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Medeiros, Ibéria, Neves, Nuno.  2020.  Impact of Coding Styles on Behaviours of Static Analysis Tools for Web Applications. 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S). :55–56.
Web applications have become an essential resource to access the services of diverse subjects (e.g., financial, healthcare) available on the Internet. Despite the efforts that have been made on its security, namely on the investigation of better techniques to detect vulnerabilities on its source code, the number of vulnerabilities exploited has not decreased. Static analysis tools (SATs) are often used to test the security of applications since their outcomes can help developers in the correction of the bugs they found. The conducted investigation made over SATs stated they often generate errors (false positives (FP) and false negatives (FN)), whose cause is recurrently associated with very diverse coding styles, i.e., similar functionality is implemented in distinct manners, and programming practices that create ambiguity, such as the reuse and share of variables. Based on a common practice of using multiple forms in a same webpage and its processing in a single file, we defined a use case for user login and register with six coding styles scenarios for processing their data, and evaluated the behaviour of three SATs (phpSAFE, RIPS and WAP) with them to verify and understand why SATs produce FP and FN.
Stegemann-Philipps, Christian, Butz, Martin V..  2021.  Learn It First: Grounding Language in Compositional Event-Predictive Encodings. 2021 IEEE International Conference on Development and Learning (ICDL). :1–6.
While language learning in infants and toddlers progresses somewhat seamlessly, in artificial systems the grounding of language in knowledge structures that are learned from sensorimotor experiences remains a hard challenge. Here we introduce LEARNA, which learns event-characterizing abstractions to resolve natural language ambiguity. LEARNA develops knowledge structures from simulated sensorimotor experiences. Given a possibly ambiguous descriptive utterance, the learned knowledge structures enable LEARNA to infer environmental scenes, and events unfolding within, which essentially constitute plausible imaginations of the utterance’s content. Similar event-predictive structures may help in developing artificial systems that can generate and comprehend descriptions of scenes and events.
Tahirovic, Alma Ademovic, Angeli, David, Strbac, Goran.  2021.  A Complex Network Approach to Power System Vulnerability Analysis based on Rebalance Based Flow Centrality. 2021 IEEE Power & Energy Society General Meeting (PESGM). :01—05.
The study of networks is an extensively investigated field of research, with networks and network structure often encoding relationships describing certain systems or processes. Critical infrastructure is understood as being a structure whose failure or damage has considerable impact on safety, security and wellbeing of society, with power systems considered a classic example. The work presented in this paper builds on the long-lasting foundations of network and complex network theory, proposing an extension in form of rebalance based flow centrality for structural vulnerability assessment and critical component identification in adaptive network topologies. The proposed measure is applied to power system vulnerability analysis, with performance demonstrated on the IEEE 30-, 57- and 118-bus test system, outperforming relevant methods from the state-of-the-art. The proposed framework is deterministic (guaranteed), analytically obtained (interpretable) and generalizes well with changing network parameters, providing a complementary tool to power system vulnerability analysis and planning.
Obert, James, Loffredo, Tim.  2021.  Efficient Binary Static Code Data Flow Analysis Using Unsupervised Learning. 2021 4th International Conference on Artificial Intelligence for Industries (AI4I). :89—90.
The ever increasing need to ensure that code is reliably, efficiently and safely constructed has fueled the evolution of popular static binary code analysis tools. In identifying potential coding flaws in binaries, tools such as IDA Pro are used to disassemble the binaries into an opcode/assembly language format in support of manual static code analysis. Because of the highly manual and resource intensive nature involved with analyzing large binaries, the probability of overlooking potential coding irregularities and inefficiencies is quite high. In this paper, a light-weight, unsupervised data flow methodology is described which uses highly-correlated data flow graph (CDFGs) to identify coding irregularities such that analysis time and required computing resources are minimized. Such analysis accuracy and efficiency gains are achieved by using a combination of graph analysis and unsupervised machine learning techniques which allows an analyst to focus on the most statistically significant flow patterns while performing binary static code analysis.
Nagata, Daiya, Hayashi, Yu-ichi, Mizuki, Takaaki, Sone, Hideaki.  2021.  QR Bar-Code Designed Resistant against EM Information Leakage. 2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS). :1–4.
A threat of eavesdropping display screen image of information device is caused by unintended EM leakage emanation. QR bar-code is capable of error correction, and its information is possibly read from a damaged screen image from EM leakage. A new design of QR bar-code proposed in this paper uses selected colors in consideration of correlation between the EM wave leakage and display color. Proposed design of QR bar-code keeps error correction of displayed image, and makes it difficult to read information on the eavesdropped image.
Sakk, Eric, Wang, Shuangbao Paul.  2021.  Code Structures for Quantum Encryption and Decryption. 2021 IEEE 5th International Conference on Cryptography, Security and Privacy (CSP). :7—11.
The paradigm of quantum computation has led to the development of new algorithms as well variations on existing algorithms. In particular, novel cryptographic techniques based upon quantum computation are of great interest. Many classical encryption techniques naturally translate into the quantum paradigm because of their well-structured factorizations and the fact that they can be phased in the form of unitary operators. In this work, we demonstrate a quantum approach to data encryption and decryption based upon the McEliece cryptosystem using Reed-Muller codes. This example is of particular interest given that post-quantum analyses have highlighted this system as being robust against quantum attacks. Finally, in anticipation of quantum computation operating over binary fields, we discuss alternative operator factorizations for the proposed cryptosystem.
Harrison, Willie K., Shoushtari, Morteza.  2021.  On Caching with Finite Blocklength Coding for Secrecy over the Binary Erasure Wiretap Channel. 2021 Wireless Telecommunications Symposium (WTS). :1–6.
In this paper, we show that caching can aid in achieving secure communications by considering a wiretap scenario where the transmitter and legitimate receiver share access to a secure cache, and an eavesdropper is able to tap transmissions over a binary erasure wiretap channel during the delivery phase of a caching protocol. The scenario under consideration gives rise to a new channel model for wiretap coding that allows the transmitter to effectively choose a subset of bits to erase at the eavesdropper by caching the bits ahead of time. The eavesdropper observes the remainder of the coded bits through the wiretap channel for the general case. In the wiretap type-II scenario, the eavesdropper is able to choose a set of revealed bits only from the subset of bits not cached. We present a coding approach that allows efficient use of the cache to realize a caching gain in the network, and show how to use the cache to optimize the information theoretic security in the choice of a finite blocklength code and the choice of the cached bit set. To our knowledge, this is the first work on explicit algorithms for secrecy coding in any type of caching network.
Pinto, Thyago M. S., Vilela, João P., Gomes, Marco A. C., Harrison, Willie K..  2021.  Keyed Polar Coding for Physical-Layer Security without Channel State Information. ICC 2021 - IEEE International Conference on Communications. :1–6.
Polar codes have been shown to provide an effective mechanism for achieving physical-layer security over various wiretap channels. A majority of these schemes require channel state information (CSI) at the encoder for both intended receivers and eavesdroppers. In this paper, we consider a polar coding scheme for secrecy over a Gaussian wiretap channel when no CSI is available. We show that the availability of a shared keystream between friendly parties allows polar codes to be used for both secure and reliable communications, even when the eavesdropper knows a large fraction of the keystream. The scheme relies on a predetermined strategy for partitioning the bits to be encoded into a set of frozen bits and a set of information bits. The frozen bits are filled with bits from the keystream, and we evaluate the security gap when the cyclic redundancy check-aided successive cancellation list decoder is used at both receivers in the wiretap channel model.
El-Halabi, Mustafa, Mokbel, Hoda.  2021.  Physical-Layer Security for 5G Wireless Networks: Sharing Non-Causal CSI with the Eavesdropper. IEEE EUROCON 2021 - 19th International Conference on Smart Technologies. :343–347.
Physical-layer security is a new paradigm that offers data protection against eavesdropping in wireless 5G networks. In this context, the Gaussian channel is a typical model that captures the practical aspects of confidentially transmitting a message through the wireless medium. In this paper, we consider the peculiar case of transmitting a message through a wireless, state-dependent channel which is prone to eavesdropping, where the state knowledge is non-causally known and shared between the sender and the eavesdropper. We show that a novel structured coding scheme, which combines random coding arguments and the dirty-paper coding technique, achieves the fundamental limit of secure and reliable communication for the considered model.
Li, Lintao, Xing, Yiran, Yao, Xiaoxia, Luo, Yuquan.  2021.  McEliece Coding Method based on LDPC Code with Application to Physical Layer Security. 2021 7th International Conference on Computer and Communications (ICCC). :2042–2045.
The ubiquity of wireless communication systems has resulted in extensive concern regarding their security issues. Combination of signaling and secrecy coding can provide greater improvement of confidentiality than tradition methods. In this work, we mainly focus on the secrecy coding design for physical layer security in wireless communications. When the main channel and wiretap channel are noisy, we propose a McEliece secure coding method based on LDPC which can guarantee both reliability between intended users and information security with respect to eavesdropper simultaneously. Simulation results show that Bob’s BER will be significantly decreased with the SNR increased, while Eve get a BER of 0.5 no matter how the SNR changes.
Liu, Tang, Tuninetti, Daniela.  2021.  Optimal Linear Coding Schemes for the Secure Decentralized Pliable Index Coding Problem. 2020 IEEE Information Theory Workshop (ITW). :1—5.
This paper studies the secure decentralized Pliable Index CODing (PICOD) problem, where the security constraint forbids users to decode more than one message while the decentralized setting imposes that there is no central transmitter in the system, and thus transmissions occur only among users. A converse bound from the Authors' previous work showed a factor of three difference in optimal code-length between the centralized and the decentralized versions of the problem, under the constraint of linear encoding. This paper first lists all linearly infeasible cases, that is, problems where no linear code can simultaneously achieve both correctness/decodability and security. Then, it proposes linear coding schemes for the remaining cases and shows that their code-length is to within an additive constant gap from the converse bound.
Yudin, Oleksandr, Artemov, Volodymyr, Krasnorutsky, Andrii, Barannik, Vladimir, Tupitsya, Ivan, Pris, Gennady.  2021.  Creating a Mathematical Model for Estimating the Impact of Errors in the Process of Reconstruction of Non-Uniform Code Structures on the Quality of Recoverable Video Images. 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT). :40—45.
Existing compression coding technologies are investigated using a statistical approach. The fundamental strategies used in the process of statistical coding of video information data are analyzed. Factors that have a significant impact on the reliability and efficiency of video delivery in the process of statistical coding are analyzed. A model for estimating the impact of errors in the process of reconstruction of uneven code structures on the quality of recoverable video images is being developed.The influence of errors that occur in data transmission channels on the reliability of the reconstructed video image is investigated.
Pan, Conglin, Chen, Si, Wu, Wei, Qian, Jiachuan, Wang, Lijun.  2021.  Research on Space-Time Block Code Technology in MIMO System. 2021 7th International Conference on Computer and Communications (ICCC). :1875—1879.
MIMO technology has been widely used in the telecommunication systems nowadays, and the space-time coding is a key part of MIMO technology. A good coding scheme can exploit the spatial diversity to correct the error which is generated in transmission, and increase the normalized transfer rate with low decoding complexity. On the Basis of the research on different Space-Time Block Codes, this essay proposes a new STBC, Diagonal Block Orthogonal Space-Time Block Code. Then we will compare it with other STBCs in the performance of bit error rate, transfer rate, decoding complexity and peek-to-average power ratio, the final result will prove the superiority of DBOAST.
Senlin, Yan.  2021.  Study on An Alternate-Channel Chaotic Laser Secure Communication System and Shifting Secret Keys to Enhance Security. 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). :1—6.
We present an alternate-channel chaotic laser secure communication system to enhance information communication security and study its technical solution via combining chaos shift keying (CSK) and chaos masking (CM). Two coupled lasers and other two single lasers are introduced as a novel alternate-channel secure communication system, where one of two coupled lasers is modulated via CSK to encode a digital signal and the other of coupled lasers is used to emit a chaotic carrier to mask an information using CM. The two single lasers are used to decode CSK and CM information, respectively. And such CSK performance results in enhancement of CM secure performance because of in-time variation of the emitter' parameter as secret keys. The obtained numerical results show that the encoding and decoding can be successfully performed. The study is beneficial to chaotic cryptography and optics secure communication.
Hofbauer, Heinz, Martínez-Díaz, Yoanna, Kirchgasser, Simon, Méndez-Vázquez, Heydi, Uhl, Andreas.  2021.  Highly Efficient Protection of Biometric Face Samples with Selective JPEG2000 Encryption. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :2580–2584.
When biometric databases grow larger, a security breach or leak can affect millions. In order to protect against such a threat, the use of encryption is a natural choice. However, a biometric identification attempt then requires the decryption of a potential huge database, making a traditional approach potentially unfeasible. The use of selective JPEG2000 encryption can reduce the encryption’s computational load and enable a secure storage of biometric sample data. In this paper we will show that selective encryption of face biometric samples is secure. We analyze various encoding settings of JPEG2000, selective encryption parameters on the "Labeled Faces in the Wild" database and apply several traditional and deep learning based face recognition methods.
Dekarske, Jason, Joshi, Sanjay S..  2021.  Human Trust of Autonomous Agent Varies With Strategy and Capability in Collaborative Grid Search Task. 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS). :1–6.
Trust is an important emerging area of study in human-robot cooperation. Many studies have begun to look at the issue of robot (agent) capability as a predictor of human trust in the robot. However, the assumption that agent capability is the sole predictor of human trust could underestimate the complexity of the problem. This study aims to investigate the effects of agent-strategy and agent-capability in a visual search task. Fourteen subjects were recruited to partake in a web-based grid search task. They were each paired with a series of autonomous agents to search an on-screen grid to find a number of outlier objects as quickly as possible. Both the human and agent searched the grid concurrently and the human was able to see the movement of the agent. Each trial, a different autonomous agent with its assigned capability, used one of three search strategies to assist their human counterpart. After each trial, the autonomous agent reported the number of outliers it found, and the human subject was asked to determine the total number of outliers in the area. Some autonomous agents reported only a fraction of the outliers they encountered, thus coding a varying level of agent capability. Human subjects then evaluated statements related to the behavior, reliability, and trust of the agent. The results showed increased measures of trust and reliability with increasing capability. Additionally, the most legible search strategies received the highest average ratings in a measure of familiarity. Remarkably, given no prior information about capabilities or strategies that they would see, subjects were able to determine consistent trustworthiness of the agent. Furthermore, both capability and strategy of the agent had statistically significant effects on the human’s trust in the agent.
Imtiaz, Sayem Mohammad, Sultana, Kazi Zakia, Varde, Aparna S..  2021.  Mining Learner-friendly Security Patterns from Huge Published Histories of Software Applications for an Intelligent Tutoring System in Secure Coding. 2021 IEEE International Conference on Big Data (Big Data). :4869–4876.
Security patterns are proven solutions to recurring problems in software development. The growing importance of secure software development has introduced diverse research efforts on security patterns that mostly focused on classification schemes, evolution and evaluation of the patterns. Despite a huge mature history of research and popularity among researchers, security patterns have not fully penetrated software development practices. Besides, software security education has not been benefited by these patterns though a commonly stated motivation is the dissemination of expert knowledge and experience. This is because the patterns lack a simple embodiment to help students learn about vulnerable code, and to guide new developers on secure coding. In order to address this problem, we propose to conduct intelligent data mining in the context of software engineering to discover learner-friendly software security patterns. Our proposed model entails knowledge discovery from large scale published real-world vulnerability histories in software applications. We harness association rule mining for frequent pattern discovery to mine easily comprehensible and explainable learner-friendly rules, mainly of the type "flaw implies fix" and "attack type implies flaw", so as to enhance training in secure coding which in turn would augment secure software development. We propose to build a learner-friendly intelligent tutoring system (ITS) based on the newly discovered security patterns and rules explored. We present our proposed model based on association rule mining in secure software development with the goal of building this ITS. Our proposed model and prototype experiments are discussed in this paper along with challenges and ongoing work.
Jobst, Matthias, Liu, Chen, Partzsch, Johannes, Yan, Yexin, Kappel, David, Gonzalez, Hector A., Ji, Yue, Vogginger, Bernhard, Mayr, Christian.  2020.  Event-based Neural Network for ECG Classification with Delta Encoding and Early Stopping. 2020 6th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP). :1–4.
We present a scalable architecture based on a trained filter bank for input pre-processing and a recurrent neural network (RNN) for the detection of atrial fibrillation in electrocardiogram (ECG) signals, with the focus on enabling a very efficient hardware implementation as application-specific integrated circuit (ASIC). Our already very efficient base architecture is further improved by replacing the RNN with a delta-encoded gated recurrent unit (GRU) and adding a confidence measure (CM) for terminating the computation as early as possible. With these optimizations, we demonstrate a reduction of the processing load of 58 % on an internal dataset while still achieving near state-of-the-art classification results on the Physionet ECG dataset with only 1202 parameters.
Nguyen, Vu, Cabrera, Juan A., Pandi, Sreekrishna, Nguyen, Giang T., Fitzek, Frank H. P..  2020.  Exploring the Benefits of Memory-Limited Fulcrum Recoding for Heterogeneous Nodes. GLOBECOM 2020 - 2020 IEEE Global Communications Conference. :1–6.
Fulcrum decoders can trade off between computational complexity and the number of received packets. This allows heterogeneous nodes to decode at different level of complexity in accordance with their computing power. Variations of Fulcrum codes, like dynamic sparsity and expansion packets (DSEP) have significantly reduced the encoders and decoders' complexity by using dynamic sparsity and expansion packets. However, limited effort had been done for recoders of Fulcrum codes and their variations, limiting their full potential when being deployed at multi-hop networks. In this paper, we investigate the drawback of the conventional Fulcrum recoding and introduce a novel recoding scheme for the family of Fulcrum codes by limiting the buffer size, and thus memory needs. Our evaluations indicate that DSEP recoding mechamism increases the recoding goodput by 50%, and reduces the decoding overhead by 60%-90% while maintaining high decoding goodput at receivers and small memory usage at recoders compared with the conventional Fulcrum recoding. This further reduces the resources needed for Fulcrum codes at the recoders.
Qin, Yishuai, Xiao, Bing, Li, Yaodong, Yu, Jintao.  2021.  Structure adjustment of early warning information system based on timeliness. 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 5:2742–2747.
Aimed at the high requirement of timeliness in the process of information assurance, this paper describes the average time delay of information transmission in the system, and designs a timeliness index that can quantitatively describe the ability of early warning information assurance. In response to the problem that system capability cannot meet operational requirements due to enemy attacks, this paper analyzes the structure of the early warning information system, Early warning information complex network model is established, based on the timeliness index, a genetic algorithm based on simulated annealing with special chromosome coding is proposed.the algorithm is used to adjust the network model structure, the ability of early warning information assurance has been improved. Finally, the simulation results show the effectiveness of the proposed method.
Yao, Bing, Wang, Hongyu, Su, Jing, Zhang, Wanjia.  2021.  Graph-Based Lattices Cryptosystem As New Technique Of Post-Quantum Cryptography. 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 5:9–13.
A new method for judging degree sequence is shown by means of perfect ice-flower systems made by operators - stars (particular complete bipartite graphs), and moreover this method can be used to build up degree sequences and perfect ice-flower systems. Graphic lattice, graph-graphic lattice, caterpillar-graphic lattice and topological coding lattice are defined. We establish some connections between traditional lattices and graphic lattices trying to provide new techniques for Lattice-based cryptosystem and post-quantum cryptography, and trying to enrich the theoretical knowledge of topological coding.
Zhang, Cheng, Yamana, Hayato.  2021.  Improving Text Classification Using Knowledge in Labels. 2021 IEEE 6th International Conference on Big Data Analytics (ICBDA). :193–197.
Various algorithms and models have been proposed to address text classification tasks; however, they rarely consider incorporating the additional knowledge hidden in class labels. We argue that hidden information in class labels leads to better classification accuracy. In this study, instead of encoding the labels into numerical values, we incorporated the knowledge in the labels into the original model without changing the model architecture. We combined the output of an original classification model with the relatedness calculated based on the embeddings of a sequence and a keyword set. A keyword set is a word set to represent knowledge in the labels. Usually, it is generated from the classes while it could also be customized by the users. The experimental results show that our proposed method achieved statistically significant improvements in text classification tasks. The source code and experimental details of this study can be found on Github11
Chen, Jian, Shu, Tao.  2021.  Spoofing Detection for Indoor Visible Light Systems with Redundant Orthogonal Encoding. ICC 2021 - IEEE International Conference on Communications. :1–6.
As more and more visible light communication (VLC) and visible light sensing (VLS) systems are mounted on today’s light fixtures, how to guarantee the authenticity of the visible light (VL) signal in these systems becomes an urgent problem. This is because almost all of today’s light fixtures are unprotected and can be openly accessed by almost anyone, and hence are subject to tampering and substitution attacks. In this paper, by exploiting the intrinsic linear superposition characteristics of visible light, we propose VL-Watchdog, a scalable and always-on signal-level spoofing detection framework that is applicable to both VLC and VLS systems. VL-Watchdog is based on redundant orthogonal encoding of the transmitted visible light, and can be implemented as a small hardware add-on to an existing VL system. The effectiveness of the proposed framework was validated through extensive numerical evaluations against a comprehensive set of factors.
Gasimov, Vagif A., Mammadov, Jabir I..  2021.  Image encryption algorithm using DNA pseudo-symbols and chaotic map. 2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). :1—5.
There have been developed image encryption algorithm using chaotic map and DNA pseudo-symbols sequence gained on the basis of real DNA symbols. In the suggested algorithm, the address for the selecting of DNA symbols sequence from Gene Bank, encoding rule of the DNA symbols, also the initial parameters of the chaotic map are determined on the secret key basis. Image pixels modification is based on the numerical values of the chaotic points sets coordinates obtained with the chaos play description of the DNA pseudo-symbols and the transference of pixels is based on displacement table constructed with the chaotic map.
Goswami, Partha Sarathi, Chakraborty, Tamal, Chattopadhyay, Abir.  2021.  A Secured Quantum Key Exchange Algorithm using Fermat Numbers and DNA Encoding. 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT). :1—8.
To address the concerns posed by certain security attacks on communication protocol, this paper proposes a Quantum Key Exchange algorithm coupled with an encoding scheme based on Fermat Numbers and DNA sequences. The concept of Watson-Crick’s transformation of DNA sequences and random property of the Fermat Numbers is applied for protection of the communication system by means of dual encryption. The key generation procedure is governed by a quantum bit rotation mechanism. The total process is illustrated with an example. Also, security analysis of the encryption and decryption process is also discussed.