markov based mathematical model, and quantify the risk associated with private key leakage. We identify existing threats to the wallet scheme and existing work done to both attack and secure the scheme. We provide an overview the proposed model and outline justification for our methods. We follow with next steps in our remaining work and the overarching goals and motivation for our methods.

2020-08-03
Qin, Xinghong, Li, Bin, Huang, Jiwu.  2019.  A New Spatial Steganographic Scheme by Modeling Image Residuals with Multivariate Gaussian Model. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :2617–2621.
Embedding costs used in content-adaptive image steganographic schemes can be defined in a heuristic way or with a statistical model. Inspired by previous steganographic methods, i.e., MG (multivariate Gaussian model) and MiPOD (minimizing the power of optimal detector), we propose a model-driven scheme in this paper. Firstly, we model image residuals obtained by high-pass filtering with quantized multivariate Gaussian distribution. Then, we derive the approximated Fisher Information (FI). We show that FI is related to both Gaussian variance and filter coefficients. Lastly, by selecting the maximum FI value derived with various filters as the final FI, we obtain embedding costs. Experimental results show that the proposed scheme is comparable to existing steganographic methods in resisting steganalysis equipped with rich models and selection-channel-aware rich models. It is also computational efficient when compared to MiPOD, which is the state-of-the-art model-driven method.
2020-07-20
Marakis, Evangelos, van Harten, Wouter, Uppu, Ravitej, Vos, Willem L., Pinkse, Pepijn W. H..  2017.  Reproducibility of artificial multiple scattering media. 2017 Conference on Lasers and Electro-Optics Europe European Quantum Electronics Conference (CLEO/Europe-EQEC). :1–1.
Summary form only given. Authentication of people or objects using physical keys is insecure against secret duplication. Physical unclonable functions (PUF) are special physical keys that are assumed to be unclonable due to the large number of degrees of freedom in their manufacturing [1]. Opaque scattering media, such as white paint and teeth, comprise of millions of nanoparticles in a random arrangement. Under coherent light illumination, the multiple scattering from these nanoparticles gives rise to a complex interference resulting in a speckle pattern. The speckle pattern is seemingly random but highly sensitive to the exact position and size of the nanoparticles in the given piece of opaque scattering medium [2], thereby realizing an ideal optical PUF. These optical PUFs enabled applications such as quantum-secure authentication (QSA) and communication [3, 4].
2020-07-10
Xiao, Tianran, Tong, Wei, Lei, Xia, Liu, Jingning, Liu, Bo.  2019.  Per-File Secure Deletion for Flash-Based Solid State Drives. 2019 IEEE International Conference on Networking, Architecture and Storage (NAS). :1—8.

File update operations generate many invalid flash pages in Solid State Drives (SSDs) because of the-of-place update feature. If these invalid flash pages are not securely deleted, they will be left in the “missing” state, resulting in leakage of sensitive information. However, deleting these invalid pages in real time greatly reduces the performance of SSD. In this paper, we propose a Per-File Secure Deletion (PSD) scheme for SSD to achieve non-real-time secure deletion. PSD assigns a globally unique identifier (GUID) to each file to quickly locate the invalid data blocks and uses Security-TRIM command to securely delete these invalid data blocks. Moreover, we propose a PSD-MLC scheme for Multi-Level Cell (MLC) flash memory. PSD-MLC distributes the data blocks of a file in pairs of pages to avoid the influence of programming crosstalk between paired pages. We evaluate our schemes on different hardware platforms of flash media, and the results prove that PSD and PSD-MLC only have little impact on the performance of SSD. When the cache is disabled and enabled, compared with the system without the secure deletion, PSD decreases SSD throughput by 1.3% and 1.8%, respectively. PSD-MLC decreases SSD throughput by 9.5% and 10.0%, respectively.

2020-04-13
Horne, Benjamin D., Gruppi, Mauricio, Adali, Sibel.  2019.  Trustworthy Misinformation Mitigation with Soft Information Nudging. 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :245–254.

Research in combating misinformation reports many negative results: facts may not change minds, especially if they come from sources that are not trusted. Individuals can disregard and justify lies told by trusted sources. This problem is made even worse by social recommendation algorithms which help amplify conspiracy theories and information confirming one's own biases due to companies' efforts to optimize for clicks and watch time over individuals' own values and public good. As a result, more nuanced voices and facts are drowned out by a continuous erosion of trust in better information sources. Most misinformation mitigation techniques assume that discrediting, filtering, or demoting low veracity information will help news consumers make better information decisions. However, these negative results indicate that some news consumers, particularly extreme or conspiracy news consumers will not be helped. We argue that, given this background, technology solutions to combating misinformation should not simply seek facts or discredit bad news sources, but instead use more subtle nudges towards better information consumption. Repeated exposure to such nudges can help promote trust in better information sources and also improve societal outcomes in the long run. In this article, we will talk about technological solutions that can help us in developing such an approach, and introduce one such model called Trust Nudging.

2020-03-02
Gyawali, Sohan, Qian, Yi.  2019.  Misbehavior Detection Using Machine Learning in Vehicular Communication Networks. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.

Vehicular networks are susceptible to variety of attacks such as denial of service (DoS) attack, sybil attack and false alert generation attack. Different cryptographic methods have been proposed to protect vehicular networks from these kind of attacks. However, cryptographic methods have been found to be less effective to protect from insider attacks which are generated within the vehicular network system. Misbehavior detection system is found to be more effective to detect and prevent insider attacks. In this paper, we propose a machine learning based misbehavior detection system which is trained using datasets generated through extensive simulation based on realistic vehicular network environment. The simulation results demonstrate that our proposed scheme outperforms previous methods in terms of accurately identifying various misbehavior.

2020-02-10
Alia, Mohammad A., Maria, Khulood Abu, Alsarayreh, Maher A., Maria, Eman Abu, Almanasra, Sally.  2019.  An Improved Video Steganography: Using Random Key-Dependent. 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT). :234–237.

Steganography is defined as the art of hiding secret data in a non-secret digital carrier called cover media. Trading delicate data without assurance against intruders that may intrude on this data is a lethal. In this manner, transmitting delicate information and privileged insights must not rely on upon just the current communications channels insurance advancements. Likewise should make more strides towards information insurance. This article proposes an improved approach for video steganography. The improvement made by searching for exact matching between the secret text and the video frames RGB channels and Random Key -Dependent Data, achieving steganography performance criteria, invisibility, payload/capacity and robustness.

2019-12-16
Lin, Ping-Hsien, Chang, Yu-Ming, Li, Yung-Chun, Wang, Wei-Chen, Ho, Chien-Chung, Chang, Yuan-Hao.  2018.  Achieving Fast Sanitization with Zero Live Data Copy for MLC Flash Memory. 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). :1–8.
As data security has become the major concern in modern storage systems with low-cost multi-level-cell (MLC) flash memories, it is not trivial to realize data sanitization in such a system. Even though some existing works employ the encryption or the built-in erase to achieve this requirement, they still suffer the risk of being deciphered or the issue of performance degradation. In contrast to the existing work, a fast sanitization scheme is proposed to provide the highest degree of security for data sanitization; that is, every old version of data could be immediately sanitized with zero live-data-copy overhead once the new version of data is created/written. In particular, this scheme further considers the reliability issue of MLC flash memories; the proposed scheme includes a one-shot sanitization design to minimize the disturbance during data sanitization. The feasibility and the capability of the proposed scheme were evaluated through extensive experiments based on real flash chips. The results demonstrate that this scheme can achieve the data sanitization with zero live-data-copy, where performance overhead is less than 1%.
2019-09-30
Jiao, Y., Hohlfield, J., Victora, R. H..  2018.  Understanding Transition and Remanence Noise in HAMR. IEEE Transactions on Magnetics. 54:1–5.

Transition noise and remanence noise are the two most important types of media noise in heat-assisted magnetic recording. We examine two methods (spatial splitting and principal components analysis) to distinguish them: both techniques show similar trends with respect to applied field and grain pitch (GP). It was also found that PW50can be affected by GP and reader design, but is almost independent of write field and bit length (larger than 50 nm). Interestingly, our simulation shows a linear relationship between jitter and PW50NSRrem, which agrees qualitatively with experimental results.