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Kaur, Jasleen, Singh, Tejpreet, Lakhwani, Kamlesh.  2019.  An Enhanced Approach for Attack Detection in VANETs Using Adaptive Neuro-Fuzzy System. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :191—197.
Vehicular Ad-hoc Networks (VANETs) are generally acknowledged as an extraordinary sort of Mobile Ad hoc Network (MANET). VANETs have seen enormous development in a decade ago, giving a tremendous scope of employments in both military and in addition non-military personnel exercises. The temporary network in the vehicles can likewise build the driver's capability on the road. In this paper, an effective information dispersal approach is proposed which enhances the vehicle-to-vehicle availability as well as enhances the QoS between the source and the goal. The viability of the proposed approach is shown with regards to the noteworthy gets accomplished in the parameters in particular, end to end delay, packet drop ratio, average download delay and throughput in comparison with the existing approaches.
Kaur, Kudrat Jot, Hahn, Adam.  2018.  Exploring Ensemble Classifiers for Detecting Attacks in the Smart Grids. Proceedings of the Fifth Cybersecurity Symposium. :13:1–13:4.
The advent of machine learning has made it a popular tool in various areas. It has also been applied in network intrusion detection. However, machine learning hasn't been sufficiently explored in the cyberphysical domains such as smart grids. This is because a lot of factors weigh in while using these tools. This paper is about intrusion detection in smart grids and how some machine learning techniques can help achieve this goal. It considers the problems of feature and classifier selection along with other data ambiguities. The goal is to apply the machine learning ensemble classifiers on the smart grid traffic and evaluate if these methods can detect anomalies in the system.
Kaur, M., Malik, A..  2018.  An Efficient and Reliable Routing Protocol Using Bio-Inspired Techniques for Congestion Control in WSN. 2018 4th International Conference on Computing Sciences (ICCS). :15—22.

In wireless sensor networks (WSNs), congestion control is a very essential region of concern. When the packets that are coming get increased than the actual capacity of network or nodes results into congestion in the network. Congestion in network can cause reduction in throughput, increase in network delay, and increase in packet loss and sensor energy waste. For that reason, new complex methods are mandatory to tackle with congestion. So it is necessary to become aware of congestion and manage the congested resources in wireless sensor networks for enhancing the network performance. Diverse methodologies for congestion recognition and prevention have been presented in the previous couple of years. To handle some of the problems, this paper exhibits a new technique for controlling the congestion. An efficient and reliable routing protocol (ERRP) based on bio inspired algorithms is introduced in this paper for solving congestion problem. In the proposed work, a way is calculated to send the packets on the new pathway. The proposed work has used three approaches for finding the path which results into a congestion free path. Our analysis and simulation results shows that our approach provides better performance as compared to previous approaches in terms of throughput, packet loss, delay etc.

Kaur, Prabhjot, Kang, Sandeep Singh.  2019.  Trust Aware Routing Protocols in Wireless Body Area Networks. 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom). :1106–1112.

The technology made it easier to design the sensors of small size such that human can easily wear/implant them on his body and free to do his regular activities without any interruption. These tiny sensors can monitor, track and record the physical and environmental changes occurred in the surrounding. It is preferred to deploy the sensors where the regular continuous interference of human is very difficult. For a quality life, healthcare is the main concern today. Wireless Body Area Networks (WBAN) can play an important role in improving the quality of life. The main contribution of this paper is to review the trust-aware routing protocols which are able to detect the malicious nodes during communication by using node's trust factor as important metric to make the node to node communication secure. In this paper, we also present an overview of the WAN, its architecture, communication technologies used, various routing parameters, applications, security issues, and challenges. We further give a brief discussion about the flaws in the existing trust-aware routing protocols of WBAN.

Kaur, R., Singh, A., Singh, S., Sharma, S..  2016.  Security of software defined networks: Taxonomic modeling, key components and open research area. 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). :2832–2839.

Software defined networking promises network operators to dramatically simplify network management. It provides flexibility and innovation through network programmability. With SDN, network management moves from codifying functionality in terms of low-level device configuration to building software that facilitates network management and debugging[1]. SDN provides new techniques to solve long-standing problems in networking like routing by separating the complexity of state distribution from network specification. Despite all the hype surrounding SDNs, exploiting its full potential is demanding. Security is still the major issue and a striking challenge that reduces the growth of SDNs. Moreover the introduction of various architectural components and up cycling of novel entities of SDN poses new security issues and threats. SDN is considered as major target for digital threats and cyber-attacks[2] and have more devastating effects than simple networks. Initial SDN design doesn't considered security as its part; therefore, it must be raised on the agenda. This article discusses the security solutions proposed to secure SDNs. We categorize the security solutions in the article by presenting a thematic taxonomy based on SDN architectural layers/interfaces[3], security measures and goals, simulation framework. Moreover, the literature also points out the possible attacks[2] targeting different layers/interfaces of SDNs. For securing SDNs, the potential requirements and their key enablers are also identified and presented. Also, the articles sketch the design of secure and dependable SDNs. At last, we discuss open issues and challenges of SDN security that may be rated appropriate to be handled by professionals and researchers in the future.

Kaur, R., Singh, S..  2015.  Detecting anomalies in Online Social Networks using graph metrics. 2015 Annual IEEE India Conference (INDICON). :1–6.

Online Social Networks have emerged as an interesting area for analysis where each user having a personalized user profile interact and share information with each other. Apart from analyzing the structural characteristics, detection of abnormal and anomalous activities in social networks has become need of the hour. These anomalous activities represent the rare and mischievous activities that take place in the network. Graphical structure of social networks has encouraged the researchers to use various graph metrics to detect the anomalous activities. One such measure that seemed to be highly beneficial to detect the anomalies was brokerage value which helped to detect the anomalies with high accuracy. Also, further application of the measure to different datasets verified the fact that the anomalous behavior detected by the proposed measure was efficient as compared to the already proposed measures in Oddball Algorithm.

Kaur, R., Singh, M..  2014.  A Survey on Zero-Day Polymorphic Worm Detection Techniques. Communications Surveys Tutorials, IEEE. 16:1520-1549.

Zero-day polymorphic worms pose a serious threat to the Internet security. With their ability to rapidly propagate, these worms increasingly threaten the Internet hosts and services. Not only can they exploit unknown vulnerabilities but can also change their own representations on each new infection or can encrypt their payloads using a different key per infection. They have many variations in the signatures of the same worm thus, making their fingerprinting very difficult. Therefore, signature-based defenses and traditional security layers miss these stealthy and persistent threats. This paper provides a detailed survey to outline the research efforts in relation to detection of modern zero-day malware in form of zero-day polymorphic worms.

Kaur, S., Singh, S..  2020.  Highly Secured all Optical DIM Codes using AND Gate. 2020 Indo – Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN). :64—68.
Optical Code Division Multiple Access (OCDMA) is an inevitable innovation to cope up with the impediments of regularly expanding information traffic and numerous user accesses in optical systems. In Spectral Amplitude Coding (SAC)-OCDMA systems cross correlation and Multiple Access Interference (MAI) are utmost concerns. For eliminating the cross correlation, reducing the MAI and to enhance the security, in this work, all optical Diagonal Identity Matrices codes (DIM) with Zero Cross-Correlation (ZCC) and optical gating are presented. Chip rate of the proposed work is 0.03 ns and total 60 users are considered with semiconductor optical amplifier based AND operation. Effects of optical gating are analyzed in the presence/absence of eavesdropper in terms of Q factor and received extinction ratio. Proposed system has advantages for service provider because this is mapping free technique and can be easily designed for large number of users.
Kaur, S., Jindal, A..  2020.  Singular Value Decomposition (SVD) based Image Tamper Detection Scheme. 2020 International Conference on Inventive Computation Technologies (ICICT). :695—699.
Image authentication techniques are basically used to check whether the received document is accurate or actual as it was transmitted by the source node or not. Image authentication ensures the integrity of the digital images and identify the ownership of the copyright of the digital images. Singular Value Decomposition (SVD) is method based on spatial domain which is used to extract important features from an image. SVD function decomposes an image into three matrices (U, S, V), the S matrix is a diagonal matrix constitutes singular values. These values are important features of that particular image. The quick response code features are utilized to create QR code from the extracted values. The evaluations produced represents that this designed method is better in producing authenticated image as compared to existing schemes.
Kaushal, P. K., Bagga, A., Sobti, R..  2017.  Evolution of bitcoin and security risk in bitcoin wallets. 2017 International Conference on Computer, Communications and Electronics (Comptelix). :172–177.

This paper identifies trust factor and rewarding nature of bitcoin system, and analyzes bitcoin features which may facilitate bitcoin to emerge as a universal currency. Paper presents the gap between proposed theoretical-architecture and current practical-implementation of bitcoin system in terms of achieving decentralization, anonymity of users, and consensus. Paper presents three different ways in which a user can manage bitcoins. We attempt to identify the security risk and feasible attacks on these configurations of bitcoin management. We have shown that not all bitcoin wallets are safe against all possible types of attacks. Bitcoin core is only safest mode of operating bitcoin till date as it is secure against all feasible attacks, and is vulnerable only against block-chain rewriting.

Kaushik, Ila, Sharma, Nikhil, Singh, Nanhay.  2019.  Intrusion Detection and Security System for Blackhole Attack. 2019 2nd International Conference on Signal Processing and Communication (ICSPC). :320—324.

Communication is considered as an essential part of our lives. Different medium was used for exchange of information, but due to advancement in field of technology, different network setup came into existence. One of the most suited in wireless field is Wireless Sensor Network (WSN). These networks are set up by self-organizing nodes which operate over radio environment. Since communication is done more rapidly, they are confined to many attacks which operate at different layers. In order to have efficient communication, some security measure must be introduced in the network ho have secure communication. In this paper, we describe various attacks functioning at different layers also one of the common network layer attack called Blackhole Attack with its mitigation technique using Intrusion Detection System (IDS) over network simulator ns2 has been discussed.

Kautsarina, Anggorojati, Bayu.  2018.  A Conceptual Model for Promoting Positive Security Behavior in Internet of Things Era. 2018 Global Wireless Summit (GWS). :358–363.
As the Internet of Things (IoT) era raise, billions of additional connected devices in new locations and applications will create new challenges. Security and privacy are among the major challenges in IoT as any breaches and misuse in those aspects will have the adverse impact on users. Among many factors that determine the security of any system, human factor is the most important aspect to be considered; as it is renowned that human is the weakest link in the information security cycle. Experts express the need to increase cyber resilience culture and a focus on the human factors involved in cybersecurity to counter cyber risks. The aim of this study is to propose a conceptual model to improve cyber resilience in IoT users that is adapted from a model in public health sector. Cyber resilience is improved through promoting security behavior by gathering the existing knowledge and gain understanding about every contributing aspects. The proposed approach is expected to be used as foundation for government, especially in Indonesia, to derive strategies in improving cyber resilience of IoT users.
Kavitha, R., Malathi, K., Kunjachen, L. M..  2020.  Interference of Cyber Endanger using Support Vector Machine. 2020 International Conference on Computer Communication and Informatics (ICCCI). :1–4.
The wonder of cyberbullying, implied as persistent and repeated mischief caused through the use of PC systems, mobile phones, and noteworthy propelled contraptions. for instance, Hinduja and Patching upheld that 10-forty% of outlined children masses surrendered having dealt with it each as a harmed individual or as a with the guide of the use of-stander wherein additional progressively young individuals use development to issue, undermine, embarrass, or by and large burden their mates. Advanced badgering has starting at now been said as one which reason first rate harm to society and monetary machine. Advances in development related with web record remark and the assortment of the web associations renders the area and following of such models as a credibility hard and extremely problematic. This paper portrays a web structure for robotized revelation and seeing of Cyber-tormenting cases from on-line exchanges and on line associations. The device is mainly assembled completely absolutely as for the revelation of 3 basic ordinary language sections like Insults, Swears and 2d person. A sort machine and cosmology like reasoning had been contracted to go over the normality of such substances inside the trade board/web documents, which may conceivable explanation a message to security in case you have to take fitting improvement. The instrument has been dissected on staggering social occasions and achieves less steeply-esteemed acknowledgment displays.
Kawaguchi, Ikkaku, Kodama, Yuki, Kuzuoka, Hideaki, Otsuki, Mai, Suzuki, Yusuke.  2016.  Effect of Embodiment Presentation by Humanoid Robot on Social Telepresence. Proceedings of the Fourth International Conference on Human Agent Interaction. :253–256.

In this study, we used a humanoid robot as a telepresence robot and compared with the basic telepresence robot which can only rotate the display in order to reveal the effect of embodiment. We also investigated the effect caused by changing the body size of the humanoid robot by using two different size of robots. Our experimental results revealed that the embodiment increases the remote person's social telepresence, familiarity, and directivity. The comparison between small and big humanoid robots showed no difference and both of them were effective.

Kawanishi, Y., Nishihara, H., Souma, D., Yoshida, H., Hata, Y..  2018.  A Study on Quantitative Risk Assessment Methods in Security Design for Industrial Control Systems. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :62-69.

In recent years, there has been progress in applying information technology to industrial control systems (ICS), which is expected to make the development cost of control devices and systems lower. On the other hand, the security threats are becoming important problems. In 2017, a command injection issue on a data logger was reported. In this paper, we focus on the risk assessment in security design for data loggers used in industrial control systems. Our aim is to provide a risk assessment method optimized for control devices and systems in such a way that one can prioritize threats more preciously, that would lead work resource (time and budget) can be assigned for more important threats than others. We discuss problems with application of the automotive-security guideline of JASO TP15002 to ICS risk assessment. Consequently, we propose a three-phase risk assessment method with a novel Risk Scoring Systems (RSS) for quantitative risk assessment, RSS-CWSS. The idea behind this method is to apply CWSS scoring systems to RSS by fixing values for some of CWSS metrics, considering what the designers can evaluate during the concept phase. Our case study with ICS employing a data logger clarifies that RSS-CWSS can offer an interesting property that it has better risk-score dispersion than the TP15002-specified RSS.

Kayes, A.S.M., Hammoudeh, Mohammad, Badsha, Shahriar, Watters, Paul A., Ng, Alex, Mohammed, Fatma, Islam, Mofakharul.  2020.  Responsibility Attribution Against Data Breaches. 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT). :498–503.
Electronic crimes like data breaches in healthcare systems are often a fundamental failures of access control mechanisms. Most of current access control systems do not provide an accessible way to engage users in decision making processes, about who should have access to what data and when. We advocate that a policy ontology can contribute towards the development of an effective access control system by attributing responsibility for data breaches. We propose a responsibility attribution model as a theoretical construct and discuss its implication by introducing a cost model for data breach countermeasures. Then, a policy ontology is presented to realize the proposed responsibility and cost models. An experimental study on the performance of the proposed framework is conducted with respect to a more generic access control framework. The practicality of the proposed solution is demonstrated through a case study from the healthcare domain.
Kazemi, M., Azmi, R..  2014.  Privacy preserving and anonymity in multi sinks wireless sensor networks with master sink. Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on. :1-7.

The wireless network is become larger than past. So in the recent years the wireless with multiple sinks is more useful. The anonymity and privacy in this network is a challenge now. In this paper, we propose a new method for anonymity in multi sink wireless sensor network. In this method we use layer encryption to provide source and event privacy and we use a label switching routing method to provide sink anonymity in each cluster. A master sink that is a powerful base station is used to connect sinks to each other.

Kazemi, M., Delavar, M., Mohajeri, J., Salmasizadeh, M..  2018.  On the Security of an Efficient Anonymous Authentication with Conditional Privacy-Preserving Scheme for Vehicular Ad Hoc Networks. Iranian Conference on Electrical Engineering (ICEE). :510–514.

Design of anonymous authentication scheme is one of the most important challenges in Vehicular Ad hoc Networks (VANET). Most of the existing schemes have high computational and communication overhead and they do not meet security requirements. Recently, Azees et al. have introduced an Efficient Anonymous Authentication with Conditional Privacy-Preserving (EAAP) scheme for VANET and claimed that it is secure. In this paper, we show that this protocol is vulnerable against replay attack, impersonation attack and message modification attack. Also, we show that the messages sent by a vehicle are linkable. Therefore, an adversary can easily track the vehicles. In addition, it is shown that vehicles face with some problems when they enter in a new Trusted Authority (TA) range. As a solution, we propose a new authentication protocol which is more secure than EAAP protocol without increasing its computational and communication overhead.

Kazemi, Z., Fazeli, M., Hély, D., Beroulle, V..  2020.  Hardware Security Vulnerability Assessment to Identify the Potential Risks in A Critical Embedded Application. 2020 IEEE 26th International Symposium on On-Line Testing and Robust System Design (IOLTS). :1—6.

Internet of Things (IoT) is experiencing significant growth in the safety-critical applications which have caused new security challenges. These devices are becoming targets for different types of physical attacks, which are exacerbated by their diversity and accessibility. Therefore, there is a strict necessity to support embedded software developers to identify and remediate the vulnerabilities and create resilient applications against such attacks. In this paper, we propose a hardware security vulnerability assessment based on fault injection of an embedded application. In our security assessment, we apply a fault injection attack by using our clock glitch generator on a critical medical IoT device. Furthermore, we analyze the potential risks of ignoring these attacks in this embedded application. The results will inform the embedded software developers of various security risks and the required steps to improve the security of similar MCU-based applications. Our hardware security assessment approach is easy to apply and can lead to secure embedded IoT applications against fault attacks.

Ke, Liyiming, Li, Bo, Vorobeychik, Yevgeniy.  2016.  Behavioral Experiments in Email Filter Evasion.

Despite decades of effort to combat spam, unwanted and even malicious emails, such as phish which aim to deceive recipients into disclosing sensitive information, still routinely find their way into one’s mailbox. To be sure, email filters manage to stop a large fraction of spam emails from ever reaching users, but spammers and phishers have mastered the art of filter evasion, or manipulating the content of email messages to avoid being filtered. We present a unique behavioral experiment designed to study email filter evasion. Our experiment is framed in somewhat broader terms: given the widespread use of machine learning methods for distinguishing spam and non-spam, we investigate how human subjects manipulate a spam template to evade a classification-based filter. We find that adding a small amount of noise to a filter significantly reduces the ability of subjects to evade it, observing that noise does not merely have a short-term impact, but also degrades evasion performance in the longer term. Moreover, we find that greater coverage of an email template by the classifier (filter) features significantly increases the difficulty of evading it. This observation suggests that aggressive feature reduction—a common practice in applied machine learning—can actually facilitate evasion. In addition to the descriptive analysis of behavior, we develop a synthetic model of human evasion behavior which closely matches observed behavior and effectively replicates experimental findings in simulation.

Ke, Qi, Sheng, Lin.  2019.  Content Adaptive Image Steganalysis in Spatial Domain Using Selected Co-Occurrence Features. 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). :28–33.

In this paper, a general content adaptive image steganography detector in the spatial domain is proposed. We assemble conventional Haar and LBP features to construct local co-occurrence features, then the boosted classifiers are used to assemble the features as well as the final detector, and each weak classifier of the boosted classifiers corresponds to the co-occurrence feature of a local image region. Moreover, the classification ability and the generalization power of the candidate features are both evaluated for decision in the feature selection procedure of boosting training, which makes the final detector more accuracy. The experimental results on standard dataset show that the proposed framework can detect two primary content adaptive stego algorithms in the spatial domain with higher accuracy than the state-of-the-art steganalysis method.

Ke, Yu-Ming, Chen, Chih-Wei, Hsiao, Hsu-Chun, Perrig, Adrian, Sekar, Vyas.  2016.  CICADAS: Congesting the Internet with Coordinated and Decentralized Pulsating Attacks. Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security. :699–710.

This study stems from the premise that we need to break away from the "reactive" cycle of developing defenses against new DDoS attacks (e.g., amplification) by proactively investigating the potential for new types of DDoS attacks. Our specific focus is on pulsating attacks, a particularly debilitating type that has been hypothesized in the literature. In a pulsating attack, bots coordinate to generate intermittent pulses at target links to significantly reduce the throughput of TCP connections traversing the target. With pulsating attacks, attackers can cause significantly greater damage to legitimate users than traditional link flooding attacks. To date, however, pulsating attacks have been either deemed ineffective or easily defendable for two reasons: (1) they require a central coordinator and can thus be tracked; and (2) they require tight synchronization of pulses, which is difficult even in normal non-congestion scenarios. This paper argues that, in fact, the perceived drawbacks of pulsating attacks are in fact not fundamental. We develop a practical pulsating attack called CICADAS using two key ideas: using both (1) congestion as an implicit signal for decentralized implementation, and (2) a Kalman-filter-based approach to achieve tight synchronization. We validate CICADAS using simulations and wide-area experiments. We also discuss possible countermeasures against this attack.

Kearney, Paul, Asal, Rasool.  2019.  ERAMIS: A Reference Architecture-Based Methodology for IoT Systems. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:366—367.

Opportunities arising from IoT-enabled applications are significant, but market growth is inhibited by concerns over security and complexity. To address these issues, we propose the ERAMIS methodology, which is based on instantiation of a reference architecture that captures common design features, embodies best practice, incorporates good security properties by design, and makes explicit provision for operational security services and processes.

Kebande, V. R., Kigwana, I., Venter, H. S., Karie, N. M., Wario, R. D..  2018.  CVSS Metric-Based Analysis, Classification and Assessment of Computer Network Threats and Vulnerabilities. 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD). :1–10.

This paper provides a Common Vulnerability Scoring System (CVSS) metric-based technique for classifying and analysing the prevailing Computer Network Security Vulnerabilities and Threats (CNSVT). The problem that is addressed in this paper, is that, at the time of writing this paper, there existed no effective approaches for analysing and classifying CNSVT for purposes of assessments based on CVSS metrics. The authors of this paper have achieved this by generating a CVSS metric-based dynamic Vulnerability Analysis Classification Countermeasure (VACC) criterion that is able to rank vulnerabilities. The CVSS metric-based VACC has allowed the computation of vulnerability Similarity Measure (VSM) using the Hamming and Euclidean distance metric functions. Nevertheless, the CVSS-metric based on VACC also enabled the random measuring of the VSM for a selected number of vulnerabilities based on the [Ma-Ma], [Ma-Mi], [Mi-Ci], [Ma-Ci] ranking score. This is a technique that is aimed at allowing security experts to be able to conduct proper vulnerability detection and assessments across computer-based networks based on the perceived occurrence by checking the probability that given threats will occur or not. The authors have also proposed high-level countermeasures of the vulnerabilities that have been listed. The authors have evaluated the CVSS-metric based VACC and the results are promising. Based on this technique, it is worth noting that these propositions can help in the development of stronger computer and network security tools.

Kebande, V. R., Karie, N. M., Venter, H. S..  2017.  Cloud-Centric Framework for Isolating Big Data as Forensic Evidence from IoT Infrastructures. 2017 1st International Conference on Next Generation Computing Applications (NextComp). :54–60.

Cloud computing paradigm continues to revolutionize the way business processes are being conducted through the provision of massive resources, reliability across networks and ability to offer parallel processing. However, miniaturization, proliferation and nanotechnology within devices has enabled digitization of almost every object which eventually has seen the rise of a new technological marvel dubbed Internet of Things (IoT). IoT enables self-configurable/smart devices to connect intelligently through Radio Frequency Identification (RFID), WI-FI, LAN, GPRS and other methods by further enabling timeously processing of information. Based on these developments, the integration of the cloud and IoT infrastructures has led to an explosion of the amount of data being exchanged between devices which have in turn enabled malicious actors to use this as a platform to launch various cybercrime activities. Consequently, digital forensics provides a significant approach that can be used to provide an effective post-event response mechanism to these malicious attacks in cloud-based IoT infrastructures. Therefore, the problem being addressed is that, at the time of writing this paper, there still exist no accepted standards or frameworks for conducting digital forensic investigation on cloud-based IoT infrastructures. As a result, the authors have proposed a cloud-centric framework that is able to isolate Big data as forensic evidence from IoT (CFIBD-IoT) infrastructures for proper analysis and examination. It is the authors' opinion that if the CFIBD-IoT framework is implemented fully it will support cloud-based IoT tool creation as well as support future investigative techniques in the cloud with a degree of certainty.