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2019-05-20
Caminha, J., Perkusich, A., Perkusich, M..  2018.  A smart middleware to detect on-off trust attacks in the Internet of Things. 2018 IEEE International Conference on Consumer Electronics (ICCE). :1–2.
Security is a key concern in Internet of Things (IoT) designs. In a heterogeneous and complex environment, service providers and service requesters must trust each other. On-off attack is a sophisticated trust threat in which a malicious device can perform good and bad services randomly to avoid being rated as a low trust node. Some countermeasures demands prior level of trust knowing and time to classify a node behavior. In this paper, we introduce a Smart Middleware that automatically assesses the IoT resources trust, evaluating service providers attributes to protect against On-off attacks.
Terkawi, A., Innab, N., al-Amri, S., Al-Amri, A..  2018.  Internet of Things (IoT) Increasing the Necessity to Adopt Specific Type of Access Control Technique. 2018 21st Saudi Computer Society National Computer Conference (NCC). :1–5.
The Internet of Things (IoT) is one of the emerging technologies that has seized the attention of researchers, the reason behind that was the IoT expected to be applied in our daily life in the near future and human will be wholly dependent on this technology for comfort and easy life style. Internet of things is the interconnection of internet enabled things or devices to connect with each other and to humans in order to achieve some goals or the ability of everyday objects to connect to the Internet and to send and receive data. However, the Internet of Things (IoT) raises significant challenges that could stand in the way of realizing its potential benefits. This paper discusses access control area as one of the most crucial aspect of security and privacy in IoT and proposing a new way of access control that would decide who is allowed to access what and who is not to the IoT subjects and sensors.
2019-05-09
Ivanov, A. V., Sklyarov, V. A..  2018.  The Urgency of the Threats of Attacks on Interfaces and Field-Layer Protocols in Industrial Control Systems. 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). :162-165.
The paper is devoted to analysis of condition of executing devices and sensors of Industrial Control Systems information security. The work contains structures of industrial control systems divided into groups depending on system's layer. The article contains the analysis of analog interfaces work and work features of data transmission protocols in industrial control system field layer. Questions about relevance of industrial control systems information security, both from the point of view of the information security occurring incidents, and from the point of view of regulators' reaction in the form of normative legal acts, are described. During the analysis of the information security systems of industrial control systems a possibility of leakage through technical channels of information leakage at the field layer was found. Potential vectors of the attacks on devices of field layer and data transmission network of an industrial control system are outlined in the article. The relevance analysis of the threats connected with the attacks at the field layer of an industrial control system is carried out, feature of this layer and attractiveness of this kind of attacks is observed.
Hata, K., Sasaki, T., Mochizuki, A., Sawada, K., Shin, S., Hosokawa, S..  2018.  Collaborative Model-Based Fallback Control for Secured Networked Control Systems. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. :5963-5970.
The authors have proposed the Fallback Control System (FCS) as a countermeasure after cyber-attacks happen in Industrial Control Systems (ICSs). For increased robustness against cyber-attacks, introducing multiple countermeasures is desirable. Then, an appropriate collaboration is essential. This paper introduces two FCSs in ICS: field network signal is driven FCS and analog signal driven FCS. This paper also implements a collaborative FCS by a collaboration function of the two FCSs. The collaboration function is that the analog signal driven FCS estimates the state of the other FCS. The collaborative FCS decides the countermeasure based on the result of the estimation after cyber-attacks happen. Finally, we show practical experiment results to analyze the effectiveness of the proposed method.
2019-03-28
Chen, J., Xu, R., Li, C..  2018.  Research of Security Situational Awareness and Visualization Approach in Cloud Computing. 2018 International Conference on Networking and Network Applications (NaNA). :201-205.
Cloud computing is an innovative mechanism to optimize computing and storage resource utilization. Due to its cost-saving, high-efficiency advantage, the technology receives wide adoption from IT industries. However, the frequent emergences of security events become the heaviest obstacle for its advancement. The multi-layer and distributive characteristics of cloud computing make IT admins compulsively collect all necessary situational information at cloud runtime if they want to grasp the panoramic secure state, hereby practice configuration management and emergency response methods when necessary. On the other hand, technologies such as elastic resource pooling, dynamic load balancing and virtual machine real-time migration complicate the difficulty of data gathering, where secure information may come from virtual machine hypervisor, network accounting or host monitor proxies. How to classify, arrange, standardize and visualize these data turns into the most crucial issue for cloud computing security situation awareness and presentation. This dissertation borrows traditional fashion of data visualization to integrate into cloud computing features, proposes a new method for aggregating and displaying secure information which IT admins concern, and expects that by method realization cloud security monitor/management capabilities could be notably enhanced.
2019-03-22
Kumar, A., Abdelhadi, A., Clancy, C..  2018.  Novel Anomaly Detection and Classification Schemes for Machine-to-Machine Uplink. 2018 IEEE International Conference on Big Data (Big Data). :1284-1289.
Machine-to-Machine (M2M) networks being connected to the internet at large, inherit all the cyber-vulnerabilities of the standard Information Technology (IT) systems. Since perfect cyber-security and robustness is an idealistic construct, it is worthwhile to design intrusion detection schemes to quickly detect and mitigate the harmful consequences of cyber-attacks. Volumetric anomaly detection have been popularized due to their low-complexity, but they cannot detect low-volume sophisticated attacks and also suffer from high false-alarm rate. To overcome these limitations, feature-based detection schemes have been studied for IT networks. However these schemes cannot be easily adapted to M2M systems due to the fundamental architectural and functional differences between the M2M and IT systems. In this paper, we propose novel feature-based detection schemes for a general M2M uplink to detect Distributed Denial-of-Service (DDoS) attacks, emergency scenarios and terminal device failures. The detection for DDoS attack and emergency scenarios involves building up a database of legitimate M2M connections during a training phase and then flagging the new M2M connections as anomalies during the evaluation phase. To distinguish between DDoS attack and emergency scenarios that yield similar signatures for anomaly detection schemes, we propose a modified Canberra distance metric. It basically measures the similarity or differences in the characteristics of inter-arrival time epochs for any two anomalous streams. We detect device failures by inspecting for the decrease in active M2M connections over a reasonably large time interval. Lastly using Monte-Carlo simulations, we show that the proposed anomaly detection schemes have high detection performance and low-false alarm rate.
2019-02-25
Akhtar, T., Gupta, B. B., Yamaguchi, S..  2018.  Malware Propagation Effects on SCADA System and Smart Power Grid. 2018 IEEE International Conference on Consumer Electronics (ICCE). :1-6.
Critical infrastructures have suffered from different kind of cyber attacks over the years. Many of these attacks are performed using malwares by exploiting the vulnerabilities of these resources. Smart power grid is one of the major victim which suffered from these attacks and its SCADA system are frequently targeted. In this paper we describe our proposed framework to analyze smart power grid, while its SCADA system is under attack by malware. Malware propagation and its effects on SCADA system is the focal point of our analysis. OMNeT++ simulator and openDSS is used for developing and analyzing the simulated smart power grid environment.
Al-Waisi, Zainab, Agyeman, Michael Opoku.  2018.  On the Challenges and Opportunities of Smart Meters in Smart Homes and Smart Grids. Proceedings of the 2Nd International Symposium on Computer Science and Intelligent Control. :16:1-16:6.
Nowadays, electricity companies have started applying smart grid in their systems rather than the conventional electrical grid (manual grid). Smart grid produces an efficient and effective energy management and control, reduces the cost of production, saves energy and it is more reliable compared to the conventional grid. As an advanced energy meter, smart meters can measure the power consumption as well as monitor and control electrical devices. Smart meters have been adopted in many countries since the 2000s as they provide economic, social and environmental benefits for multiple stakeholders. The design of smart meter can be customized depending on the customer and the utility company needs. There are different sensors and devices supported by dedicated communication infrastructure which can be utilized to implement smart meters. This paper presents a study of the challenges associated with smart meters, smart homes and smart grids as an effort to highlight opportunities for emerging research and industrial solutions.
2019-02-14
Schuette, J., Brost, G. S..  2018.  LUCON: Data Flow Control for Message-Based IoT Systems. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :289-299.
Today's emerging Industrial Internet of Things (IIoT) scenarios are characterized by the exchange of data between services across enterprises. Traditional access and usage control mechanisms are only able to determine if data may be used by a subject, but lack an understanding of how it may be used. The ability to control the way how data is processed is however crucial for enterprises to guarantee (and provide evidence of) compliant processing of critical data, as well as for users who need to control if their private data may be analyzed or linked with additional information - a major concern in IoT applications processing personal information. In this paper, we introduce LUCON, a data-centric security policy framework for distributed systems that considers data flows by controlling how messages may be routed across services and how they are combined and processed. LUCON policies prevent information leaks, bind data usage to obligations, and enforce data flows across services. Policy enforcement is based on a dynamic taint analysis at runtime and an upfront static verification of message routes against policies. We discuss the semantics of these two complementing enforcement models and illustrate how LUCON policies are compiled from a simple policy language into a first-order logic representation. We demonstrate the practical application of LUCON in a real-world IoT middleware and discuss its integration into Apache Camel. Finally, we evaluate the runtime impact of LUCON and discuss performance and scalability aspects.
2019-02-08
Gurabi, M. A., Alfandi, O., Bochem, A., Hogrefe, D..  2018.  Hardware Based Two-Factor User Authentication for the Internet of Things. 2018 14th International Wireless Communications Mobile Computing Conference (IWCMC). :1081-1086.
In the distributed Internet of Things (IoT) architecture, sensors collect data from vehicles, home appliances and office equipment and other environments. Various objects contain the sensor which process data, cooperate and exchange information with other embedded devices and end users in a distributed network. It is important to provide end-to-end communication security and an authentication system to guarantee the security and reliability of the data in such a distributed system. Two-factor authentication is a solution to improve the security level of password-based authentication processes and immunized the system against many attacks. At the same time, the computational and storage overhead of an authentication method also needs to be considered in IoT scenarios. For this reason, many cryptographic schemes are designed especially for the IoT; however, we observe a lack of laboratory hardware test beds and modules, and universal authentication hardware modules. This paper proposes a design and analysis for a hardware module in the IoT which allows the use of two-factor authentication based on smart cards, while taking into consideration the limited processing power and energy reserves of nodes, as well as designing the system with scalability in mind.
2019-01-21
Samanta, P., Kelly, E., Bashir, A., Debroy, S..  2018.  Collaborative Adversarial Modeling for Spectrum Aware IoT Communications. 2018 International Conference on Computing, Networking and Communications (ICNC). :447–451.
In order to cater the growing spectrum demands of large scale future 5G Internet of Things (IoT) applications, Dynamic Spectrum Access (DSA) based networks are being proposed as a high-throughput and cost-effective solution. However the lack of understanding of DSA paradigm's inherent security vulnerabilities on IoT networks might become a roadblock towards realizing such spectrum aware 5G vision. In this paper, we make an attempt to understand how such inherent DSA vulnerabilities in particular Spectrum Sensing Data Falsification (SSDF) attacks can be exploited by collaborative group of selfish adversaries and how that can impact the performance of spectrum aware IoT applications. We design a utility based selfish adversarial model mimicking collaborative SSDF attack in a cooperative spectrum sensing scenario where IoT networks use dedicated environmental sensing capability (ESC) for spectrum availability estimation. We model the interactions between the IoT system and collaborative selfish adversaries using a leader-follower game and investigate the existence of equilibrium. Using simulation results, we show the nature of adversarial and system utility components against system variables. We also explore Pareto-optimal adversarial strategy design that maximizes the attacker utility for varied system strategy spaces.
Nicolaou, N., Eliades, D. G., Panayiotou, C., Polycarpou, M. M..  2018.  Reducing Vulnerability to Cyber-Physical Attacks in Water Distribution Networks. 2018 International Workshop on Cyber-physical Systems for Smart Water Networks (CySWater). :16–19.
Cyber-Physical Systems (CPS), such as Water Distribution Networks (WDNs), deploy digital devices to monitor and control the behavior of physical processes. These digital devices, however, are susceptible to cyber and physical attacks, that may alter their functionality, and therefore the integrity of their measurements/actions. In practice, industrial control systems utilize simple control laws, which rely on various sensor measurements and algorithms which are expected to operate normally. To reduce the impact of a potential failure, operators may deploy redundant components; this however may not be useful, e.g., when a cyber attack at a PLC component occurs. In this work, we address the problem of reducing vulnerability to cyber-physical attacks in water distribution networks. This is achieved by augmenting the graph which describes the information flow from sensors to actuators, by adding new connections and algorithms, to increase the number of redundant cyber components. These, in turn, increase the \textitcyber-physical security level, which is defined in the present paper as the number of malicious attacks a CPS may sustain before becoming unable to satisfy the control requirements. A proof-of-concept of the approach is demonstrated over a simple WDN, with intuition on how this can be used to increase the cyber-physical security level of the system.
Yu, Z., Du, H., Xiao, D., Wang, Z., Han, Q., Guo, B..  2018.  Recognition of Human Computer Operations Based on Keystroke Sensing by Smartphone Microphone. IEEE Internet of Things Journal. 5:1156–1168.
Human computer operations such as writing documents and playing games have become popular in our daily lives. These activities (especially if identified in a non-intrusive manner) can be used to facilitate context-aware services. In this paper, we propose to recognize human computer operations through keystroke sensing with a smartphone. Specifically, we first utilize the microphone embedded in a smartphone to sense the input audio from a computer keyboard. We then identify keystrokes using fingerprint identification techniques. The determined keystrokes are then corrected with a word recognition procedure, which utilizes the relations of adjacent letters in a word. Finally, by fusing both semantic and acoustic features, a classification model is constructed to recognize four typical human computer operations: 1) chatting; 2) coding; 3) writing documents; and 4) playing games. We recruited 15 volunteers to complete these operations, and evaluated the proposed approach from multiple aspects in realistic environments. Experimental results validated the effectiveness of our approach.
2019-01-16
Zhang, R., Yang, G., Wang, Y..  2018.  Propagation Characteristics of Acoustic Emission Signals in Multi Coupling Interface of the Engine. 2018 IEEE 3rd International Conference on Integrated Circuits and Microsystems (ICICM). :254–258.
The engine is a significant and dynamic component of the aircraft. Because of the complicated structure and severe operating environment, the fault detection of the engine has always been the key and difficult issue in the field of reliability. Based on an engine and the acoustic emission technology, we propose a method of identifying fault types and determining different components in the engine by constructing the attenuation coefficient. There are several common faults of engines, and three different types of fault sources are generated experimentally in this work. Then the fault signal of the above fault sources propagating in different engine components are obtained. Finally, the acoustic emission characteristics of the fault signal are extracted and judged by the attenuation coefficient. The work effectively identifies different types of faults and studies the effects of different structural components on the propagation of fault acoustic emission signals, which provides a method for the use of acoustic emission technology to identify the faults types of the engine and to study the propagation characteristics of AE signals on the engine.*
Hossain, M., Xie, J..  2018.  Off-sensing and Route Manipulation Attack: A Cross-Layer Attack in Cognitive Radio based Wireless Mesh Networks. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. :1376–1384.
Cognitive Radio (CR) has garnered much attention in the last decade, while the security issues are not fully studied yet. Existing research on attacks and defenses in CR - based networks focuses mostly on individual network layers, whereas cross-layer attacks remain fortified against single-layer defenses. In this paper, we shed light on a new vulnerability in cross-layer routing protocols and demonstrate how a perpetrator can exploit this vulnerability to manipulate traffic flow around it. We propose this cross-layer attack in CR-based wireless mesh networks (CR-WMNs), which we call off-sensing and route manipulation (OS-RM) attack. In this cross-layer assault, off-sensing attack is launched at the lower layers as the point of attack but the final intention is to manipulate traffic flow around the perpetrator. We also introduce a learning strategy for a perpetrator, so that it can gather information from the collaboration with other network entities and capitalize this information into knowledge to accelerate its malice intentions. Simulation results show that this attack is far more detrimental than what we have experienced in the past and need to be addressed before commercialization of CR-based networks.
2018-12-10
Farooq, M. J., Zhu, Q..  2017.  Secure and reconfigurable network design for critical information dissemination in the Internet of battlefield things (IoBT). 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt). :1–8.

The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas such as smart homes, smart cities, health care, transportation, etc. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to the battlefield specific challenges such as the absence of communication infrastructure, and the susceptibility of devices to cyber and physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and the information dissemination in the presence of adversaries. This work aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to study the communication of mission-critical data among different types of network devices and consequently design the network in a cost effective manner.

Mirzamohammadi, Saeed, Chen, Justin A., Sani, Ardalan Amiri, Mehrotra, Sharad, Tsudik, Gene.  2017.  Ditio: Trustworthy Auditing of Sensor Activities in Mobile & IoT Devices. Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. :28:1–28:14.
Mobile and Internet-of-Things (IoT) devices, such as smartphones, tablets, wearables, smart home assistants (e.g., Google Home and Amazon Echo), and wall-mounted cameras, come equipped with various sensors, notably camera and microphone. These sensors can capture extremely sensitive and private information. There are several important scenarios where, for privacy reasons, a user might require assurance about the use (or non-use) of these sensors. For example, the owner of a home assistant might require assurance that the microphone on the device is not used during a given time of the day. Similarly, during a confidential meeting, the host needs assurance that attendees do not record any audio or video. Currently, there are no means to attain such assurance in modern mobile and IoT devices. To this end, this paper presents Ditio, a system approach for auditing sensor activities. Ditio records sensor activity logs that can be later inspected by an auditor and checked for compliance with a given policy. It is based on a hybrid security monitor architecture that leverages both ARM's virtualization hardware and TrustZone. Ditio includes an authentication protocol for establishing a logging session with a trusted server and a formally verified companion tool for log analysis. Ditio prototypes on ARM Juno development board and Nexus 5 smartphone show that it introduces negligible performance overhead for both the camera and microphone. However, it incurs up to 17% additional power consumption under heavy use for the Nexus 5 camera.
2018-11-19
Sun, K., Esnaola, I., Perlaza, S. M., Poor, H. V..  2017.  Information-Theoretic Attacks in the Smart Grid. 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm). :455–460.
Gaussian random attacks that jointly minimize the amount of information obtained by the operator from the grid and the probability of attack detection are presented. The construction of the attack is posed as an optimization problem with a utility function that captures two effects: firstly, minimizing the mutual information between the measurements and the state variables; secondly, minimizing the probability of attack detection via the Kullback-Leibler (KL) divergence between the distribution of the measurements with an attack and the distribution of the measurements without an attack. Additionally, a lower bound on the utility function achieved by the attacks constructed with imperfect knowledge of the second order statistics of the state variables is obtained. The performance of the attack construction using the sample covariance matrix of the state variables is numerically evaluated. The above results are tested in the IEEE 30-Bus test system.
Ali, S., Khan, M. A., Ahmad, J., Malik, A. W., ur Rehman, A..  2018.  Detection and Prevention of Black Hole Attacks in IOT Amp;Amp; WSN. 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC). :217–226.
Wireless Sensor Network is the combination of small devices called sensor nodes, gateways and software. These nodes use wireless medium for transmission and are capable to sense and transmit the data to other nodes. Generally, WSN composed of two types of nodes i.e. generic nodes and gateway nodes. Generic nodes having the ability to sense while gateway nodes are used to route that information. IoT now extended to IoET (internet of Everything) to cover all electronics exist around, like a body sensor networks, VANET's, smart grid stations, smartphone, PDA's, autonomous cars, refrigerators and smart toasters that can communicate and share information using existing network technologies. The sensor nodes in WSN have very limited transmission range as well as limited processing speed, storage capacities and low battery power. Despite a wide range of applications using WSN, its resource constrained nature given birth to a number severe security attacks e.g. Selective Forwarding attack, Jamming-attack, Sinkhole attack, Wormhole attack, Sybil attack, hello Flood attacks, Grey Hole, and the most dangerous BlackHole Attacks. Attackers can easily exploit these vulnerabilities to compromise the WSN network.
Samudrala, A. N., Blum, R. S..  2017.  Asymptotic Analysis of a New Low Complexity Encryption Approach for the Internet of Things, Smart Cities and Smart Grid. 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC). :200–204.
Parameter estimation in wireless sensor networks (WSN) using encrypted non-binary quantized data is studied. In a WSN, sensors transmit their observations to a fusion center through a wireless medium where the observations are susceptible to unauthorized eavesdropping. Encryption approaches for WSNs with fixed threshold binary quantization were previously explored. However, fixed threshold binary quantization limits parameter estimation to scalar parameters. In this paper, we propose a stochastic encryption approach for WSNs that can operate on non-binary quantized observations and has the capability for vector parameter estimation. We extend a binary stochastic encryption approach proposed previously, to a non-binary generalized case. Sensor outputs are quantized using a quantizer with R + 1 levels, where R $ε$ 1, 2, 3,..., encrypted by flipping them with certain flipping probabilities, and then transmitted. Optimal estimators using maximum-likelihood estimation are derived for both a legitimate fusion center (LFC) and a third party fusion center (TPFC) perspectives. We assume the TPFC is unaware of the encryption. Asymptotic analysis of the estimators is performed by deriving the Cramer-Rao lower bound for LFC estimation, and the asymptotic bias and variance for TPFC estimation. Numerical results validating the asymptotic analysis are presented.
2018-11-14
Alagar, V., Alsaig, A., Ormandjiva, O., Wan, K..  2018.  Context-Based Security and Privacy for Healthcare IoT. 2018 IEEE International Conference on Smart Internet of Things (SmartIoT). :122–128.
Healthcare Internet of Things (HIoT) is transforming healthcare industry by providing large scale connectivity for medical devices, patients, physicians, clinical and nursing staff who use them and facilitate real-time monitoring based on the information gathered from the connected things. Heterogeneity and vastness of this network provide both opportunity and challenges for information collection and sharing. Patient-centric information such as health status and medical devices used by them must be protected to respect their safety and privacy, while healthcare knowledge should be shared in confidence by experts for healthcare innovation and timely treatment of patients. In this paper an overview of HIoT is given, emphasizing its characteristics to those of Big Data, and a security and privacy architecture is proposed for it. Context-sensitive role-based access control scheme is discussed to ensure that HIoT is reliable, provides data privacy, and achieves regulatory compliance.
2018-09-28
Husak, M., Čermák, M..  2017.  A graph-based representation of relations in network security alert sharing platforms. 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :891–892.

In this paper, we present a framework for graph-based representation of relation between sensors and alert types in a security alert sharing platform. Nodes in a graph represent either sensors or alert types, while edges represent various relations between them, such as common type of reported alerts or duplicated alerts. The graph is automatically updated, stored in a graph database, and visualized. The resulting graph will be used by network administrators and security analysts as a visual guide and situational awareness tool in a complex environment of security alert sharing.

2018-08-23
Randles, Martin, Johnson, Princy, Hussain, Abir.  2017.  Internet of Things Eco-systems: Assured Interactivity of Devices and Data Through Cloud Based Team Work. Proceedings of the Second International Conference on Internet of Things, Data and Cloud Computing. :15:1–15:9.
IoT systems continue to grow in scale and exhibit similarities to complex systems seen in nature and biology: Systems are composed of heterogeneous entities (mobile devices, servers, sensors, data items, databases, etc.) coordinated in a Cloud environment forming a digital eco-system. Properties of such systems include variety, emergent outcome, self-organisation, etc. The scale of IoT systems, and the disparity in the capabilities of the devices on the market, means there needs to be a unifying model to enable a secure and assured interaction among those `things'. The authors propose conceptual designs for an efficient architecture, run-time decision models using assured models for such an interaction in a digital eco-system. This is done using the situation calculus modelling to represent the fundamental requirements for adjustable decentralised feedback control mechanisms necessary for the IoT-ready software systems: It is shown that complex properties and emergent outcomes of the system can be deduced, emanating from the simple distributed interaction models. A case study from the rail industry is used to assess the design and possible implementation.
Chaturvedi, P., Daniel, A. K..  2017.  Trust aware node scheduling protocol for target coverage using rough set theory. 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). :511–514.

Wireless sensor networks have achieved the substantial research interest in the present time because of their unique features such as fault tolerance, autonomous operation etc. The coverage maximization while considering the resource scarcity is a crucial problem in the wireless sensor networks. The approaches which address these problems and maximize the network lifetime are considered prominent. The node scheduling is such mechanism to address this issue. The scheduling strategy which addresses the target coverage problem based on coverage probability and trust values is proposed in Energy Efficient Coverage Protocol (EECP). In this paper the optimized decision rules is obtained by using the rough set theory to determine the number of active nodes. The results show that the proposed extension results in the lesser number of decision rules to consider in determination of node states in the network, hence it improves the network efficiency by reducing the number of packets transmitted and reducing the overhead.

Chowdhury, F. H., Shuvo, B., Islam, M. R., Ghani, T., Akash, S. A., Ahsan, R., Hassan, N. N..  2017.  Design, control amp;amp; performance analysis of secure you IoT based smart security system. 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–6.

The paper introduces a smart system developed with sensors that is useful for internal and external security. The system is useful for people living in houses, apartments, high officials, bank, and offices. The system is developed in two phases one for internal security like home another is external security like open areas, streets. The system is consist of a mobile application, capacitive sensing, smart routing these valuable features to ensure safety of life and wealth. This security system is wireless sensor based which is an effective alternative of cctv cameras and other available security systems. Efficiency of this system is developed after going through practical studies and prototyping. The end result explains the feasibility rate, positive impact factor, reliability of the system. More research is possible in future based on this system this research explains that.