Visible to the public Biblio

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2020-06-26
Yan, Liang.  2019.  Dynamic Mulitiple Agent Based IoT Security Management System. 2019 IEEE 2nd International Conference on Information Communication and Signal Processing (ICICSP). :48—51.
It is important to provide strong security for IoT devices with limited security related resources. We introduce a new dynamic security agent management framework, which dynamically chooses the best security agent to support security functions depending on the applications' security requirements of IoT devices in the system. This framework is designed to overcome the challenges including high computation costs, multiple security protocol compatibility, and efficient energy management in IoT system.
Salman, Ahmad, El-Tawab, Samy.  2019.  Efficient Hardware/Software Co-Design of Elliptic-Curve Cryptography for the Internet of Things. 2019 International Conference on Smart Applications, Communications and Networking (SmartNets). :1—6.

The Internet of Things (IoT) is connecting the world in a way humanity has never seen before. With applications in healthcare, agricultural, transportation, and more, IoT devices help in bridging the gap between the physical and the virtual worlds. These devices usually carry sensitive data which requires security and protection in transit and rest. However, the limited power and energy consumption make it harder and more challenging to implementing security protocols, especially Public-Key Cryptosystems (PKC). In this paper, we present a hardware/software co-design for Elliptic-Curve Cryptography (ECC) PKC suitable for lightweight devices. We present the implementation results for our design on an edge node to be used for indoor localization in a healthcare facilities.

2020-06-19
Haefner, Kyle, Ray, Indrakshi.  2019.  ComplexIoT: Behavior-Based Trust For IoT Networks. 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :56—65.

This work takes a novel approach to classifying the behavior of devices by exploiting the single-purpose nature of IoT devices and analyzing the complexity and variance of their network traffic. We develop a formalized measurement of complexity for IoT devices, and use this measurement to precisely tune an anomaly detection algorithm for each device. We postulate that IoT devices with low complexity lead to a high confidence in their behavioral model and have a correspondingly more precise decision boundary on their predicted behavior. Conversely, complex general purpose devices have lower confidence and a more generalized decision boundary. We show that there is a positive correlation to our complexity measure and the number of outliers found by an anomaly detection algorithm. By tuning this decision boundary based on device complexity we are able to build a behavioral framework for each device that reduces false positive outliers. Finally, we propose an architecture that can use this tuned behavioral model to rank each flow on the network and calculate a trust score ranking of all traffic to and from a device which allows the network to autonomously make access control decisions on a per-flow basis.

Novak, Marek, Skryja, Petr.  2019.  Efficient Partial Firmware Update for IoT Devices with Lua Scripting Interface. 2019 29th International Conference Radioelektronika (RADIOELEKTRONIKA). :1—4.

The paper introduces a method of efficient partial firmware update with several advantages compared to common methods. The amount of data to transfer for an update is reduced, the energetic efficiency is increased and as the method is designed for over the air update, the radio spectrum occupancy is decreased. Herein described approach uses Lua scripting interface to introduce updatable fragments of invokable native code. This requires a dedicated memory layout, which is herein introduced. This method allows not only to distribute patches for deployed systems, but also on demand add-ons. At the end, the security aspects of proposed firmware update system is discussed and its limitations are presented.

2020-06-01
da Silva Andrade, Richardson B., Souto Rosa, Nelson.  2019.  MidSecThings: Assurance Solution for Security Smart Homes in IoT. 2019 IEEE 19th International Symposium on High Assurance Systems Engineering (HASE). :171–178.
The interest over building security-based solutions to reduce the vulnerability exploits and mitigate the risks associated with smart homes in IoT is growing. However, our investigation identified to architect and implement distributed security mechanisms is still a challenge because is necessary to handle security and privacy in IoT middleware with a strong focus. Our investigation, it was identified the significant proportion of the systems that did not address security and did not describe the security approach in any meaningful detail. The idea proposed in this work is to provide middleware aim to implement security mechanisms in smart home and contribute as how guide to beginner developers' IoT middleware. The advantages of using MidSecThings are to avoid leakage data, unavailable service, unidentification action and not authorized access over IoT devices in smart home.
Talusan, Jose Paolo, Tiausas, Francis, Yasumoto, Keiichi, Wilbur, Michael, Pettet, Geoffrey, Dubey, Abhishek, Bhattacharjee, Shameek.  2019.  Smart Transportation Delay and Resiliency Testbed Based on Information Flow of Things Middleware. 2019 IEEE International Conference on Smart Computing (SMARTCOMP). :13–18.
Edge and Fog computing paradigms are used to process big data generated by the increasing number of IoT devices. These paradigms have enabled cities to become smarter in various aspects via real-time data-driven applications. While these have addressed some flaws of cloud computing some challenges remain particularly in terms of privacy and security. We create a testbed based on a distributed processing platform called the Information flow of Things (IFoT) middleware. We briefly describe a decentralized traffic speed query and routing service implemented on this framework testbed. We configure the testbed to test countermeasure systems that aim to address the security challenges faced by prior paradigms. Using this testbed, we investigate a novel decentralized anomaly detection approach for time-sensitive distributed smart transportation systems.
Sarrab, Mohamed, Alnaeli, Saleh M..  2018.  Critical Aspects Pertaining Security of IoT Application Level Software Systems. 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). :960–964.
With the prevalence of Internet of Things (IoT) devices and systems, touching almost every single aspect of our modern life, one core factor that will determine whether this technology will succeed, and gain people trust, or fail is security. This technology aimed to facilitate and improve the quality of our life; however, it is hysterical and fast growth makes it an attractive and prime target for a whole variety of hackers posing a significant risk to our technology and IT infrastructures at both enterprise and individual levels. This paper discusses and identifies some critical aspects from software security perspective that need to be addressed and considered when designing IoT applications. This paper mainly concerned with potential security issues of the applications running on IoT devices including insecure interfaces, insecure software, constrained application protocol and middleware security. This effort is part of a funded research project that investigates internet of things (IoT) security and privacy issues related to architecture, connectivity and data collection.
Luo, Xupeng, Yan, Qiao, Wang, Mingde, Huang, Wenyao.  2019.  Using MTD and SDN-based Honeypots to Defend DDoS Attacks in IoT. 2019 Computing, Communications and IoT Applications (ComComAp). :392–395.
With the rapid development of Internet of Things (IoT), distributed denial of service (DDoS) attacks become the important security threat of the IoT. Characteristics of IoT, such as large quantities and simple function, which have easily caused the IoT devices or servers to be attacked and be turned into botnets for launching DDoS attacks. In this paper, we use software-defined networking (SDN) to develop moving target defense (MTD) architecture that increases uncertainty because of ever changing attack surface. In addition, we deploy SDN-based honeypots to mimic IoT devices, luring attackers and malwares. Finally, experimental results show that combination of MTD and SDN-based honeypots can effectively hide network asset from scanner and defend against DDoS attacks in IoT.
2020-05-29
Arefin, Sayed Erfan, Heya, Tasnia Ashrafi, Chakrabarty, Amitabha.  2019.  Agent Based Fog Architecture using NDN and Trust Management for IoT. TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON). :257—262.

Statistics suggests, proceeding towards IoT generation, is increasing IoT devices at a drastic rate. This will be very challenging for our present-day network infrastructure to manage, this much of data. This may risk, both security and traffic collapsing. We have proposed an infrastructure with Fog Computing. The Fog layer consists two layers, using the concepts of Service oriented Architecture (SOA) and the Agent based composition model which ensures the traffic usage reduction. In order to have a robust and secured system, we have modified the Fog based agent model by replacing the SOA with secured Named Data Network (NDN) protocol. Knowing the fact that NDN has the caching layer, we are combining NDN and with Fog, as it can overcome the forwarding strategy limitation and memory constraints of NDN by the Agent Society, in the Middle layer along with Trust management.

2020-05-15
Ge, Mengmeng, Fu, Xiping, Syed, Naeem, Baig, Zubair, Teo, Gideon, Robles-Kelly, Antonio.  2019.  Deep Learning-Based Intrusion Detection for IoT Networks. 2019 IEEE 24th Pacific Rim International Symposium on Dependable Computing (PRDC). :256—25609.

Internet of Things (IoT) has an immense potential for a plethora of applications ranging from healthcare automation to defence networks and the power grid. The security of an IoT network is essentially paramount to the security of the underlying computing and communication infrastructure. However, due to constrained resources and limited computational capabilities, IoT networks are prone to various attacks. Thus, safeguarding the IoT network from adversarial attacks is of vital importance and can be realised through planning and deployment of effective security controls; one such control being an intrusion detection system. In this paper, we present a novel intrusion detection scheme for IoT networks that classifies traffic flow through the application of deep learning concepts. We adopt a newly published IoT dataset and generate generic features from the field information in packet level. We develop a feed-forward neural networks model for binary and multi-class classification including denial of service, distributed denial of service, reconnaissance and information theft attacks against IoT devices. Results obtained through the evaluation of the proposed scheme via the processed dataset illustrate a high classification accuracy.

Egert, Rolf, Grube, Tim, Born, Dustin, Mühlhäuser, Max.  2019.  Modular Vulnerability Indication for the IoT in IP-Based Networks. 2019 IEEE Globecom Workshops (GC Wkshps). :1—6.

With the rapidly increasing number of Internet of Things (IoT) devices and their extensive integration into peoples' daily lives, the security of those devices is of primary importance. Nonetheless, many IoT devices suffer from the absence, or the bad application, of security concepts, which leads to severe vulnerabilities in those devices. To achieve early detection of potential vulnerabilities, network scanner tools are frequently used. However, most of those tools are highly specialized; thus, multiple tools and a meaningful correlation of their results are required to obtain an adequate listing of identified network vulnerabilities. To simplify this process, we propose a modular framework for automated network reconnaissance and vulnerability indication in IP-based networks. It allows integrating a diverse set of tools as either, scanning tools or analysis tools. Moreover, the framework enables result aggregation of different modules and allows information sharing between modules facilitating the development of advanced analysis modules. Additionally, intermediate scanning and analysis data is stored, enabling a historical view of derived information and also allowing users to retrace decision-making processes. We show the framework's modular capabilities by implementing one scanner module and three analysis modules. The automated process is then evaluated using an exemplary scenario with common IP-based IoT components.

2020-05-08
Bolla, R., Carrega, A., Repetto, M..  2019.  An abstraction layer for cybersecurity context. 2019 International Conference on Computing, Networking and Communications (ICNC). :214—218.

The growing complexity and diversification of cyber-attacks are largely reflected in the increasing sophistication of security appliances, which are often too cumbersome to be run in virtual services and IoT devices. Hence, the design of cyber-security frameworks is today looking at more cooperative models, which collect security-related data from a large set of heterogeneous sources for centralized analysis and correlation.In this paper, we outline a flexible abstraction layer for access to security context. It is conceived to program and gather data from lightweight inspection and enforcement hooks deployed in cloud applications and IoT devices. We also provide a preliminary description of its implementation, by reviewing the main software components and their role.

2020-04-13
Lange, Thomas, Kettani, Houssain.  2019.  On Security Threats of Botnets to Cyber Systems. 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN). :176–183.
As the dynamics of cyber warfare continue to change, it is very important to be aware of the issues currently confronting cyberspace. One threat which continues to grow in the danger it poses to cyber security are botnets. Botnets can launch massive Distributed Denial of Service (DDoS) attacks against internet connected hosts anonymously, undertake intricate spam campaigns, launch mass financial fraud campaigns, and even manipulate public opinion via social media bots. The network topology and technology undergirding each botnet varies greatly, as do the motivations commonly behind such networks. Furthermore, as botnets have continued to evolve, many newer ones demonstrate increased levels of anonymity and sophistication, making it more difficult to effectively counter them. Increases in the production of vulnerable Internet of Things (IoT) devices has made it easier for malicious actors to quickly assemble sizable botnets. Because of this, the steps necessary to stop botnets also vary, and in some cases, it may be extremely difficult to effectively defeat a fully functional and sophisticated botnet. While in some cases, the infrastructure supporting the botnet can be targeted and remotely disabled, other cases require the physical assistance of law enforcement to shut down the botnet. In the latter case, it is often a significant challenge to cheaply end a botnet. On the other hand, there are many steps and mitigations that can be taken by end-users to prevent their own devices from becoming part of a botnet. Many of these solutions involve implementing basic cybersecurity practices like installing firewalls and changing default passwords. More sophisticated botnets may require similarly sophisticated intrusion detection systems, to detect and remove malicious infections. Much research has gone into such systems and in recent years many researchers have begun to implement machine learning techniques to defeat botnets. This paper is intended present a review on botnet evolution, trends and mitigations, and offer related examples and research to provide the reader with quick access to a broad understanding of the issues at hand.
2020-04-10
Mucchi, Lorenzo, Nizzi, Francesca, Pecorella, Tommaso, Fantacci, Romano, Esposito, Flavio.  2019.  Benefits of Physical Layer Security to Cryptography: Tradeoff and Applications. 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). :1—3.
Physical-layer security (PLS) has raised the attention of the research community in recent years, particularly for Internet of things (IoT) applications. Despite the use of classical cryptography, PLS provides security at physical layer, regardless of the computational power owned by the attacker. The investigations on PLS are numerous in the literature, but one main issue seems to be kept apart: how to measure the benefit that PLS can bring to cryptography? This paper tries to answer this question with an initial performance analysis of PLS in conjunction with typical cryptography of wireless communication protocols. Our results indicate that PLS can help cryptography to harden the attacker job in real operative scenario: PLS can increase the detection errors at the attacker's receiver, leading to inability to recover the cipher key, even if the plaintext is known.
2020-03-30
Verma, Rajat Singh, Chandavarkar, B. R., Nazareth, Pradeep.  2019.  Mitigation of hard-coded credentials related attacks using QR code and secured web service for IoT. 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–5.
Hard-coded credentials such as clear text log-in id and password provided by the IoT manufacturers and unsecured ways of remotely accessing IoT devices are the major security concerns of industry and academia. Limited memory, power, and processing capabilities of IoT devices further worsen the situations in improving the security of IoT devices. In such scenarios, a lightweight security algorithm up to some extent can minimize the risk. This paper proposes one such approach using Quick Response (QR) code to mitigate hard-coded credentials related attacks such as Mirai malware, wreak havoc, etc. The QR code based approach provides non-clear text unpredictable login id and password. Further, this paper also proposes a secured way of remotely accessing IoT devices through modified https. The proposed algorithms are implemented and verified using Raspberry Pi 3 model B.
2020-03-27
Salehi, Majid, Hughes, Danny, Crispo, Bruno.  2019.  MicroGuard: Securing Bare-Metal Microcontrollers against Code-Reuse Attacks. 2019 IEEE Conference on Dependable and Secure Computing (DSC). :1–8.
Bare-metal microcontrollers are a family of Internet of Things (IoT) devices which are increasingly deployed in critical industrial environments. Similar to other IoT devices, bare-metal microcontrollers are vulnerable to memory corruption and code-reuse attacks. We propose MicroGuard, a novel mitigation method based on component-level sandboxing and automated code randomization to securely encapsulate application components in isolated environments. We implemented MicroGuard and evaluated its efficacy and efficiency with a real-world benchmark against different types of attacks. As our evaluation shows, MicroGuard provides better security than ACES, current state-of-the-art protection framework for bare-metal microcontrollers, with a comparable performance overhead.
2020-03-23
Korenda, Ashwija Reddy, Afghah, Fatemeh, Cambou, Bertrand, Philabaum, Christopher.  2019.  A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices. 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :1–8.
This paper provides a proof of concept for using SRAM based Physically Unclonable Functions (PUFs) to generate private keys for IoT devices. PUFs are utilized, as there is inadequate protection for secret keys stored in the memory of the IoT devices. We utilize a custom-made Arduino mega shield to extract the fingerprint from SRAM chip on demand. We utilize the concepts of ternary states to exclude the cells which are easily prone to flip, allowing us to extract stable bits from the fingerprint of the SRAM. Using the custom-made software for our SRAM device, we can control the error rate of the PUF to achieve an adjustable memory-based PUF for key generation. We utilize several fuzzy extractor techniques based on using different error correction coding methods to generate secret keys from the SRAM PUF, and study the trade-off between the false authentication rate and false rejection rate of the PUF.
2020-03-16
Rosa, Taras, Kaidan, Mykola, Gazda, Juraj, Bykovyy, Pavlo, Sapozhnyk, Grygoriy, Maksymyuk, Taras.  2019.  Scalable QAM Modulation for Physical Layer Security of Wireless Networks. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). 2:1095–1098.
The rapid growth of the connected devices driven by Internet of Things (IoT) concept requires a complete rethinking of the conventional approaches for the network design. One of the key constraints of the IoT devices are their low capabilities in order to optimize energy consumption. On the other hand, many IoT applications require high level of data protection and privacy, which can be provided only by advanced cryptographic algorithms, which are not feasible for IoT devices. In this paper, we propose a scalable quadrature modulation aiming to solve the problem of secure communications at the physical layer. The key idea of the proposed approach is to transmit only part of information in way that allows target receiver to retrieve the complete information. Such approach allows to ensure the security of wireless channel, while reducing the overhead of advanced cryptographic algorithms.
2020-03-12
Vieira, Leandro, Santos, Leonel, Gon\c calves, Ramiro, Rabadão, Carlos.  2019.  Identifying Attack Signatures for the Internet of Things: An IP Flow Based Approach. 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). :1–7.

At the time of more and more devices being connected to the internet, personal and sensitive information is going around the network more than ever. Thus, security and privacy regarding IoT communications, devices, and data are a concern due to the diversity of the devices and protocols used. Since traditional security mechanisms cannot always be adequate due to the heterogeneity and resource limitations of IoT devices, we conclude that there are still several improvements to be made to the 2nd line of defense mechanisms like Intrusion Detection Systems. Using a collection of IP flows, we can monitor the network and identify properties of the data that goes in and out. Since network flows collection have a smaller footprint than packet capturing, it makes it a better choice towards the Internet of Things networks. This paper aims to study IP flow properties of certain network attacks, with the goal of identifying an attack signature only by observing those properties.

2020-02-24
Brotsis, Sotirios, Kolokotronis, Nicholas, Limniotis, Konstantinos, Shiaeles, Stavros, Kavallieros, Dimitris, Bellini, Emanuele, Pavué, Clément.  2019.  Blockchain Solutions for Forensic Evidence Preservation in IoT Environments. 2019 IEEE Conference on Network Softwarization (NetSoft). :110–114.
The technological evolution brought by the Internet of things (IoT) comes with new forms of cyber-attacks exploiting the complexity and heterogeneity of IoT networks, as well as, the existence of many vulnerabilities in IoT devices. The detection of compromised devices, as well as the collection and preservation of evidence regarding alleged malicious behavior in IoT networks, emerge as areas of high priority. This paper presents a blockchain-based solution, which is designed for the smart home domain, dealing with the collection and preservation of digital forensic evidence. The system utilizes a private forensic evidence database, where the captured evidence is stored, along with a permissioned blockchain that allows providing security services like integrity, authentication, and non-repudiation, so that the evidence can be used in a court of law. The blockchain stores evidences' metadata, which are critical for providing the aforementioned services, and interacts via smart contracts with the different entities involved in an investigation process, including Internet service providers, law enforcement agencies and prosecutors. A high-level architecture of the blockchain-based solution is presented that allows tackling the unique challenges posed by the need for digitally handling forensic evidence collected from IoT networks.
2020-02-18
Saha, Arunima, Srinivasan, Chungath.  2019.  White-Box Cryptography Based Data Encryption-Decryption Scheme for IoT Environment. 2019 5th International Conference on Advanced Computing Communication Systems (ICACCS). :637–641.

The economic progress of the Internet of Things (IoT) is phenomenal. Applications range from checking the alignment of some components during a manufacturing process, monitoring of transportation and pedestrian levels to enhance driving and walking path, remotely observing terminally ill patients by means of medical devices such as implanted devices and infusion pumps, and so on. To provide security, encrypting the data becomes an indispensable requirement, and symmetric encryptions algorithms are becoming a crucial implementation in the resource constrained environments. Typical symmetric encryption algorithms like Advanced Encryption Standard (AES) showcases an assumption that end points of communications are secured and that the encryption key being securely stored. However, devices might be physically unprotected, and attackers may have access to the memory while the data is still encrypted. It is essential to reserve the key in such a way that an attacker finds it hard to extract it. At present, techniques like White-Box cryptography has been utilized in these circumstances. But it has been reported that applying White-Box cryptography in IoT devices have resulted in other security issues like the adversary having access to the intermediate values, and the practical implementations leading to Code lifting attacks and differential attacks. In this paper, a solution is presented to overcome these problems by demonstrating the need of White-Box Cryptography to enhance the security by utilizing the cipher block chaining (CBC) mode.

2020-01-20
Noura, Hassan, Chehab, Ali, Couturier, Raphael.  2019.  Lightweight Dynamic Key-Dependent and Flexible Cipher Scheme for IoT Devices. 2019 IEEE Wireless Communications and Networking Conference (WCNC). :1–8.

Security attacks against Internet of Things (IoT) are on the rise and they lead to drastic consequences. Data confidentiality is typically based on a strong symmetric-key algorithm to guard against confidentiality attacks. However, there is a need to design an efficient lightweight cipher scheme for a number of applications for IoT systems. Recently, a set of lightweight cryptographic algorithms have been presented and they are based on the dynamic key approach, requiring a small number of rounds to minimize the computation and resource overhead, without degrading the security level. This paper follows this logic and provides a new flexible lightweight cipher, with or without chaining operation mode, with a simple round function and a dynamic key for each input message. Consequently, the proposed cipher scheme can be utilized for real-time applications and/or devices with limited resources such as Multimedia Internet of Things (MIoT) systems. The importance of the proposed solution is that it produces dynamic cryptographic primitives and it performs the mixing of selected blocks in a dynamic pseudo-random manner. Accordingly, different plaintext messages are encrypted differently, and the avalanche effect is also preserved. Finally, security and performance analysis are presented to validate the efficiency and robustness of the proposed cipher variants.

Giaretta, Alberto, Dragoni, Nicola, Massacci, Fabio.  2019.  Protecting the Internet of Things with Security-by-Contract and Fog Computing. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). :1–6.

Nowadays, the Internet of Things (IoT) is a consolidated reality. Smart homes are equipped with a growing number of IoT devices that capture more and more information about human beings lives. However, manufacturers paid little or no attention to security, so that various challenges are still in place. In this paper, we propose a novel approach to secure IoT systems that combines the concept of Security-by-Contract (S×C) with the Fog computing distributed paradigm. We define the pillars of our approach, namely the notions of IoT device contract, Fog node policy and contract-policy matching, the respective life-cycles, and the resulting S×C workflow. To better understand all the concepts of the S×C framework, and highlight its practical feasibility, we use a running case study based on a context-aware system deployed in a real smart home.

Tedeschi, Pietro, Sciancalepore, Savio.  2019.  Edge and Fog Computing in Critical Infrastructures: Analysis, Security Threats, and Research Challenges. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :1–10.

The increasing integration of information and communication technologies has undoubtedly boosted the efficiency of Critical Infrastructures (CI). However, the first wave of IoT devices, together with the management of enormous amount of data generated by modern CIs, has created serious architectural issues. While the emerging Fog and Multi-Access Edge Computing (FMEC) paradigms can provide a viable solution, they also bring inherent security issues, that can cause dire consequences in the context of CIs. In this paper, we analyze the applications of FMEC solutions in the context of CIs, with a specific focus on related security issues and threats for the specific while broad scenarios: a smart airport, a smart port, and a smart offshore oil and gas extraction field. Leveraging these scenarios, a set of general security requirements for FMEC is derived, together with crucial research challenges whose further investigation is cornerstone for a successful adoption of FMEC in CIs.

Alhazmi, Omar H., Aloufi, Khalid S..  2019.  Fog-Based Internet of Things: A Security Scheme. 2019 2nd International Conference on Computer Applications Information Security (ICCAIS). :1–6.

Internet of Things (IoT) stack models differ in their architecture, applications and needs. Hence, there are different approaches to apply IoT; for instance, it can be based on traditional data center or based on cloud computing. In fact, Cloud-based IoT is gaining more popularity due to its high scalability and cost effectiveness; hence, it is becoming the norm. However, Cloud is usually located far from the IoT devices and some recent research suggests using Fog-Based IoT by using a nearby light-weight middleware to bridge the gap and to provide the essential support and communication between devices, sensors, receptors and the servers. Therefore, Fog reduces centrality and provides local processing for faster analysis, especially for the time-sensitive applications. Thus, processing is done faster, giving the system flexibility for faster response time. Fog-Based Internet of Things security architecture should be suitable to the environment and provide the necessary measures to improve all security aspects with respect to the available resources and within performance constraints. In this work, we discuss some of these challenges, analyze performance of Fog based IoT and propose a security scheme based on MQTT protocol. Moreover, we present a discussion on security-performance tradeoffs.