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Filters: Keyword is Complexity theory  [Clear All Filters]
2021-09-07
Kumar, Nripesh, Srinath, G., Prataap, Abhishek, Nirmala, S. Jaya.  2020.  Attention-based Sequential Generative Conversational Agent. 2020 5th International Conference on Computing, Communication and Security (ICCCS). :1–6.
In this work, we examine the method of enabling computers to understand human interaction by constructing a generative conversational agent. An experimental approach in trying to apply the techniques of natural language processing using recurrent neural networks (RNNs) to emulate the concept of textual entailment or human reasoning is presented. To achieve this functionality, our experiment involves developing an integrated Long Short-Term Memory cell neural network (LSTM) system enhanced with an attention mechanism. The results achieved by the model are shown in terms of the number of epochs versus loss graphs as well as a brief illustration of the model's conversational capabilities.
Simud, Thikamporn, Ruengittinun, Somchoke, Surasvadi, Navaporn, Sanglerdsinlapachai, Nuttapong, Plangprasopchok, Anon.  2020.  A Conversational Agent for Database Query: A Use Case for Thai People Map and Analytics Platform. 2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). :1–6.
Since 2018, Thai People Map and Analytics Platform (TPMAP) has been developed with the aims of supporting government officials and policy makers with integrated household and community data to analyze strategic plans, implement policies and decisions to alleviate poverty. However, to acquire complex information from the platform, non-technical users with no database background have to ask a programmer or a data scientist to query data for them. Such a process is time-consuming and might result in inaccurate information retrieved due to miscommunication between non-technical and technical users. In this paper, we have developed a Thai conversational agent on top of TPMAP to support self-service data analytics on complex queries. Users can simply use natural language to fetch information from our chatbot and the query results are presented to users in easy-to-use formats such as statistics and charts. The proposed conversational agent retrieves and transforms natural language queries into query representations with relevant entities, query intentions, and output formats of the query. We employ Rasa, an open-source conversational AI engine, for agent development. The results show that our system yields Fl-score of 0.9747 for intent classification and 0.7163 for entity extraction. The obtained intents and entities are then used for query target information from a graph database. Finally, our system achieves end-to-end performance with accuracies ranging from 57.5%-80.0%, depending on query message complexity. The generated answers are then returned to users through a messaging channel.
2021-08-31
Amjath, M.I.M., Senthooran, V..  2020.  Secure Communication Using Steganography in IoT Environment. 2020 2nd International Conference on Advancements in Computing (ICAC). 1:114—119.
IoT is an emerging technology in modern world of communication. As the usage of IoT devices is increasing in day to day life, the secure data communication in IoT environment is the major challenge. Especially, small sized Single-Board Computers (SBCs) or Microcontrollers devices are widely used to transfer data with another in IoT. Due to the less processing power and storage capabilities, the data acquired from these devices must be transferred very securely in order to avoid some ethical issues. There are many cryptography approaches are applied to transfer data between IoT devices, but there are obvious chances to suspect encrypted messages by eavesdroppers. To add more secure data transfer, steganography mechanism is used to avoid the chances of suspicion as another layer of security. Based on the capabilities of IoT devices, low complexity images are used to hide the data with different hiding algorithms. In this research study, the secret data is encoded through QR code and embedded in low complexity cover images by applying image to image hiding fashion. The encoded image is sent to the receiving device via the network. The receiving device extracts the QR code from image using secret key then decoded the original data. The performance measure of the system is evaluated by the image quality parameters mainly Peak Signal to Noise Ratio (PSNR), Normalized Coefficient (NC) and Security with maintaining the quality of contemporary IoT system. Thus, the proposed method hides the precious information within an image using the properties of QR code and sending it without any suspicion to attacker and competes with the existing methods in terms of providing more secure communication between Microcontroller devices in IoT environment.
Rathod, Pawan Manoj, Shende, RajKumar K..  2020.  Recommendation System using optimized Matrix Multiplication Algorithm. 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC). :1–4.
Volume, Variety, Velocity, Veracity & Value of data has drawn the attention of many analysts in the last few years. Performance optimization and comparison are the main challenges we face when we talk about the humongous volume of data. Data Analysts use data for activities like forecasting or deep learning and to process these data various tools are available which helps to achieve this task with minimum efforts. Recommendation System plays a crucial role while running any business such as a shopping website or travel agency where the system recommends the user according to their search history, likes, comments, or their past order/booking details. Recommendation System works on various strategies such as Content Filtering, Collaborative Filtering, Neighborhood Methods, or Matrix Factorization methods. For achieving maximum efficiency and accuracy based on the data a specific strategy can be the best case or the worst case for that scenario. Matrix Factorization is the key point of interest in this work. Matrix Factorization strategy includes multiplication of user matrix and item matrix in-order to get a rating matrix that can be recommended to the users. Matrix Multiplication can be achieved by using various algorithms such as Naive Algorithm, Strassen Algorithm, Coppersmith - Winograd (CW) Algorithm. In this work, a new algorithm is proposed to achieve less amount of time and space complexity used in-order for performing matrix multiplication which helps to get the results much faster. By using the Matrix Factorization strategy with various Matrix Multiplication Algorithm we are going to perform a comparative analysis of the same to conclude the proposed algorithm is more efficient.
2021-08-02
Qi, Xiaoxia, Shen, Shuai, Wang, Qijin.  2020.  A Moving Target Defense Technology Based on SCIT. 2020 International Conference on Computer Engineering and Application (ICCEA). :454—457.
Moving target defense technology is one of the revolutionary techniques that is “changing the rules of the game” in the field of network technology, according to recent propositions from the US Science and Technology Commission. Building upon a recently-developed approach called Self Cleansing Intrusion Tolerance (SCIT), this paper proposes a moving target defense system that is based on server switching and cleaning. A protected object is maneuvered to improve its safety by exploiting software diversity and thereby introducing randomness and unpredictability into the system. Experimental results show that the improved system increases the difficulty of attack and significantly reduces the likelihood of a system being invaded, thus serving to enhance system security.
2021-07-28
Alsmadi, Izzat, Zarrad, Anis, Yassine, Abdulrahmane.  2020.  Mutation Testing to Validate Networks Protocols. 2020 IEEE International Systems Conference (SysCon). :1—8.
As networks continue to grow in complexity using wired and wireless technologies, efficient testing solutions should accommodate such changes and growth. Network simulators provide a network-independent environment to provide different types of network testing. This paper is motivated by the observation that, in many cases in the literature, the success of developed network protocols is very sensitive to the initial conditions and assumptions of the testing scenarios. Network services are deployed in complex environments; results of testing and simulation can vary from one environment to another and sometimes in the same environment at different times. Our goal is to propose mutation-based integration testing that can be deployed with network protocols and serve as Built-in Tests (BiT).This paper proposes an integrated mutation testing framework to achieve systematic test cases' generation for different scenario types. Scenario description and variables' setting should be consistent with the protocol specification and the simulation environment. We focused on creating test cases for critical scenarios rather than preliminary or simplified scenarios. This will help users to report confident simulation results and provide credible protocol analysis. The criticality is defined as a combination of network performance metrics and critical functions' coverage. The proposed solution is experimentally proved to obtain accurate evaluation results with less testing effort by generating high-quality testing scenarios. Generated test scenarios will serve as BiTs for the network simulator. The quality of the test scenarios is evaluated from three perspectives: (i) code coverage, (ii) mutation score and (iii) testing effort. In this work, we implemented the testing framework in NS2, but it can be extended to any other simulation environment.
ISSN: 2472-9647
Aigner, Andreas, Khelil, Abdelmajid.  2020.  A Semantic Model-Based Security Engineering Framework for Cyber-Physical Systems. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1826—1833.
The coupling of safety-relevant embedded- and cyber-space components to build Cyber-Physical Systems (CPS) extends the functionality and quality in many business domains, while also creating new ones. Prime examples like Internet of Things and Industry 4.0 enable new technologies and extend the service capabilities of physical entities by building a universe of connected devices. In addition to higher complexity, the coupling of these heterogeneous systems results in many new challenges, which should be addressed by engineers and administrators. Here, security represents a major challenge, which may be well addressed in cyber-space engineering, but less in embedded system or CPS design. Although model-based engineering provides significant benefits for system architects, like reducing complexity and automated analysis, as well as being considered as standard methodology in embedded systems design, the aspect of security may not have had a major role in traditional engineering concepts. Especially the characteristics of CPS, as well as the coupling of safety-relevant (physical) components with high-scalable entities of the cyber-space domain have an enormous impact on the overall level of security, based on the introduced side effects and uncertainties. Therefore, we aim to define a model-based security-engineering framework, which is tailored to the needs of CPS engineers. Hereby, we focus on the actual modeling process, the evaluation of security, as well as quantitatively expressing security of a deployed CPS. Overall and in contrast to other approaches, we shift the engineering concepts on a semantic level, which allows to address the proposed challenges in CPS in the most efficient way.
Aigner, Andreas, Khelil, Abdelmajid.  2020.  A Scoring System to Efficiently Measure Security in Cyber-Physical Systems. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1141—1145.
The importance of Cyber-Physical Systems (CPS) gains more and more weight in our daily business and private life. Although CPS build the backbone for major trends, like Industry 4.0 and connected vehicles, they also propose many new challenges. One major challenge can be found in achieving a high level of security within such highly connected environments, in which an unpredictable number of heterogeneous systems with often-distinctive characteristics interact with each other. In order to develop high-level security solutions, system designers must eventually know the current level of security of their specification. To this end, security metrics and scoring frameworks are essential, as they quantitatively express security of a given design or system. However, existing solutions may not be able to handle the proposed challenges of CPS, as they mainly focus on one particular system and one specific attack. Therefore, we aim to elaborate a security scoring mechanism, which can efficiently be used in CPS, while considering all essential information. We break down each system within the CPS into its core functional blocks and analyze a variety of attacks in terms of exploitability, scalability of attacks, as well as potential harm to targeted assets. With this approach, we get an overall assessment of security for the whole CPS, as it integrates the security-state of all interacting systems. This allows handling the presented complexity in CPS in a more efficient way, than existing solutions.
2021-07-27
Reviriego, Pedro, Rottenstreich, Ori.  2020.  Pollution Attacks on Counting Bloom Filters for Black Box Adversaries. 2020 16th International Conference on Network and Service Management (CNSM). :1–7.
The wide adoption of Bloom filters makes their security an important issue to be addressed. For example, an attacker can increase their error rate through polluting and eventually saturating the filter by inserting elements that set to one a large number of positions in the filter. This is known as a pollution attack and requires that the attacker knows the hash functions used to construct the filter. Such information is not available in many practical settings and in addition a simple protection can be achieved through using a random salt in the hash functions. The same pollution attacks can also be done to counting Bloom filters that in addition to insertions and lookups support removals. This paper considers pollution attacks on counting Bloom filters. We describe two novel pollution attacks that do not require any knowledge of the counting Bloom filter implementation details and evaluate them. These methods show that a counting Bloom filter is vulnerable to pollution attacks even when the attacker has only access to the filter as a black box to perform insertions, removals, and lookups.
2021-06-02
Applebaum, Benny, Kachlon, Eliran, Patra, Arpita.  2020.  The Round Complexity of Perfect MPC with Active Security and Optimal Resiliency. 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS). :1277—1284.
In STOC 1988, Ben-Or, Goldwasser, and Wigderson (BGW) established an important milestone in the fields of cryptography and distributed computing by showing that every functionality can be computed with perfect (information-theoretic and error-free) security at the presence of an active (aka Byzantine) rushing adversary that controls up to n/3 of the parties. We study the round complexity of general secure multiparty computation in the BGW model. Our main result shows that every functionality can be realized in only four rounds of interaction, and that some functionalities cannot be computed in three rounds. This completely settles the round-complexity of perfect actively-secure optimally-resilient MPC, resolving a long line of research. Our lower-bound is based on a novel round-reduction technique that allows us to lift existing three-round lower-bounds for verifiable secret sharing to four-round lower-bounds for general MPC. To prove the upper-bound, we develop new round-efficient protocols for computing degree-2 functionalities over large fields, and establish the completeness of such functionalities. The latter result extends the recent completeness theorem of Applebaum, Brakerski and Tsabary (TCC 2018, Eurocrypt 2019) that was limited to the binary field.
2021-05-25
Zhang, ZhiShuo, Zhang, Wei, Qin, Zhiguang.  2020.  Multi-Authority CP-ABE with Dynamical Revocation in Space-Air-Ground Integrated Network. 2020 International Conference on Space-Air-Ground Computing (SAGC). :76–81.
Space-air-ground integrated network (SAGIN) is emerged as a versatile computing and traffic architecture in recent years. Though SAGIN brings many significant benefits for modern communication and computing services, there are many unprecedented challenges in SAGIN. The one critical challenge in SAGIN is the data security. In SAGIN, because the data will be stored in cleartext on cloud, the sensitive data may suffer from the illegal access by the unauthorized users even the untrusted cloud servers (CSs). Ciphertext-policy attribute-based encryption (CP-ABE), which is a type of attribute-based encryption (ABE), has been regarded as a promising solution to the critical challenge of the data security on cloud. But there are two main blemishes in traditional CP-ABE. The first one is that there is only one attribute authority (AA) in CP-ABE. If the single AA crashs down, the whole system will be shut down. The second one is that the AA cannot effectively manage the life cycle of the users’ private keys. If a user on longer has one attribute, the AA cannot revoke the user’s private key of this attribute. This means the user can still decrypt some ciphertexts using this invalid attribute. In this paper, to solve the two flaws mentioned above, we propose a multi-authority CP-ABE (MA-CP-ABE) scheme with the dynamical key revocation (DKR). Our key revocation supports both user revocation and attribute revocation. And the our revocation is time friendly. What’s more, by using our dynamically tag-based revocation algorithm, AAs can dynamically and directly re-enable or revoke the invalid attributes to users. Finally, by evaluating and implementing our scheme, we can observe that our scheme is more comprehensive and practical for cloud applications in SAGIN.
Abbas, Syed Ghazanfar, Hashmat, Fabiha, Shah, Ghalib A..  2020.  A Multi-layer Industrial-IoT Attack Taxonomy: Layers, Dimensions, Techniques and Application. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1820—1825.

Industrial IoT (IIoT) is a specialized subset of IoT which involves the interconnection of industrial devices with ubiquitous control and intelligent processing services to improve industrial system's productivity and operational capability. In essence, IIoT adapts a use-case specific architecture based on RFID sense network, BLE sense network or WSN, where heterogeneous industrial IoT devices can collaborate with each other to achieve a common goal. Nonetheless, most of the IIoT deployments are brownfield in nature which involves both new and legacy technologies (SCADA (Supervisory Control and Data Acquisition System)). The merger of these technologies causes high degree of cross-linking and decentralization which ultimately increases the complexity of IIoT systems and introduce new vulnerabilities. Hence, industrial organizations becomes not only vulnerable to conventional SCADA attacks but also to a multitude of IIoT specific threats. However, there is a lack of understanding of these attacks both with respect to the literature and empirical evaluation. As a consequence, it is infeasible for industrial organizations, researchers and developers to analyze attacks and derive a robust security mechanism for IIoT. In this paper, we developed a multi-layer taxonomy of IIoT attacks by considering both brownfield and greenfield architecture of IIoT. The taxonomy consists of 11 layers 94 dimensions and approximately 100 attack techniques which helps to provide a holistic overview of the incident attack pattern, attack characteristics and impact on industrial system. Subsequently, we have exhibited the practical relevance of developed taxonomy by applying it to a real-world use-case. This research will benefit researchers and developers to best utilize developed taxonomy for analyzing attack sequence and to envisage an efficient security platform for futuristic IIoT applications.

2021-05-13
Zhang, Yaqin, Ma, Duohe, Sun, Xiaoyan, Chen, Kai, Liu, Feng.  2020.  WGT: Thwarting Web Attacks Through Web Gene Tree-based Moving Target Defense. 2020 IEEE International Conference on Web Services (ICWS). :364–371.
Moving target defense (MTD) suggests a game-changing way of enhancing web security by increasing uncertainty and complexity for attackers. A good number of web MTD techniques have been investigated to counter various types of web attacks. However, in most MTD techniques, only fixed attributes of the attack surface are shifted, leaving the rest exploitable by the attackers. Currently, there are few mechanisms to support the whole attack surface movement and solve the partial coverage problem, where only a fraction of the possible attributes shift in the whole attack surface. To address this issue, this paper proposes a Web Gene Tree (WGT) based MTD mechanism. The key point is to extract all potential exploitable key attributes related to vulnerabilities as web genes, and mutate them using various MTD techniques to withstand various attacks. Experimental results indicate that, by randomly shifting web genes and diversely inserting deceptive ones, the proposed WGT mechanism outperforms other existing schemes and can significantly improve the security of web applications.
Everson, Douglas, Cheng, Long.  2020.  Network Attack Surface Simplification for Red and Blue Teams. 2020 IEEE Secure Development (SecDev). :74–80.
Network port scans are a key first step to developing a true understanding of a network-facing attack surface. However in large-scale networks, the data resulting from such scans can be too numerous for Red Teams to process for manual and semiautomatic testing. Indiscriminate port scans can also compromise a Red Team seeking to quickly gain a foothold on a network. A large attack surface can even complicate Blue Team activities like threat hunting. In this paper we provide a cluster analysis methodology designed to group similar hosts to reduce security team workload and Red Team observability. We also measure the Internet-facing network attack surface of 13 organizations by clustering their hosts based on similarity. Through a case study we demonstrate how the output of our clustering technique provides new insight to both Red and Blue Teams, allowing them to quickly identify potential high-interest points on the attack surface.
2021-05-05
Tabiban, Azadeh, Jarraya, Yosr, Zhang, Mengyuan, Pourzandi, Makan, Wang, Lingyu, Debbabi, Mourad.  2020.  Catching Falling Dominoes: Cloud Management-Level Provenance Analysis with Application to OpenStack. 2020 IEEE Conference on Communications and Network Security (CNS). :1—9.

The dynamicity and complexity of clouds highlight the importance of automated root cause analysis solutions for explaining what might have caused a security incident. Most existing works focus on either locating malfunctioning clouds components, e.g., switches, or tracing changes at lower abstraction levels, e.g., system calls. On the other hand, a management-level solution can provide a big picture about the root cause in a more scalable manner. In this paper, we propose DOMINOCATCHER, a novel provenance-based solution for explaining the root cause of security incidents in terms of management operations in clouds. Specifically, we first define our provenance model to capture the interdependencies between cloud management operations, virtual resources and inputs. Based on this model, we design a framework to intercept cloud management operations and to extract and prune provenance metadata. We implement DOMINOCATCHER on OpenStack platform as an attached middleware and validate its effectiveness using security incidents based on real-world attacks. We also evaluate the performance through experiments on our testbed, and the results demonstrate that DOMINOCATCHER incurs insignificant overhead and is scalable for clouds.

2021-05-03
Naik, Nikhil, Nuzzo, Pierluigi.  2020.  Robustness Contracts for Scalable Verification of Neural Network-Enabled Cyber-Physical Systems. 2020 18th ACM-IEEE International Conference on Formal Methods and Models for System Design (MEMOCODE). :1–12.
The proliferation of artificial intelligence based systems in all walks of life raises concerns about their safety and robustness, especially for cyber-physical systems including multiple machine learning components. In this paper, we introduce robustness contracts as a framework for compositional specification and reasoning about the robustness of cyber-physical systems based on neural network (NN) components. Robustness contracts can encompass and generalize a variety of notions of robustness which were previously proposed in the literature. They can seamlessly apply to NN-based perception as well as deep reinforcement learning (RL)-enabled control applications. We present a sound and complete algorithm that can efficiently verify the satisfaction of a class of robustness contracts on NNs by leveraging notions from Lagrangian duality to identify system configurations that violate the contracts. We illustrate the effectiveness of our approach on the verification of NN-based perception systems and deep RL-based control systems.
Mishra, Shachee, Polychronakis, Michalis.  2020.  Saffire: Context-sensitive Function Specialization against Code Reuse Attacks. 2020 IEEE European Symposium on Security and Privacy (EuroS P). :17–33.
The sophistication and complexity of recent exploitation techniques, which rely on memory disclosure and whole-function reuse to bypass address space layout randomization and control flow integrity, is indicative of the effect that the combination of exploit mitigations has in challenging the construction of reliable exploits. In addition to software diversification and control flow enforcement, recent efforts have focused on the complementary approach of code and API specialization to restrict further the critical operations that an attacker can perform as part of a code reuse exploit. In this paper we propose Saffire, a compiler-level defense against code reuse attacks. For each calling context of a critical function, Saffire creates a specialized and hardened replica of the function with a restricted interface that can accommodate only that particular invocation. This is achieved by applying staticargumentbinding, to eliminate arguments with static values and concretize them within the function body, and dynamicargumentbinding, which applies a narrow-scope form of data flow integrity to restrict the acceptable values of arguments that cannot be statically derived. We have implemented Saffire on top of LLVM, and applied it to a set of 11 applications, including Nginx, Firefox, and Chrome. The results of our experimental evaluation with a set of 17 real-world ROP exploits and three whole-function reuse exploits demonstrate the effectiveness of Saffire in preventing these attacks while incurring a negligible runtime overhead.
2021-04-27
Mladenova, T..  2020.  Software Quality Metrics – Research, Analysis and Recommendation. 2020 International Conference Automatics and Informatics (ICAI). :1—5.

Software Quality Testing has always been a crucial part of the software development process and lately, there has been a rise in the usage of testing applications. While a well-planned and performed test, regardless of its nature - automated or manual, is a key factor when deciding on the results of the test, it is often not enough to give a more deep and thorough view of the whole process. That can be achieved with properly selected software metrics that can be used for proper risk assessment and evaluation of the development.This paper considers the most commonly used metrics when measuring a performed test and examines metrics that can be applied in the development process.

Masmali, O., Badreddin, O..  2020.  Comprehensive Model-Driven Complexity Metrics for Software Systems. 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C). :674—675.

Measuring software complexity is key in managing the software lifecycle and in controlling its maintenance. While there are well-established and comprehensive metrics to measure the complexity of the software code, assessment of the complexity of software designs remains elusive. Moreover, there are no clear guidelines to help software designers chose alternatives that reduce design complexity, improve design comprehensibility, and improve the maintainability of the software. This paper outlines a language independent approach to measuring software design complexity using objective and deterministic metrics. The paper outlines the metrics for two major software design notations; UML Class Diagrams and UML State Machines. The approach is based on the analysis of the design elements and their mutual interactions. The approach can be extended to cover other UML design notations.

Ding, K., Meng, Z., Yu, Z., Ju, Z., Zhao, Z., Xu, K..  2020.  Photonic Compressive Sampling of Sparse Broadband RF Signals using a Multimode Fiber. 2020 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC). :1–3.
We propose a photonic compressive sampling scheme based on multimode fiber for radio spectrum sensing, which shows high accuracy and stability, and low complexity and cost. Pulse overlapping is utilized for a fast detection. © 2020 The Author(s).
2021-03-22
Ban, T. Q., Nguyen, T. T. T., Long, V. T., Dung, P. D., Tung, B. T..  2020.  A Benchmarking of the Effectiveness of Modular Exponentiation Algorithms using the library GMP in C language. 2020 International Conference on Computational Intelligence (ICCI). :237–241.
This research aims to implement different modular exponentiation algorithms and evaluate the average complexity and compare it to the theoretical value. We use the library GMP to implement seven modular exponentiation algorithms. They are Left-to-right Square and Multiply, Right-to-left Square and Multiply, Left-to-right Signed Digit Square, and Multiply Left-to-right Square and Multiply Always Right-to-left Square and Multiply Always, Montgomery Ladder and Joye Ladder. For some exponent bit length, we choose 1024 bits and execute each algorithm on many exponent values and count the average numbers of squares and the average number of multiplications. Whenever relevant, our programs will check the consistency relations between the registers at the end of the exponentiation.
2021-03-15
Xiong, J., Zhang, L..  2020.  Simplified Calculation of Bhattacharyya Parameters in Polar Codes. 2020 IEEE 14th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :169–173.
The construction of polar code refers to selecting K "most reliable polarizing channels" in N polarizing channels to WN(1)transmit information bits. For non-systematic polar code, Arikan proposed a method to measure the channel reliability for BEC channel, which is called Bhattacharyya Parameter method. The calculated complexity of this method is O(N) . In this paper, we find the complementarity of Bhattacharyya Parameter. According to the complementarity, the code construction under a certain channel condition can be quickly deduced from the complementary channel condition.
2021-03-09
Adhikari, M., Panda, P. K., Chattopadhyay, S., Majumdar, S..  2020.  A Novel Group-Based Authentication and Key Agreement Protocol for IoT Enabled LTE/LTE–A Network. 2020 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET). :168—172.

This paper deals with novel group-based Authentication and Key Agreement protocol for Internet of Things(IoT) enabled LTE/LTE-A network to overcome the problems of computational overhead, complexity and problem of heterogeneous devices, where other existing methods are lagging behind in attaining security requirements and computational overhead. In this work, two Groups are created among Machine Type Communication Devices (MTCDs) on the basis of device type to reduce complexity and problems of heterogeneous devices. This paper fulfills all the security requirements such as preservation, mutual authentication, confidentiality. Bio-metric authentication has been used to enhance security level of the network. The security and performance analysis have been verified through simulation results. Moreover, the performance of the proposed Novel Group-Based Authentication and key Agreement(AKA) Protocol is analyzed with other existing IoT enabled LTE/LTE-A protocol.

2021-03-01
Golagha, M., Pretschner, A., Briand, L. C..  2020.  Can We Predict the Quality of Spectrum-based Fault Localization? 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). :4–15.
Fault localization and repair are time-consuming and tedious. There is a significant and growing need for automated techniques to support such tasks. Despite significant progress in this area, existing fault localization techniques are not widely applied in practice yet and their effectiveness varies greatly from case to case. Existing work suggests new algorithms and ideas as well as adjustments to the test suites to improve the effectiveness of automated fault localization. However, important questions remain open: Why is the effectiveness of these techniques so unpredictable? What are the factors that influence the effectiveness of fault localization? Can we accurately predict fault localization effectiveness? In this paper, we try to answer these questions by collecting 70 static, dynamic, test suite, and fault-related metrics that we hypothesize are related to effectiveness. Our analysis shows that a combination of only a few static, dynamic, and test metrics enables the construction of a prediction model with excellent discrimination power between levels of effectiveness (eight metrics yielding an AUC of .86; fifteen metrics yielding an AUC of.88). The model hence yields a practically useful confidence factor that can be used to assess the potential effectiveness of fault localization. Given that the metrics are the most influential metrics explaining the effectiveness of fault localization, they can also be used as a guide for corrective actions on code and test suites leading to more effective fault localization.
2021-02-22
Rivera, S., Fei, Z., Griffioen, J..  2020.  POLANCO: Enforcing Natural Language Network Policies. 2020 29th International Conference on Computer Communications and Networks (ICCCN). :1–9.
Network policies govern the use of an institution's networks, and are usually written in a high-level human-readable natural language. Normally these policies are enforced by low-level, technically detailed network configurations. The translation from network policies into network configurations is a tedious, manual and error-prone process. To address this issue, we propose a new intermediate language called POlicy LANguage for Campus Operations (POLANCO), which is a human-readable network policy definition language intended to approximate natural language. Because POLANCO is a high-level language, the translation from natural language policies to POLANCO is straightforward. Despite being a high-level human readable language, POLANCO can be used to express network policies in a technically precise way so that policies written in POLANCO can be automatically translated into a set of software defined networking (SDN) rules and actions that enforce the policies. Moreover, POLANCO is capable of incorporating information about the current network state, reacting to changes in the network and adjusting SDN rules to ensure network policies continue to be enforced correctly. We present policy examples found on various public university websites and show how they can be written as simplified human-readable statements using POLANCO and how they can be automatically translated into SDN rules that correctly enforce these policies.