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This book constitutes the refereed proceedings of the 20th International Conference on Innovations for Community Services, I4CS 2020, held in Bhubaneswar, India, in January, 2020.

The 16 revised full papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers focus on all aspects of: communities and social networks; information and system security; cloud and network security; communication and networks; and data analytics and e-governance.

The Telecommunication Data Cockpit – Full Control for the Household Community

Abstract
Consumers of telecommunication services become more and more aware and concerned of how their data is treated by providers. Both, the European General Data Protection Regulation and the versatility of new communication-related data use cases drive this challenge. The Data Cockpit Minimum Viable Product is an important step to generate more transparency for private telco customers. It is part of a new 360-degree customer view, which is generated to emphasize the user position in managing telco services and contracts of an entire household. Extensive user research has identified crucial steps to reach use case acceptance, respectively opt-in, by customers as well as key success factors behind building up users’ confidence and giving them more control over their data.
Gerald Eichler, Claudia Pohlink, Wolfgang Kurz

A Mobile Recommender System for Location-Aware Telemedical Diagnostics

Abstract
As recommender systems have proven their effectiveness in providing personalised recommendations based on previous user preferences in e-commerce, this approach is to be transferred for use in medicine. In particular, the aim is to complement the diagnoses made by physicians in rural hospitals of developing countries, in remote areas or in situations of uncertainty by machine recommendations that draw on large bases of expert knowledge to reduce the risk to patients. To this end, a database of patients’ medical history and a cluster model is maintained centrally. The model is constructed incrementally by a combination of collaborative and knowledge-based filtering, employing a weighted similarity distance specifically derived for medical knowledge. In the course of this process, the model permanently widens its base of knowledge on a medical area given. To give a recommendation, the model’s cluster best matching the diagnostic pattern of a considered patient is sought. Fuzzy sets are employed to cope with possible confusion in decision making, which may occur when large data sets cause clusters to overlap. The degrees of membership to these fuzzy sets are expressed by the Mahalanobis distance, whose weights are derived from risk factors identified by experts. The therapy actually applied after the recommendation and its subsequently observed consequences are fed back for model updating. Readily available mobile digital accessories can be used for remote data entry and recommendation display as well as for communication with the central site. The approach is validated in the area of obstetrics and gynecology.
Maytiyanin Komkhao, Sunantha Sodsee, Wolfgang A. Halang

NewYouthHack: Using Design Thinking to Reimagine Settlement Services for New Canadians

Abstract
In 2018–2019 we applied Design Thinking (DT) to reimagining settlement services for refugee and immigrant youth in Canada. DT continues to gain followers as a practical approach to incorporating human factors into the design process. One insight motivating DT is that design is a series of experiments in which we learn about our users. Iterative prototyping and user feedback are paramount. But we also wanted to expose them to career pathways related to software design and development. In this paper we report on (1) the NewYouthHack process, (2) the resulting app and central role played by social interactions, and (3) the framework we developed to support this work.
We launched with a two-day designathon with 12 identified problems and proposed solutions. Social interaction and community supported by software were threaded through almost all of the solutions. This presented two new challenges: securing iteratively developed network software for vulnerable users, and meaningfully engaging the youth in necessarily complex software. Previously we had developed an outreach curriculum with tool support based on a library in Elm for stand-alone graphical web apps. We taught interaction using state diagrams. In Petri App Land (PAL), we generalized this, with tokens representing users visiting places within the app. Transitions now capture user interactions. To facilitate significant changes from iteration to iteration, much of the code is (re)generated based on a PAL spec.
Christopher Schankula, Emily Ham, Jessica Schultz, Yumna Irfan, Nhan Thai, Lucas Dutton, Padma Pasupathi, Chinmay Sheth, Taranum Khan, Salima Tejani, Dima Amad, Robert Fleisig, Christopher Kumar Anand

Community Based Emotional Behaviour Using Ekman’s Emotional Scale

Abstract
In the current era, the analysis of social network data is one of the challenging tasks. Social networks are represented as a graphical structure where the users will be treated as nodes and the edges represent the social tie between the users. Research such as community identification, detection of centrality, detection of fraud, prediction of links and many other social issues are carried out in social network analysis. However, the community plays an important role in solving major issues in a real-world scenario. In a community structure, nodes inside a community are densely connected, whereas nodes between the communities are sparsely connected. Determining the emotional behavior from communities is the major concern because, emotional behavior of community helps us to solve problems like brand reachability, find target audience, build brand awareness and much more. Ekman’s emotional scale is a popular categorical model which assumes that there is a finite number of basic and discrete emotions and is used to classify the emotions. In this paper, a novel method is proposed to determine the community-specific emotional behavior of the users related to a particular topic. Communities are formed based on network topology rather than emotions. Girvan Newman algorithm is used to construct the communities of different users, who share their views on twitter media platforms regarding a topic. Then Ekman’s emotional scale is used to categorize the emotions of the users of each community. This identifies how the people of different communities react to an incident. The incident can be treated as NEWS/Trending threads on Twitter/Facebook shares. The emotional analysis is done community-specific so that the behavioral analysis of an incident is performed specifically for that community. Further, the comprehensive experimental analysis shows that the proposed methodology constructs influential communities and performs emotional analysis efficiently.
Debadatta Naik, Naveen Babu Gorojanam, Dharavath Ramesh

Non-fear-Based Road Safety Campaign as a Community Service: Contexts from Social Media

Abstract
Traffic crash is a critical health hazard throughout the world. Traffic safety campaigns are important in increasing behavioral safety. Social media makes safety campaigns convenient due to its greater accessibility compared to mass media. Most road safety campaigns are fear-based. There is a need to use these campaigns carefully to reach a wider audience. Non-fear-based safety campaigns are limited in number, and their impact is significant in changing public attitudes towards safety. This study collected YouTube comment data from two non-fear-based safety campaigns and compared their impacts by using natural language processing tools. The findings of this study can help policymakers in understanding public perception and determining appropriate measures to improve road user behavior.
Subasish Das, Anandi Dutta, Abhisek Mudgal, Songjukta Datta

Survey on Social Networks Data Analysis

Abstract
Social networks are the most successful Web 2.0 applications, where users share and create over 2.5 quintillion bytes of data daily. This data can be exploited to retrieve many kinds of information which will be used in several applications. In fact, social networks have attracted considerable attention from researchers in different domains. This paper serves as an introduction to social network data analysis. In this work we present the recent and representative works in social network data analysis in an analytical fashion. We also highlight most important applications and used methods in the context of structural data analysis. Then, we list the major tasks and approaches proposed to analyse added-content in social media.
Soufien Jaffali, Salma Jamoussi, Nesrine Khelifi, Abdelmajid Ben Hamadou

ReFIT: Reliability Challenges and Failure Rate Mitigation Techniques for IoT Systems

Abstract
As the number of Internet-of-Things (IoT) devices increases, ensuring the reliability of the IoT system has become a challenging job. Apart from the emerging security issues, reliable IoT system design depends on many other factors. In this work, for the first time, we have shown all the reliability challenges of an IoT system in details, which may arise due to the random faults. We have also proposed a mathematical formulation of the lifetime of the IoT system. Subsequently, we devise an algorithm which uses Lévy distribution-based duty cycling approach to improve the IoT network lifetime. We have validated our proposed method using Cooja simulation software. The simulation results show 1.5 $$\times$$ increment in network lifetime for the IoT system using our proposed method than the state-of-the-artwork. We have also demonstrated that our proposed method does not degrade the network performance.
Sukanta Dey, Pradeepkumar Bhale, Sukumar Nandi

The Ultimate Victory of White- over Blacklisting for the Editing of Encrypted Instant Messages Without Decrypting Nor Understanding Them

Abstract
The European Union Agency for Law Enforcement Cooperation (hereinafter denominated as Europol) has constantly warned society about the unbowed growth of child sexual exploitation in its six issued IOCTAs (Internet Organised Crime Threat Assessments). If already all attempts succeed to thwart grooming as the initiation of contacts between pedophiles and adolescents, then CSEM (Child Sexual Exploitation Material) cannot accrue and SGEM (Self Generated Explicit Material) does not find its way to perpetrators. IM (Instant Messaging) spearheads the list of preferred communication tools that render grooming possible. The consensual editing of encrypted instant messages without decrypting nor understanding them based on black- or whitelisting commits itself to the thwarting of grooming. Existing literature attests whitelisting better functionality and worse performance than blacklisting. In contrast, recent related work objects to the inferior performance of whitelisting, since former experiments for both paradigms happened under incomparable conditions, and demands their remake under fair circumstances. This scholarly piece refutes the inferiority of whitelisting by exhibiting the results of a new test series in which blacklisting screens the complementary set of words that whitelisting does not incorporate. At the end, it corroborates that whitelisting outplays blacklisting and emerges victorious.
Günter Fahrnberger

Code-Tampering Defense for Internet of Things Using System Call Traces

Abstract
This paper proposes a novel method to prevent an attack mounted by an adversary on an IoT device by executing suspicious system calls. An adversary in such cases would want to modify the behavior of an IoT device for hijacking the control by mounting malicious code. This paper uses system call traces to find out illegal accesses made on an IoT node. We develop a kernel-level processor tracing method for jeopardizing adversary’s activities. The method is rigorously tested on various IoT nodes like Raspberry Pi 3, Intel Galileo Gen 2, Arduino Uno etc.
Rajesh Kumar Shrivastava, Chittaranjan Hota

Binary Binomial Tree Based Secure and Efficient Electronic Healthcare Record Storage in Cloud Environment

Abstract
Electronic Health Records (EHRs) is a key form of healthcare records that attracts a great deal of attention. It is regarded that the sharing of healthcare records is a vital strategy for improving the quality of healthcare services and reducing medical expenses. Presently, the cloud computing paradigm supports many significant characteristics in Electronics Health Records (EHRs). However, in the cloud model, the patients have no longer control over their crucial healthcare records after outsourcing the records to cloud servers, which can lead to severe data integrity related concerns. Therefore, in this manuscript, we introduce a novel secure and efficient cloud based EHR data storage system by constructing Binary Binomial Tree like data structure. Furthermore, we extend the proposed model to attain significant cloud model based public auditing characteristics such as data dynamics, batch auditing, privacy preserving, blockless verification, data traceability, and recoverability. Extensive experiments and results demonstrate that the proposed cloud based EHR system is secure and efficient over other existing strategies.
Rahul Mishra, Dharavath Ramesh, Damodar Reddy Edla, Manoj Kumar Sah

Energy Efficient Approach to Detect Sinkhole Attack Using Roving IDS in 6LoWPAN Network

Abstract
The Internet of Things (IoT) has become a widespread technology where everyday objects are being transferred toward intelligent devices. These smart devices incorporate sensing, computing, and networking abilities into them. A smartphone, a smartwatch can be utilized for various tasks other than calling and timekeeping. Even home appliances also incorporate a midrange computer. Therefore, the most advanced applications and services have considerably risen. Despite numerous gains, security threats increased in terms of recorded catastrophic events as well as attack severity. There are multiple threads in 6LoWPAN and related routing protocol. In our research paper, we perform and assess an energy-efficient, lightweight intrusion detection system (IDS) for the 6LoWPAN network. The primary goal of this paper to target routing attacks (i.e., selective-forwarding, sinkhole, etc.). Our intended energy-efficient lightweight defense solution which identifies sinkhole attack in the IoT ecosystem. The defense method is executed with the help of Cooja network simulator on the Contiki OS. The experimental outcomes show that the solution is lightweight and can identify the sinkhole attack with a noteworthy performance, and provides 95.86% TPR and 94.31% TNR rate. It also shows minimum memory (RAM/ROM) utilization and energy consumption, which is comparable.
Pradeepkumar Bhale, Sukanta Dey, Santosh Biswas, Sukumar Nandi

BRAIN: Buffer Reservation Attack PreventIoN Using Legitimacy Score in 6LoWPAN Network

Abstract
Internet of Things (IoT) is a network of tangible objects forming a Low-Power Network with each connected device having limited resources and computing power, and each entrusted with a task of data acquisition and transmission to controller devices or users. IoTs are taking over the networking world fast and are bringing the physical and the virtual world ever closer. The most prominent security threat with IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) is the Buffer Reservation Attack. In this paper, this attack has been extensively described, simulated using Contiki cooja simulator and proposed an energy efficient solution named BRAIN that defend against buffer reservation attack. We observe that the legitimacy score based BRAIN approach is improved by 4–35% packet dropping rate and 36.16% average throughput. Along with it reduces 0.09 mJ CPU Energy Computation (CPUENC), 0.14 mJ Transmission Energy (ETX), and 0.08 mJ Reception Energy (ERX).
Pradeepkumar Bhale, Satya Prakash, Santosh Biswas, Sukumar Nandi

TA-ACS: A Trust Aware Adaptive Carrier Selection Scheme for Reliable Routing in Delay Tolerant Networks

Abstract
Delay Tolerant Network (DTN) is an infrastructure-less wireless network characterized with sporadic link connectivity and probable co-existence of high end-to-end delay. It relies on opportunistic contacts for message forwarding and builds an overlay atop disconnected networks to combat network disruptions through persistence storage. The lack of infrastructure and opportunistic contacts make DTN highly vulnerable for misbehaving (both malicious and selfish) nodes. Existence of such nodes have disadvantageous contributions (in terms of network throughput and message overhead) to the network. This paper proposes a novel Trust Aware Adaptive Carrier Selection (TA-ACS) scheme for assuring reliable routing in DTN. The efficiency of TA-ACS is evaluated through extensive simulations study in the presence of misbehaving nodes. Further, a comparative analysis of TA-ACS with other existing schemes has been carried out in terms of message delivery ratio, removed messages count, and message overhead. Results generated from the simulations verified the usability and efficacy of TA-ACS in DTN.
Amrita Bose Paul, Susmita Mondal, Santosh Biswas, Sukumar Nandi

SAS: Seasonality Aware Social-Based Forwarder Selection in Delay Tolerant Networks

Abstract
In social-based delay tolerant network (DTN) applications, hand-held mobile devices exchange information. The inherent social property of DTN has encouraged contemporary researchers in exploiting social metrics to devise forwarding techniques for efficient routing. This work observes evidence of seasonal behavior in contacts between node-pairs in real mobility traces, and exploits it to devise a novel seasonality aware similarity measure. We incorporate seasonality information into tie-strength, and then use it as link weight in a weighted similarity measure which we extend from Katz similarity index. We propose a Seasonality Aware Social-based (SAS) DTN forwarding technique based on the proposed similarity measure and ego-betweenness centrality. Finally we perform real trace driven simulations to show that SAS outperforms baseline social-based DTN forwarding methods significantly.
Amrita Bose Paul, Akhil GV, Santosh Biswas, Sukumar Nandi, Niladri Sett

DAMW: Double Auction Multi-winner Framework for Spectrum Allocation in Cognitive Radio Networks

Abstract
Under-utilization of wireless spectrum by the licensed owners creates spectrum holes which can be opportunistically exploited by secondary users (SUs). By incorporating dynamic spectrum access techniques, Cognitive Radio (CR) emerges as a novel technology which facilitates redistribution of the spectrum holes dynamically. In this context, this paper proposes a double auction framework for CR networks which addresses the channel allocation problem to boost the spectrum utilization efficiency. Multi-winner allocation relates to the condition where a common channel can be utilized by multiple non-interfering SUs which induces spectrum reuse. However, a single SU obtains at most one channel. To avoid disturbances during data transmission, availability time of a channel plays a key role. In this paper, bid submission from SUs rely on channel availability time, and to lease the idle channels, licensed users specify certain ask values. The proposed double auction mechanism develops winner determination and pricing strategies which are proved to be truthful and significantly improves the usage of the radio spectrum. Network simulations validate the improved performance of the proposed auction model compared to the McAfee auction.
Monisha Devi, Nityananda Sarma, Sanjib K. Deka

Social Inclusion and e-Governance: A Case Study in Alirajpur District

Abstract
Kollapalli Ramesh Babu, A. B. Sagar, Preeti Kothari

Designing a Blockchain Based Framework for IoT Data Trade

Abstract
With its application ranging from smart homes and wearables to smart vehicles and smart cities, Internet of Things(IoT) devices have become an integral part of our lives. These devices are enabled with sensing and networking facilities and generate an enormous amount of data, which can be highly valuable for various stakeholders of the system. Enabling the regulated exchange of IoT generated data can enhance the overall efficiency of the IoT based eco-system. However, the current state of the art data exchange frameworks is highly centralized, making it prone to a single point of failure and security breaches. Moreover, the cloud-based systems lack transparency and provide the owners of the IoT devices limited control over the data being exchanged, thus raising the privacy concerns of an individual. Also, the device owners, most of the time, are deprived of receiving proper incentives in exchange for their shared data. Blockchain Technology, with its inherent characteristics of being transparent, decentralized, always available along with smart contracts, can be one of the potential solutions for the problems mentioned above. In this work, we propose, analyze, and discuss a blockchain-based decentralized framework for IoT data trade.
Pranav Kumar Singh, Roshan Singh, Sunit Kumar Nandi, Sukumar Nandi

A Simulation Model for Quality Assurance of e-Governance Projects

Abstract
The use of e-Governance applications for the wellbeing of citizens are increasing day to day. The Government is trying to bring accuracy, availability and transparency in the system for providing services to the public at low cost. Thus the Government to Government (G2G), Government to Citizens (G2C), Government to Business (G2B) and Government to Employees (G2E) services are strengthened with use of Information and Communication Technology (ICT). Digital India Programme was formulated by Government of India for delivering effective e-Governance services in the country. Still, the sustainability, security, availability and reliability of government services is a question to-day. Many e-Governance applications are failing and some others are partially successful. Even successful e-Governance applications need improvements in service delivery, interoperability and longevity. The hassle free integration of different applications is yet to be achieved. The applications working in silo increases redundancy and result in wastage of resources. For optimal usage of resources and provisioning of services to the right person at right time, standardisation of e-Governance services is essential. Lot of standards for quality control and quality assurance are already available in different service areas including ICT. Besides international standards in Software Engineering, the Government of India emphasizes on e-Governance standards, interoperability framework, quality assurance framework, metadata & data standards and other areas to reduce failure and improvising the channels of service delivery to the public. The participation of users in governance is also encouraged to improve the quality of service. This paper focuses on provisioning a Simulation model for effective measurement of sector wise quality as well as the total quality assurance of the e-Governance projects. For an e-Governance application, in addition to software quality, the process quality, data quality and managerial quality sectors are also need to be taken care of for better result. The Simulation model will help in measuring the quality more accurately with qualitative and quantitative parameters and establish the relationship among different quality sectors of an e-Governance application. Consequently, it would be helpful in reducing the failure of e-Governance projects and create confidence in the stakeholders’ mind.
Pabitrananda Patnaik, Subhashree Pattnaik, Pratibha Singh