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2021-04-27
Khalid, O., Senthilananthan, S..  2020.  A review of data analytics techniques for effective management of big data using IoT. 2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA). :1—10.
IoT and big data are energetic technology of the world for quite a time, and both of these have become a necessity. On the one side where IoT is used to connect different objectives via the internet, the big data means having a large number of the set of structured, unstructured, and semi-structured data. The device used for processing based on the tools used. These tools help provide meaningful information used for effective management in different domains. Some of the commonly faced issues with the inadequate about the technologies are related to data privacy, insufficient analytical capabilities, and this issue is faced by in different domains related to the big data. Data analytics tools help discover the pattern of data and consumer preferences which is resulting in better decision making for the organizations. The major part of this work is to review different types of data analytics techniques for the effective management of big data using IoT. For the effective management of the ABD solution collection, analysis and control are used as the components. Each of the ingredients is described to find an effective way to manage big data. These components are considered and used in the validation criteria. The solution of effective data management is a stage towards the management of big data in IoT devices which will help the user to understand different types of elements of data management.
2021-01-28
Collins, B. C., Brown, P. N..  2020.  Exploiting an Adversary’s Intentions in Graphical Coordination Games. 2020 American Control Conference (ACC). :4638—4643.

How does information regarding an adversary's intentions affect optimal system design? This paper addresses this question in the context of graphical coordination games where an adversary can indirectly influence the behavior of agents by modifying their payoffs. We study a situation in which a system operator must select a graph topology in anticipation of the action of an unknown adversary. The designer can limit her worst-case losses by playing a security strategy, effectively planning for an adversary which intends maximum harm. However, fine-grained information regarding the adversary's intention may help the system operator to fine-tune the defenses and obtain better system performance. In a simple model of adversarial behavior, this paper asks how much a system operator can gain by fine-tuning a defense for known adversarial intent. We find that if the adversary is weak, a security strategy is approximately optimal for any adversary type; however, for moderately-strong adversaries, security strategies are far from optimal.

2020-11-30
Cheng, D., Zhou, X., Ding, Z., Wang, Y., Ji, M..  2019.  Heterogeneity Aware Workload Management in Distributed Sustainable Datacenters. IEEE Transactions on Parallel and Distributed Systems. 30:375–387.
The tremendous growth of cloud computing and large-scale data analytics highlight the importance of reducing datacenter power consumption and environmental impact of brown energy. While many Internet service operators have at least partially powered their datacenters by green energy, it is challenging to effectively utilize green energy due to the intermittency of renewable sources, such as solar or wind. We find that the geographical diversity of internet-scale services can be carefully scheduled to improve the efficiency of applying green energy in datacenters. In this paper, we propose a holistic heterogeneity-aware cloud workload management approach, sCloud, that aims to maximize the system goodput in distributed self-sustainable datacenters. sCloud adaptively places the transactional workload to distributed datacenters, allocates the available resource to heterogeneous workloads in each datacenter, and migrates batch jobs across datacenters, while taking into account the green power availability and QoS requirements. We formulate the transactional workload placement as a constrained optimization problem that can be solved by nonlinear programming. Then, we propose a batch job migration algorithm to further improve the system goodput when the green power supply varies widely at different locations. Finally, we extend sCloud by integrating a flexible batch job manager to dynamically control the job execution progress without violating the deadlines. We have implemented sCloud in a university cloud testbed with real-world weather conditions and workload traces. Experimental results demonstrate sCloud can achieve near-to-optimal system performance while being resilient to dynamic power availability. sCloud with the flexible batch job management approach outperforms a heterogeneity-oblivious approach by 37 percent in improving system goodput and 33 percent in reducing QoS violations.
2020-11-02
Wang, Nan, Yao, Manting, Jiang, Dongxu, Chen, Song, Zhu, Yu.  2018.  Security-Driven Task Scheduling for Multiprocessor System-on-Chips with Performance Constraints. 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). :545—550.

The high penetration of third-party intellectual property (3PIP) brings a high risk of malicious inclusions and data leakage in products due to the planted hardware Trojans, and system level security constraints have recently been proposed for MPSoCs protection against hardware Trojans. However, secret communication still can be established in the context of the proposed security constraints, and thus, another type of security constraints is also introduced to fully prevent such malicious inclusions. In addition, fulfilling the security constraints incurs serious overhead of schedule length, and a two-stage performance-constrained task scheduling algorithm is then proposed to maintain most of the security constraints. In the first stage, the schedule length is iteratively reduced by assigning sets of adjacent tasks into the same core after calculating the maximum weight independent set of a graph consisting of all timing critical paths. In the second stage, tasks are assigned to proper IP vendors and scheduled to time periods with a minimization of cores required. The experimental results show that our work reduces the schedule length of a task graph, while only a small number of security constraints are violated.

2020-09-28
Sliwa, Benjamin, Haferkamp, Marcus, Al-Askary, Manar, Dorn, Dennis, Wietfeld, Christian.  2018.  A radio-fingerprinting-based vehicle classification system for intelligent traffic control in smart cities. 2018 Annual IEEE International Systems Conference (SysCon). :1–5.
The measurement and provision of precise and up-to-date traffic-related key performance indicators is a key element and crucial factor for intelligent traffic control systems in upcoming smart cities. The street network is considered as a highly-dynamic Cyber Physical System (CPS) where measured information forms the foundation for dynamic control methods aiming to optimize the overall system state. Apart from global system parameters like traffic flow and density, specific data, such as velocity of individual vehicles as well as vehicle type information, can be leveraged for highly sophisticated traffic control methods like dynamic type-specific lane assignments. Consequently, solutions for acquiring these kinds of information are required and have to comply with strict requirements ranging from accuracy over cost-efficiency to privacy preservation. In this paper, we present a system for classifying vehicles based on their radio-fingerprint. In contrast to other approaches, the proposed system is able to provide real-time capable and precise vehicle classification as well as cost-efficient installation and maintenance, privacy preservation and weather independence. The system performance in terms of accuracy and resource-efficiency is evaluated in the field using comprehensive measurements. Using a machine learning based approach, the resulting success ratio for classifying cars and trucks is above 99%.
2020-07-13
Qiu, Yu, Wang, Jin-Yuan, Lin, Sheng-Hong, Wang, Jun-Bo, Lin, Min.  2019.  Secrecy Outage Probability Analysis for Visible Light Communications with SWIPT and Random Terminals. 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP). :1–6.
This paper investigates the physical-layer data secure transmission for indoor visible light communications (VLC) with simultaneous wireless information and power transfer (SWIPT) and random terminals. A typical indoor VLC system including one transmitter, one desired information receiver and one energy receiver is considered. The two receivers are randomly deployed on the floor, and the random channel characteristics is analyzed. Based on the possibility that the energy receiver is a passive information eavesdropper, the secrecy outage probability (SOP) is employed to evaluate the system performance. A closed-from expression for the lower bound of the SOP is obtained. For the derived lower bound of SOP, the theoretical results match the simulation results very well, which indicates that the derived lower bound can be used to evaluate the secrecy performance. Moreover, the gap between the results of the lower bound and the exact simulation results is also small, which verifies the correctness of the analysis method to obtain the lower bound.
Ge, Hong, Dai, Jianxin, Huang, Bo, Wang, Jin-Yuan.  2019.  Secrecy Rate Analysis for Visible Light Communications Using Spatial Modulation. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :1241–1248.
This paper mainly investigates the physical layer security for visible light communication (VLC) based on spatial modulation (SM). The indoor VLC system includes multiple transmitters, a legitimate receiver and an eavesdropper. In the system, we consider two constraints of the input signal: non-negative and dimmable average optical intensity constraints. According to the principle of information theory and the spatial modulation scheme of uniform selection (US), the upper and the lower bounds on the secrecy rate for SM based VLC are derived, respectively. Numerical results show that the performance gap between the upper and lower bounds of the secrecy rate is small and relatively close, which indicates that the derived secrecy rate bounds can be used to evaluate the system performance. Moreover, when the number of transmitters is set to be one, the spatial modulation disappears, and the secrecy rate bounds in this paper are consistent with the existing results. To further improve the secrecy performance, a channel adaptive selection (CAS) scheme is proposed for selecting the active transmitter. Numerical result indicates that the CAS scheme has better performance than the US scheme.
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.

2020-06-15
Gorbachov, Valeriy, Batiaa, Abdulrahman Kataeba, Ponomarenko, Olha, Kotkova, Oksana.  2019.  Impact Evaluation of Embedded Security Mechanisms on System Performance. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S T). :407–410.
Experience in designing general-purpose systems that enforce security goals shows that achieving universality, security, and performance remains a very difficult challenge. As a result, two directions emerged in designing, one of which focused on universality and performance with limited security mechanisms, and another - on robust security with reasonable performance for limited sets of applications. In the first case, popular but unsecure systems were created, and various efforts were subsequently made to upgrade the protected infrastructure for such systems. In the work, the latter approach is considered. It is obvious that the inclusion of built-in security mechanisms leads to a decrease in system performance. The paper considers a reference monitor and the assessment of its impact on system performance. For this purpose, the functional structure of reference monitor is built and the analytical model of impact evaluation on system performance is proposed.
2020-04-24
de Rooij, Sjors, Laguna, Antonio Jarquin.  2019.  Modelling of submerged oscillating water columns with mass transfer for wave energy extraction. 2019 Offshore Energy and Storage Summit (OSES). :1—9.
Oscillating-water-column (OWC) devices are a very important type of wave energy converters which have been extensively studied over the years. Although most designs of OWC are based on floating or fixed structures exposed above the surface level, little is known from completely submerged systems which can benefit from reduced environmental loads and a simplified structural design. The submerged type of resonant duct consists of two OWCs separated by a weir and air chamber instead of the commonly used single column. Under conditions close to resonance, water flows from the first column into the second one, resulting in a positive flow through the system from which energy can be extracted by a hydro turbine. While existing work has looked at the study of the behaviour of one OWC, this paper addresses the dynamic interaction between the two water columns including the mass transfer mechanism as well as the associated change of momentum. A numerical time-domain model is used to obtain some initial results on the performance and response of the system for different design parameters. The model is derived from 1D conservation of mass and momentum equations, including hydrodynamic effects, adiabatic air compressibility and turbine induced damping. Preliminary results indicate that the mass transfer has an important effect both on the resonance amplification and on the phase between the motion of the two columns. Simulation results are presented for the system performance over several weir heights and regular wave conditions. Further work will continue in design optimization and experimental validation of the proposed model.
2020-03-23
Daoud, Luka, Rafla, Nader.  2019.  Analysis of Black Hole Router Attack in Network-on-Chip. 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). :69–72.

Network-on-Chip (NoC) is the communication platform of the data among the processing cores in Multiprocessors System-on-Chip (MPSoC). NoC has become a target to security attacks and by outsourcing design, it can be infected with a malicious Hardware Trojan (HT) to degrades the system performance or leaves a back door for sensitive information leaking. In this paper, we proposed a HT model that applies a denial of service attack by deliberately discarding the data packets that are passing through the infected node creating a black hole in the NoC. It is known as Black Hole Router (BHR) attack. We studied the effect of the BHR attack on the NoC. The power and area overhead of the BHR are analyzed. We studied the effect of the locations of BHRs and their distribution in the network as well. The malicious nodes has very small area and power overhead, 1.98% and 0.74% respectively, with a very strong violent attack.

Naik, Nitin, Jenkins, Paul, Savage, Nick, Yang, Longzhi.  2019.  Cyberthreat Hunting - Part 1: Triaging Ransomware using Fuzzy Hashing, Import Hashing and YARA Rules. 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). :1–6.

Ransomware is currently one of the most significant cyberthreats to both national infrastructure and the individual, often requiring severe treatment as an antidote. Triaging ran-somware based on its similarity with well-known ransomware samples is an imperative preliminary step in preventing a ransomware pandemic. Selecting the most appropriate triaging method can improve the precision of further static and dynamic analysis in addition to saving significant t ime a nd e ffort. Currently, the most popular and proven triaging methods are fuzzy hashing, import hashing and YARA rules, which can ascertain whether, or to what degree, two ransomware samples are similar to each other. However, the mechanisms of these three methods are quite different and their comparative assessment is difficult. Therefore, this paper presents an evaluation of these three methods for triaging the four most pertinent ransomware categories WannaCry, Locky, Cerber and CryptoWall. It evaluates their triaging performance and run-time system performance, highlighting the limitations of each method.

2020-03-12
Zhang, Haibo, Nakamura, Toru, Sakurai, Kouichi.  2019.  Security and Trust Issues on Digital Supply Chain. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :338–343.

This exploratory investigation aims to discuss current status and challenges, especially in aspect of security and trust problems, of digital supply chain management system with applying some advanced information technologies, such as Internet of Things, cloud computing and blockchain, for improving various system performance and properties, i.e. transparency, visibility, accountability, traceability and reliability. This paper introduces the general histories and definitions, in terms of information science, of the supply chain and relevant technologies which have been applied or are potential to be applied on supply chain with purpose of lowering cost, facilitating its security and convenience. It provides a comprehensive review of current relative research work and industrial cases from several famous companies. It also illustrates requirements or performance of digital supply chain system, security management and trust issues. Finally, this paper concludes several potential or existing security issues and challenges which supply chain management is facing.

2020-02-18
Quan, Guocong, Tan, Jian, Eryilmaz, Atilla.  2019.  Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :694–702.
Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching systems in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights with successful algorithms on how to reduce cache miss ratios. Surprisingly, we show that these widely held insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to achieve efficient cache organization and data placement. The former allocates the total memory space to each of the involved caches. The latter decides data routing strategies and data replication schemes. Analytically we characterize the unreliable LRU caches by explicitly deriving their asymptotic miss probabilities. Based on these results, we optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: asymmetric cache organization is optimal even for symmetric channels. Specifically, even when channel unreliability probabilities are equal, allocating the cache spaces unequally can achieve a better performance. We also propose an explicit unequal allocation policy that outperforms the equal allocation. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than resource pooling that organizes the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels. They can potentially be exploited to further improve the system performance in real practice.
2019-12-17
Wang, Ziyan, Dong, Xinghua, Li, Yi, Fang, Li, Chen, Ping.  2018.  IoT Security Model and Performance Evaluation: A Blockchain Approach. 2018 International Conference on Network Infrastructure and Digital Content (IC-NIDC). :260-264.

It is a research hotspot that using blockchain technology to solve the security problems of the Internet of Things (IoT). Although many related ideas have been proposed, there are very few literatures with theoretical and data support. This paper focuses on the research of model construction and performance evaluation. First, an IoT security model is established based on blockchain and InterPlanetary File System (IPFS). In this model, many security risks of traditional IoT architectures can be avoided, and system performance is significantly improved in distributed large capacity storage, concurrency and query. Secondly, the performance of the proposed model is evaluated through the average latency and throughput, which are meaningful for further research and optimization of this direction. Analysis and test results demonstrate the effectiveness of the blockchain-based security model.

2019-01-21
Kafash, S. H., Giraldo, J., Murguia, C., Cárdenas, A. A., Ruths, J..  2018.  Constraining Attacker Capabilities Through Actuator Saturation. 2018 Annual American Control Conference (ACC). :986–991.
For LTI control systems, we provide mathematical tools - in terms of Linear Matrix Inequalities - for computing outer ellipsoidal bounds on the reachable sets that attacks can induce in the system when they are subject to the physical limits of the actuators. Next, for a given set of dangerous states, states that (if reached) compromise the integrity or safe operation of the system, we provide tools for designing new artificial limits on the actuators (smaller than their physical bounds) such that the new ellipsoidal bounds (and thus the new reachable sets) are as large as possible (in terms of volume) while guaranteeing that the dangerous states are not reachable. This guarantees that the new bounds cut as little as possible from the original reachable set to minimize the loss of system performance. Computer simulations using a platoon of vehicles are presented to illustrate the performance of our tools.
2015-05-06
Nower, N., Yasuo Tan, Lim, A.O..  2014.  Efficient Temporal and Spatial Data Recovery Scheme for Stochastic and Incomplete Feedback Data of Cyber-physical Systems. Service Oriented System Engineering (SOSE), 2014 IEEE 8th International Symposium on. :192-197.

Feedback loss can severely degrade the overall system performance, in addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications including stochastic and time-critical traffic patterns. Stochastic data has a randomness in its nature which make a great challenge to maintain the real-time control whenever the data is lost. In this paper, we propose a data recovery scheme, called the Efficient Temporal and Spatial Data Recovery (ETSDR) scheme for stochastic incomplete feedback of CPS. In this scheme, we identify the temporal model based on the traffic patterns and consider the spatial effect of the nearest neighbor. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithm regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.
 

Yuankai Chen, Xuan Zeng, Hai Zhou.  2014.  Recovery-based resilient latency-insensitive systems. Design, Automation and Test in Europe Conference and Exhibition (DATE), 2014. :1-6.

As the interconnect delay is becoming a larger fraction of the clock cycle time, the conventional global stalling mechanism, which is used to correct error in general synchronous circuits, would be no longer feasible because of the expensive timing cost for the stalling signal to travel across the circuit. In this paper, we propose recovery-based resilient latency-insensitive systems (RLISs) that efficiently integrate error-recovery techniques with latency-insensitive design to replace the global stalling. We first demonstrate a baseline RLIS as the motivation of our work that uses additional output buffer which guarantees that only correct data can enter the output channel. However this baseline RLIS suffers from performance degradations even when errors do not occur. We propose a novel improved RLIS that allows erroneous data to propagate in the system. Equipped with improved queues that prevent accumulation of erroneous data, the improved RLIS retains the system performance. We provide theoretical study that analyzes the impact of errors on system performance and the queue sizing problem. We also theoretically prove that the improved RLIS performs no worse than the global stalling mechanism. Experimental results show that the improved RLIS has 40.3% and even 3.1% throughput improvements compared to the baseline RLIS and the infeasible global stalling mechanism respectively, with less than 10% hardware overhead.