Biblio

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2017-03-20
Dormann, Will.  Submitted.  Google Authentication Risks on iOS. Proceedings of the 1st International Workshop on Mobile Development. :3–5.

The Google Identity Platform is a system that allows a user to sign in to applications and other services by using a Google account. Google Sign-In is one such method for providing one’s identity to the Google Identity Platform. Google Sign-In is available for Android applications and iOS applications, as well as for websites and other devices. Users of Google Sign-In find that it integrates well with the Android platform, but iOS users (iPhone, iPad, etc.) do not have the same experience. The user experience when logging in to a Google account on an iOS application can not only be more tedious than the Android experience, but it also conditions users to engage in behaviors that put the information in their Google accounts at risk.

2020-04-13
Khurana, Madhu, Malik, Priyanka, Puneet, Shweta.  2020.  Network Security Monitoring (NSM): Can it be Effective in a World with Encrypted Traffic? 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM). :140–144.
HTTPS is gaining widespread popularity for secure transactions. Most popular sites have made default choice as HTTPS. This development of encrypted traffic has brought in new challenges in the areas of network security monitoring and analysis. This paper makes a survey through various study done in the area on novel approaches for identification and investigating HTTPS traffic and its effect on network security monitoring. This work makes a complete analysis and evaluation of HTTPS protocol-is it ensuring security or are we entering in a vicious cycle of finding weaknesses and tryingto fill the gaps in Network security Monitoring. There are couple of vacuums that exist along with encrypted data, namely firewalls, IDS becoming blind to data being exchanged, enhancing vulnerabilities by making it tough to implement security policy and probability of malicious activities hidingin the ciphered traffic. Most of the current techniques namely DPI to port based to IP address to DNS to SNI filtering is prone to be ineffective in front of HTTPS traffic. The emphasis is upon the new ways to explore the expanding HTTPS volume with security breaches to cover new challenges related to Network Security Monitoring. Data collected from couple of up to date research and their conclusion hasbeen discussed to provide a brief overview so as to provide the reader with an in-depth understanding of the research progress in thisarea.
2020-04-06
Fouchal, Hacène, Ninet, Alain.  2020.  Partial Signature for Cooperative Intelligent Transport Systems. 2020 International Conference on Computing, Networking and Communications (ICNC). :586–590.
On C-ITS (Cooperative Intelligent Transport Systems) vehicles send and receive sensitive messages informing about events on roads (accidents, traffic jams, etc,..). The authentication of these messages is highly recommended in order to increase the users confidence about this system. This authentication ensures that only messages coming from trusted vehicles are accepted by receivers. An adapted PKI (Public Key Infrastructure) for C-ITS provides certificates for each vehicle. The certificate will be used to sign messages. This principle is used within deployed C-ITS solutions over the world. This solution is easy to implement but has one major flaw: each message needs to be sent with its signature and its certificate. The size of the message to send becomes high. In the meantime, for many C-ITS use cases, each message is sent many times for robustness reasons. The communication channel could be overloaded. In this paper, we propose to split the signature into some equal parts. When a message has to be sent, it will be sent with one of these parts. A receiver will save the received message with its actual part. For each reception, it will collect the remaining signature parts until all the signature parts are received. Our solution is implemented in a C-ITS architecture working through Bluetooth protocol using the advertising model. The solution is applicable for vehicle speeds reaching 130 km/h. We have proved, through a set of real experimentations, that our solution is possible.
2020-03-23
Choi, Jungyong, Shin, WoonSeob, Kim, Jonghyun, Kim, Ki-Hyung.  2020.  Random Seed Generation For IoT Key Generation and Key Management System Using Blockchain. 2020 International Conference on Information Networking (ICOIN). :663–665.
Recently, the Internet of Things (IoT) is growing rapidly. IoT sensors are attached to various devices, and information is detected, collected and utilized through various wired and wireless communication environments. As the IoT is used in various places, IoT devices face a variety of malicious attacks such as MITM and reverse engineering. To prevent these, encryption is required for device-to-device communication, and keys required for encryption must be properly managed. We propose a scheme to generate seed needed for key generation and a scheme to manage the public key using blockchain.
2020-04-06
Chu, YeonSung, Kim, Jae Min, Lee, YoonJick, Shim, SungHoon, Huh, Junho.  2020.  SS-DPKI: Self-Signed Certificate Based Decentralized Public Key Infrastructure for Secure Communication. 2020 IEEE International Conference on Consumer Electronics (ICCE). :1–6.
Currently, the most commonly used scheme for identity authentication on the Internet is based on asymmetric cryptography and the use of a centralized model. The centralized model needs a Certificate Authority (CA) as a trusted third party and a trust chain of CA. However, CA-based PKI is weak in the single point of failure and certificate transparency. Our system, called SS-DPKI, propose a public and decentralized PKI system model. We describe a detailed scheme as well as application to use decentralized PKI based secure communication. Our proposal prevents storage overhead on the data size of transactions and provide reasonable certificate verification time.
Alamleh, Hosam, AlQahtani, Ali Abdullah S..  2020.  Two Methods for Authentication Using Variable Transmission Power Patterns. 2020 10th Annual Computing and Communication Workshop and Conference (CCWC). :0355–0358.
In the last decade, the adoption of wireless systems has increased. These systems allow multiple devices to send data wirelessly using radio waves. Moreover, in some applications, authentication is done wirelessly by exchanging authentication data over the air as in wireless locks and keyless entry systems. On the other hand, most of the wireless devices today can control the radio frequency transmission power to optimize the system's performance and minimize interference. In this paper, we explore the possibility of modulating the radio frequency transmission power in wireless systems for authentication purposes and using it for source authentication. Furthermore, we propose two system models that perform authentication using variable power transmission patterns. Then, we discuss possible applications. Finally, we implement and test a prototype system using IEEE 802.11 (Wi-Fi) devices.
2020-08-03
Chowdhary, Ankur, Sengupta, Sailik, Alshamrani, Adel, Huang, Dijiang, Sabur, Abdulhakim.  2019.  Adaptive MTD Security using Markov Game Modeling. 2019 International Conference on Computing, Networking and Communications (ICNC). :577–581.
Large scale cloud networks consist of distributed networking and computing elements that process critical information and thus security is a key requirement for any environment. Unfortunately, assessing the security state of such networks is a challenging task and the tools used in the past by security experts such as packet filtering, firewall, Intrusion Detection Systems (IDS) etc., provide a reactive security mechanism. In this paper, we introduce a Moving Target Defense (MTD) based proactive security framework for monitoring attacks which lets us identify and reason about multi-stage attacks that target software vulnerabilities present in a cloud network. We formulate the multi-stage attack scenario as a two-player zero-sum Markov Game (between the attacker and the network administrator) on attack graphs. The rewards and transition probabilities are obtained by leveraging the expert knowledge present in the Common Vulnerability Scoring System (CVSS). Our framework identifies an attacker's optimal policy and places countermeasures to ensure that this attack policy is always detected, thus forcing the attacker to use a sub-optimal policy with higher cost.
2020-03-09
Perner, Cora, Kinkelin, Holger, Carle, Georg.  2019.  Adaptive Network Management for Safety-Critical Systems. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :25–30.
Present networks within safety-critical systems rely on complex and inflexible network configurations. New technologies such as software-defined networking are more dynamic and offer more flexibility, but due care needs to be exercised to ensure that safety and security are not compromised by incorrect configurations. To this end, this paper proposes the use of pre-generated and optimized configuration templates. These provide alternate routes for traffic considering availability, resilience and timing constraints where network components fail due to attacks or faults.To obtain these templates, two heuristics based on Dijkstra's algorithm and an optimization algorithm providing the maximum resilience were investigated. While the configurations obtained through optimization yield appropriate templates, the heuristics investigated are not suitable to obtain configuration templates, since they cannot fulfill all requirements.
2020-05-15
Fan, Renshi, Du, Gaoming, Xu, Pengfei, Li, Zhenmin, Song, Yukun, Zhang, Duoli.  2019.  An Adaptive Routing Scheme Based on Q-learning and Real-time Traffic Monitoring for Network-on-Chip. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :244—248.
In the Network on Chip (NoC), performance optimization has always been a research focus. Compared with the static routing scheme, dynamical routing schemes can better reduce the data of packet transmission latency under network congestion. In this paper, we propose a dynamical Q-learning routing approach with real-time monitoring of NoC. Firstly, we design a real-time monitoring scheme and the corresponding circuits to record the status of traffic congestion for NoC. Secondly, we propose a novel method of Q-learning. This method finds an optimal path based on the lowest traffic congestion. Finally, we dynamically redistribute network tasks to increase the packet transmission speed and balance the traffic load. Compared with the C-XY routing and DyXY routing, our method achieved improvement in terms of 25.6%-49.5% and 22.9%-43.8%.
2020-07-03
Adari, Suman Kalyan, Garcia, Washington, Butler, Kevin.  2019.  Adversarial Video Captioning. 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :24—27.
In recent years, developments in the field of computer vision have allowed deep learning-based techniques to surpass human-level performance. However, these advances have also culminated in the advent of adversarial machine learning techniques, capable of launching targeted image captioning attacks that easily fool deep learning models. Although attacks in the image domain are well studied, little work has been done in the video domain. In this paper, we show it is possible to extend prior attacks in the image domain to the video captioning task, without heavily affecting the video's playback quality. We demonstrate our attack against a state-of-the-art video captioning model, by extending a prior image captioning attack known as Show and Fool. To the best of our knowledge, this is the first successful method for targeted attacks against a video captioning model, which is able to inject 'subliminal' perturbations into the video stream, and force the model to output a chosen caption with up to 0.981 cosine similarity, achieving near-perfect similarity to chosen target captions.
2020-05-18
Sharma, Sarika, Kumar, Deepak.  2019.  Agile Release Planning Using Natural Language Processing Algorithm. 2019 Amity International Conference on Artificial Intelligence (AICAI). :934–938.
Once the requirement is gathered in agile, it is broken down into smaller pre-defined format called user stories. These user stories are then scoped in various sprint releases and delivered accordingly. Release planning in Agile becomes challenging when the number of user stories goes up in hundreds. In such scenarios it is very difficult to manually identify similar user stories and package them together into a release. Hence, this paper suggests application of natural language processing algorithms for identifying similar user stories and then scoping them into a release This paper takes the approach to build a word corpus for every project release identified in the project and then to convert the provided user stories into a vector of string using Java utility for calculating top 3 most occurring words from the given project corpus in a user story. Once all the user stories are represented as vector array then by using RV coefficient NLP algorithm the user stories are clustered into various releases of the software project. Using the proposed approach, the release planning for large and complex software engineering projects can be simplified resulting into efficient planning in less time. The automated commercial tools like JIRA and Rally can be enhanced to include suggested algorithms for managing release planning in Agile.
2020-07-06
Cerotti, D., Codetta-Raiteri, D., Egidi, L., Franceschinis, G., Portinale, L., Dondossola, G., Terruggia, R..  2019.  Analysis and Detection of Cyber Attack Processes targeting Smart Grids. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). :1–5.
This paper proposes an approach based on Bayesian Networks to support cyber security analysts in improving the cyber-security posture of the smart grid. We build a system model that exploits real world context information from both Information and Operational Technology environments in the smart grid, and we use it to demonstrate sample predictive and diagnostic analyses. The innovative contribution of this work is in the methodology capability of capturing the many dependencies involved in the assessment of security threats, and of supporting the security analysts in planning defense and detection mechanisms for energy digital infrastructures.
2020-01-21
Haddouti, Samia El, Ech-Cherif El Kettani, M. Dafir.  2019.  Analysis of Identity Management Systems Using Blockchain Technology. 2019 International Conference on Advanced Communication Technologies and Networking (CommNet). :1–7.
The emergence of Blockchain technology as the biggest innovations of the 21stcentury, has given rise to new concepts of Identity Management to deal with the privacy and security challenges on the one hand, and to enhance the decentralization and user control in transactions on Blockchain infrastructures on the other hand. This paper investigates and gives analysis of the most popular Identity Management Systems using Blockchain: uPort, Sovrin, and ShoCard. It then evaluates them under a set of features of digital identity that characterizes the successful of an Identity Management solution. The result of the comparative analysis is presented in a concise way to allow readers to find out easily which systems satisfy what requirements in order to select the appropriate one to fit into a specific scenario.
2020-03-23
Hyunki-Kim, Jinhyeok-Oh, Changuk-Jang, Okyeon-Yi, Juhong-Han, Hansaem-Wi, Chanil-Park.  2019.  Analysis of the Noise Source Entropy Used in OpenSSL’s Random Number Generation Mechanism. 2019 International Conference on Information and Communication Technology Convergence (ICTC). :59–62.
OpenSSL is an open source library that implements the Secure Socket Layer (SSL), a security protocol used by the TCP/IP layer. All cryptographic systems require random number generation for many reasons, such as cryptographic key generation and protocol challenge/response, OpenSSL is also the same. OpenSSL can be run on a variety of operating systems. especially when generating random numbers on Unix-like operating systems, it can use /dev /(u)random [6], as a seed to add randomness. In this paper, we analyze the process provided by OpenSSL when random number generation is required. We also provide considerations for application developers and OpenSSL users to use /dev/urandom and real-time clock (nanoseconds of timespec structure) as a seed to generate cryptographic random numbers in the Unix family.
2020-03-02
Arifeen, Md Murshedul, Islam, Al Amin, Rahman, Md Mustafizur, Taher, Kazi Abu, Islam, Md.Maynul, Kaiser, M Shamim.  2019.  ANFIS based Trust Management Model to Enhance Location Privacy in Underwater Wireless Sensor Networks. 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE). :1–6.
Trust management is a promising alternative solution to different complex security algorithms for Underwater Wireless Sensor Networks (UWSN) applications due to its several resource constraint behaviour. In this work, we have proposed a trust management model to improve location privacy of the UWSN. Adaptive Neuro Fuzzy Inference System (ANFIS) has been exploited to evaluate trustworthiness of a sensor node. Also Markov Decision Process (MDP) has been considered. At each state of the MDP, a sensor node evaluates trust behaviour of forwarding node utilizing the FIS learning rules and selects a trusted node. Simulation has been conducted in MATLAB and simulation results show that the detection accuracy of trustworthiness is 91.2% which is greater than Knowledge Discovery and Data Mining (KDD) 99 intrusion detection based dataset. So, in our model 91.2% trustworthiness is necessary to be a trusted node otherwise it will be treated as a malicious or compromised node. Our proposed model can successfully eliminate the possibility of occurring any compromised or malicious node in the network.
2020-07-13
Mahmood, Shah.  2019.  The Anti-Data-Mining (ADM) Framework - Better Privacy on Online Social Networks and Beyond. 2019 IEEE International Conference on Big Data (Big Data). :5780–5788.
The unprecedented and enormous growth of cloud computing, especially online social networks, has resulted in numerous incidents of the loss of users' privacy. In this paper, we provide a framework, based on our anti-data-mining (ADM) principle, to enhance users' privacy against adversaries including: online social networks; search engines; financial terminal providers; ad networks; eavesdropping governments; and other parties who can monitor users' content from the point where the content leaves users' computers to within the data centers of these information accumulators. To achieve this goal, our framework proactively uses the principles of suppression of sensitive data and disinformation. Moreover, we use social-bots in a novel way for enhanced privacy and provide users' with plausible deniability for their photos, audio, and video content uploaded online.
Ghosh, Debanjana, Chatterjee, Soumyajit, Kothari, Vasudha, Kumar, Aakash, Nair, Mahesh, Lokesh, Ella.  2019.  An application of Li-Fi based Wireless Communication System using Visible Light Communication. 2019 International Conference on Opto-Electronics and Applied Optics (Optronix). :1–3.
This paper attempts to clarify the concept and applications of Li-Fi technology. The current Wi-Fi network use Radio Frequency waves, but the usage of the available RF spectrum is limited. Therefore a new technology, Li-Fi has come into picture. Li-Fi is a recently developed technology. This paper explains how array of LEDs are used to transmit data in the visible light spectrum. This technology has advantages like security, increased accessible spectrum, low latency efficiency and much higher speed as compared to Wi- Fi. The aim of this research paper is to design a Li-Fi transceiver using Arduino which is able to transmit and receive data in binary format. The software coding is done in Arduino- Uno platform. Successful transmission and reception of data(alphanumeric) has been done.
2020-03-23
Xuewei, Feng, Dongxia, Wang, Zhechao, Lin.  2019.  An Approach of Code Pointer Hiding Based on a Resilient Area. 2019 Seventh International Conference on Advanced Cloud and Big Data (CBD). :204–209.
Code reuse attacks can bypass the DEP mechanism effectively. Meanwhile, because of the stealthy of the operation, it becomes one of the most intractable threats while securing the information system. Although the security solutions of code randomization and diversity can mitigate the threat at a certain extent, attackers can bypass these solutions due to the high cost and coarsely granularity, and the memory disclosure vulnerability is another magic weapon which can be used by attackers to bypass these solutions. After analyzing the principle of memory disclosure vulnerability, we propose a novel code pointer hiding method based on a resilient area. We expatiate how to create the resilient area and achieve code pointer hiding from four aspects, namely hiding return addresses in data pages, hiding function pointers in data pages, hiding target pointers of instruction JUMP in code pages, and hiding target pointers of instruction CALL in code pages. This method can stop attackers from reading and analyzing pages in memory, which is a critical stage in finding and creating ROP chains while executing a code reuse attack. Lastly, we test the method contrastively, and the results show that the method is feasible and effective while defending against ROP attacks.
2020-04-10
Repetto, M., Carrega, A., Lamanna, G..  2019.  An architecture to manage security services for cloud applications. 2019 4th International Conference on Computing, Communications and Security (ICCCS). :1—8.
The uptake of virtualization and cloud technologies has pushed novel development and operation models for the software, bringing more agility and automation. Unfortunately, cyber-security paradigms have not evolved at the same pace and are not yet able to effectively tackle the progressive disappearing of a sharp security perimeter. In this paper, we describe a novel cyber-security architecture for cloud-based distributed applications and network services. We propose a security orchestrator that controls pervasive, lightweight, and programmable security hooks embedded in the virtual functions that compose the cloud application, pursuing better visibility and more automation in this domain. Our approach improves existing management practice for service orchestration, by decoupling the management of the business logic from that of security. We also describe the current implementation stage for a programmable monitoring, inspection, and enforcement framework, which represents the ground technology for the realization of the whole architecture.
2020-03-09
Li, Chi, Zhou, Min, Gu, Zuxing, Gu, Ming, Zhang, Hongyu.  2019.  Ares: Inferring Error Specifications through Static Analysis. 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). :1174–1177.
Misuse of APIs happens frequently due to misunderstanding of API semantics and lack of documentation. An important category of API-related defects is the error handling defects, which may result in security and reliability flaws. These defects can be detected with the help of static program analysis, provided that error specifications are known. The error specification of an API function indicates how the function can fail. Writing error specifications manually is time-consuming and tedious. Therefore, automatic inferring the error specification from API usage code is preferred. In this paper, we present Ares, a tool for automatic inferring error specifications for C code through static analysis. We employ multiple heuristics to identify error handling blocks and infer error specifications by analyzing the corresponding condition logic. Ares is evaluated on 19 real world projects, and the results reveal that Ares outperforms the state-of-the-art tool APEx by 37% in precision. Ares can also identify more error specifications than APEx. Moreover, the specifications inferred from Ares help find dozens of API-related bugs in well-known projects such as OpenSSL, among them 10 bugs are confirmed by developers. Video: https://youtu.be/nf1QnFAmu8Q. Repository: https://github.com/lc3412/Ares.
2019-12-30
Kee, Ruitao, Sie, Jovan, Wong, Rhys, Yap, Chern Nam.  2019.  Arithmetic Circuit Homomorphic Encryption and Multiprocessing Enhancements. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–5.
This is a feasibility study on homomorphic encryption using the TFHE library [1] in daily computing using cloud services. A basic set of arithmetic operations namely - addition, subtraction, multiplication and division were created from the logic gates provide. This research peeks into the impact of logic gates on these operations such as latency of the gates and the operation itself. Multiprocessing enhancement were done for multiplication operation using MPI and OpenMP to reduce latency.
2020-05-18
Chen, Long.  2019.  Assertion Detection in Clinical Natural Language Processing: A Knowledge-Poor Machine Learning Approach. 2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT). :37–40.
Natural language processing (NLP) have been recently used to extract clinical information from free text in Electronic Health Record (EHR). In clinical NLP one challenge is that the meaning of clinical entities is heavily affected by assertion modifiers such as negation, uncertain, hypothetical, experiencer and so on. Incorrect assertion assignment could cause inaccurate diagnosis of patients' condition or negatively influence following study like disease modeling. Thus, clinical NLP systems which can detect assertion status of given target medical findings (e.g. disease, symptom) in clinical context are highly demanded. Here in this work, we propose a deep-learning system based on word embedding, RNN and attention mechanism (more specifically: Attention-based Bidirectional Long Short-Term Memory networks) for assertion detection in clinical notes. Unlike previous state-of-art methods which require knowledge input or feature engineering, our system is a knowledge poor machine learning system and can be easily extended or transferred to other domains. The evaluation of our system on public benchmarking corpora demonstrates that a knowledge poor deep-learning system can also achieve high performance for detecting negation and assertions comparing to state-of-the-art systems.
2020-01-21
Rana, Rima, Zaeem, Razieh Nokhbeh, Barber, K. Suzanne.  2019.  An Assessment of Blockchain Identity Solutions: Minimizing Risk and Liability of Authentication. 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI). :26–33.
Personally Identifiable Information (PII) is often used to perform authentication and acts as a gateway to personal and organizational information. One weak link in the architecture of identity management services is sufficient to cause exposure and risk identity. Recently, we have witnessed a shift in identity management solutions with the growth of blockchain. Blockchain-the decentralized ledger system-provides a unique answer addressing security and privacy with its embedded immutability. In a blockchain-based identity solution, the user is given the control of his/her identity by storing personal information on his/her device and having the choice of identity verification document used later to create blockchain attestations. Yet, the blockchain technology alone is not enough to produce a better identity solution. The user cannot make informed decisions as to which identity verification document to choose if he/she is not presented with tangible guidelines. In the absence of scientifically created practical guidelines, these solutions and the choices they offer may become overwhelming and even defeat the purpose of providing a more secure identity solution.We analyze different PII options given to users for authentication on current blockchain-based solutions. Based on our Identity Ecosystem model, we evaluate these options and their risk and liability of exposure. Powered by real world data of about 6,000 identity theft and fraud stories, our model recommends some authentication choices and discourages others. Our work paves the way for a truly effective identity solution based on blockchain by helping users make informed decisions and motivating blockchain identity solution providers to introduce better options to their users.
2020-03-09
Nadir, Ibrahim, Ahmad, Zafeer, Mahmood, Haroon, Asadullah Shah, Ghalib, Shahzad, Farrukh, Umair, Muhammad, Khan, Hassam, Gulzar, Usman.  2019.  An Auditing Framework for Vulnerability Analysis of IoT System. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :39–47.
Introduction of IoT is a big step towards the convergence of physical and virtual world as everyday objects are connected to the internet nowadays. But due to its diversity and resource constraint nature, the security of these devices in the real world has become a major challenge. Although a number of security frameworks have been suggested to ensure the security of IoT devices, frameworks for auditing this security are rare. We propose an open-source framework to audit the security of IoT devices covering hardware, firmware and communication vulnerabilities. Using existing open-source tools, we formulate a modular approach towards the implementation of the proposed framework. Standout features in the suggested framework are its modular design, extensibility, scalability, tools integration and primarily autonomous nature. The principal focus of the framework is to automate the process of auditing. The paper further mentions some tools that can be incorporated in different modules of the framework. Finally, we validate the feasibility of our framework by auditing an IoT device using proposed toolchain.
2020-07-06
Xu, Zhiheng, Ng, Daniel Jun Xian, Easwaran, Arvind.  2019.  Automatic Generation of Hierarchical Contracts for Resilience in Cyber-Physical Systems. 2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). :1–11.
With the growing scale of Cyber-Physical Systems (CPSs), it is challenging to maintain their stability under all operating conditions. How to reduce the downtime and locate the failures becomes a core issue in system design. In this paper, we employ a hierarchical contract-based resilience framework to guarantee the stability of CPS. In this framework, we use Assume Guarantee (A-G) contracts to monitor the non-functional properties of individual components (e.g., power and latency), and hierarchically compose such contracts to deduce information about faults at the system level. The hierarchical contracts enable rapid fault detection in large-scale CPS. However, due to the vast number of components in CPS, manually designing numerous contracts and the hierarchy becomes challenging. To address this issue, we propose a technique to automatically decompose a root contract into multiple lower-level contracts depending on I/O dependencies between components. We then formulate a multi-objective optimization problem to search the optimal parameters of each lower-level contract. This enables automatic contract refinement taking into consideration the communication overhead between components. Finally, we use a case study from the manufacturing domain to experimentally demonstrate the benefits of the proposed framework.