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Ameur, S. B., Smaoui, S., Zarai, F..  2017.  Visiting Mobile Node Authentication Protocol for Proxy MIPv6-Based NEtwork MObility. 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA). :1314–1321.

NEtwork MObility (NEMO) has gained recently a lot of attention from a number of standardization and researches committees. Although NEMO-Basic Support Protocol (NEMO-BSP) seems to be suitable in the context of the Intelligent Transport Systems (ITS), it has several shortcomings, such as packets loss and lack of security, since it is a host-based mobility scheme. Therefore, in order to improve handoff performance and solve these limitations, schemes adapting Proxy MIPv6 for NEMO have been appeared. But the majorities did not deal with the case of the handover of the Visiting Mobile Nodes (VMN) located below the Mobile Router (MR). Thus, this paper proposes a Visiting Mobile Node Authentication Protocol for Proxy MIPv6-Based NEtwork MObility which ensures strong authentication between entities. To evaluate the security performance of our proposition, we have used the AVISPA/SPAN software which guarantees that our proposed protocol is a safe scheme.

Almohanna, S., Alogayyel, M. S., Ajaji, A. A., Alkhdrawi, H. A., Alleli, M. A., Tareq, Q., Mukhtar, Sani, Mohammed Khan, Z. M..  2019.  Visible-NIR Laser Based Bi-directional Indoor Optical Wireless Communication. 2019 IEEE 10th GCC Conference Exhibition (GCC). :1–4.
We propose and demonstrate an indoor optical bi-directional communication system employing near-infrared (NIR) and visible light as carriers. Such a communication technology is attractive wherein red color could be deployed for down streaming purpose via, for instance, LiFi (light fidelity) system, and NIR color for up streaming purpose. This system concept is implemented over a simultaneous bidirectional audio signal transmission and reception over 0.6m indoor wireless channel. Besides, designing the transceiver circuits from off the shelf components, frequency scrambling encryption and decryption technique is also integrated in the system for security purpose. The communication system is optically characterized in terms of line-of-sight laser misalignment and communication distance.
Alves, Thiago, Das, Rishabh, Morris, Thomas.  2016.  Virtualization of Industrial Control System Testbeds for Cybersecurity. Proceedings of the 2Nd Annual Industrial Control System Security Workshop. :10–14.

With an immense number of threats pouring in from nation states and hacktivists as well as terrorists and cybercriminals, the requirement of a globally secure infrastructure becomes a major obligation. Most critical infrastructures were primarily designed to work isolated from the normal communication network, but due to the advent of the "Smart Grid" that uses advanced and intelligent approaches to control critical infrastructure, it is necessary for these cyber-physical systems to have access to the communication system. Consequently, such critical systems have become prime targets; hence security of critical infrastructure is currently one of the most challenging research problems. Performing an extensive security analysis involving experiments with cyber-attacks on a live industrial control system (ICS) is not possible. Therefore, researchers generally resort to test beds and complex simulations to answer questions related to SCADA systems. Since all conclusions are drawn from the test bed, it is necessary to perform validation against a physical model. This paper examines the fidelity of a virtual SCADA testbed to a physical test bed and allows for the study of the effects of cyber- attacks on both of the systems.

Liu, D. Y. W., Leung, A. C. Y., Au, M. H., Luo, X., Chiu, P. H. P., Im, S. W. T., Lam, W. W. M..  2019.  Virtual Laboratory: Facilitating Teaching and Learning in Cybersecurity for Students with Diverse Disciplines. 2019 IEEE International Conference on Engineering, Technology and Education (TALE). :1—6.

Cybersecurity education is a pressing need, when computer systems and mobile devices are ubiquitous and so are the associated threats. However, in the teaching and learning process of cybersecurity, it is challenging when the students are from diverse disciplines with various academic backgrounds. In this project, a number of virtual laboratories are developed to facilitate the teaching and learning process in a cybersecurity course. The aim of the laboratories is to strengthen students’ understanding of cybersecurity topics, and to provide students hands-on experience of encountering various security threats. The results of this project indicate that virtual laboratories do facilitate the teaching and learning process in cybersecurity for diverse discipline students. Also, we observed that there is an underestimation of the difficulty of studying cybersecurity by the students due to the general image of cybersecurity in public, which had a negative impact on the student’s interest in studying cybersecurity.

Bose, A. J., Aarabi, P..  2019.  Virtual Fakes: DeepFakes for Virtual Reality. 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP). :1—1.
The proliferation of data and computational resources has led into many advancements in computer vision for facial data including easily replacing a face in one video with another one, the so called DeepFake. In this paper, we apply techniques to generate DeepFakes for virtual reality applications. We empirically validate our method by generating, for the first time, Deep Fake videos in virtual reality.
Mirzamohammadi, Saeed, Amiri Sani, Ardalan.  2016.  Viola: Trustworthy Sensor Notifications for Enhanced Privacy on Mobile Systems. Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services. :263–276.

Modern mobile systems such as smartphones, tablets, and wearables contain a plethora of sensors such as camera, microphone, GPS, and accelerometer. Moreover, being mobile, these systems are with the user all the time, e.g., in user's purse or pocket. Therefore, mobile sensors can capture extremely sensitive and private information about the user including daily conversations, photos, videos, and visited locations. Such a powerful sensing capability raises important privacy concerns. To address these concerns, we believe that mobile systems must be equipped with trustworthy sensor notifications, which use indicators such as LED to inform the user unconditionally when the sensors are on. We present Viola, our design and implementation of trustworthy sensor notifications, in which we leverage two novel solutions. First, we deploy a runtime monitor in low-level system software, e.g., in the operating system kernel or in the hypervisor. The monitor intercepts writes to the registers of sensors and indicators, evaluates them against checks on sensor notification invariants, and rejects those that fail the checks. Second, we use formal verification methods to prove the functional correctness of the compilation of our invariant checks from a high-level language. We demonstrate the effectiveness of Viola on different mobile systems, such as Nexus 5, Galaxy Nexus, and ODROID XU4, and for various sensors and indicators, such as camera, microphone, LED, and vibrator. We demonstrate that Viola incurs almost no overhead to the sensor's performance and incurs only small power consumption overhead.

AL-ATHAMNEH, M., KURUGOLLU, F., CROOKES, D., FARID, M..  2016.  Video Authentication Based on Statistical Local Information. Proceedings of the 9th International Conference on Utility and Cloud Computing. :388–391.

With the outgrowth of video editing tools, video information trustworthiness becomes a hypersensitive field. Today many devices have the capability of capturing digital videos such as CCTV, digital cameras and mobile phones and these videos may transmitted over the Internet or any other non secure channel. As digital video can be used to as supporting evidence, it has to be protected against manipulation or tampering. As most video authentication techniques are based on watermarking and digital signatures, these techniques are effectively used in copyright purposes but difficult to implement in other cases such as video surveillance or in videos captured by consumer's cameras. In this paper we propose an intelligent technique for video authentication which uses the video local information which makes it useful for real world applications. The proposed algorithm relies on the video's statistical local information which was applied on a dataset of videos captured by a range of consumer video cameras. The results show that the proposed algorithm has potential to be a reliable intelligent technique in digital video authentication without the need to use for SVM classifier which makes it faster and less computationally expensive in comparing with other intelligent techniques.

Frumento, Enrico, Freschi, Federica, Andreoletti, Davide, Consoli, Angelo.  2017.  Victim Communication Stack (VCS): A Flexible Model to Select the Human Attack Vector. Proceedings of the 12th International Conference on Availability, Reliability and Security. :50:1–50:6.
Information security has rapidly grown to meet the requirements of today services. A solid discipline has been developed as far as technical security is concerned. However, the human layer plays an increasingly decisive role in the managing of Information Technology (IT) systems. The research field that studies the vulnerabilities of the human layer is referred to as Social Engineering, and has not received the same attention of its technical counterpart. We try to partially fill this gap by studying the selection of the Human Attack Vector (HAV), i.e., the path or the means that the attacker uses to compromise the human layer. To this aim, we propose a multilayer model, named Victim Communication Stack (VCS), that provides the key elements to facilitate the choice of the HAV. This work has been carried out under the DOGANA European project.
Hang Shao, Japkowicz, N., Abielmona, R., Falcon, R..  2014.  Vessel track correlation and association using fuzzy logic and Echo State Networks. Evolutionary Computation (CEC), 2014 IEEE Congress on. :2322-2329.

Tracking moving objects is a task of the utmost importance to the defence community. As this task requires high accuracy, rather than employing a single detector, it has become common to use multiple ones. In such cases, the tracks produced by these detectors need to be correlated (if they belong to the same sensing modality) or associated (if they were produced by different sensing modalities). In this work, we introduce Computational-Intelligence-based methods for correlating and associating various contacts and tracks pertaining to maritime vessels in an area of interest. Fuzzy k-Nearest Neighbours will be used to conduct track correlation and Fuzzy C-Means clustering will be applied for association. In that way, the uncertainty of the track correlation and association is handled through fuzzy logic. To better model the state of the moving target, the traditional Kalman Filter will be extended using an Echo State Network. Experimental results on five different types of sensing systems will be discussed to justify the choices made in the development of our approach. In particular, we will demonstrate the judiciousness of using Fuzzy k-Nearest Neighbours and Fuzzy C-Means on our tracking system and show how the extension of the traditional Kalman Filter by a recurrent neural network is superior to its extension by other methods.

Guo, W., Atthanayake, I., Thomas, P..  2020.  Vertical Underwater Molecular Communications via Buoyancy: Gaussian Velocity Distribution of Signal. ICC 2020 - 2020 IEEE International Conference on Communications (ICC). :1–6.
Underwater communication is vital for a variety of defence and scientific purposes. Current optical and sonar based carriers can deliver high capacity data rates, but their range and reliability is hampered by heavy propagation loss. A vertical Molecular Communication via Buoyancy (MCvB) channel is experimentally investigated here, where the dominant propagation force is buoyancy. Sequential puffs representing modulated symbols are injected and after the initial loss of momentum, the signal is driven by buoyancy forces which apply to both upwards and downwards channels. Coupled with the complex interaction of turbulent and viscous diffusion, we experimentally demonstrate that sequential symbols exhibit a Gaussian velocity spatial distribution. Our experimental results use Particle Image Velocimetry (PIV) to trace molecular clusters and infer statistical characteristics of their velocity profile. We believe our experimental paper's results can be the basis for long range underwater vertical communication between a deep sea vehicle and a surface buoy, establishing a covert and reliable delay-tolerant data link. The statistical distribution found in this paper is akin to the antenna pattern and the knowledge can be used to improve physical security.
Ahmed Khurshid, University of Illinois at Urbana-Champaign, Wenxuan Zhou, University of Illinois at Urbana-Champaign, Matthew Caesar, University of Illinois at Urbana-Champaign, P. Brighten Godfrey, University of Illinois at Urbana-Champaign.  2012.  VeriFlow: Verifying Network-Wide Invariants in Real Time. First Workshop on Hot Topics in Software Defined Networks (HotSDN 2012).

Networks are complex and prone to bugs. Existing tools that check configuration files and data-plane state operate offline at timescales of seconds to hours, and cannot detect or prevent bugs as they arise. Is it possible to check network-wide invariants in real time, as the network state evolves? The key challenge here is to achieve extremely low latency during the checks so that network performance is not affected. In this paper, we present a preliminary design, VeriFlow, which suggests that this goal is achievable. VeriFlow is a layer between a software-defined networking controller and network devices that checks for network-wide invariant violations dynamically as each forwarding rule is inserted. Based on an implementation using a Mininet OpenFlow network and Route Views trace data, we find that VeriFlow can perform rigorous checking within hundreds of microseconds per rule insertion.

Ye, Katherine Q., Green, Matthew, Sanguansin, Naphat, Beringer, Lennart, Petcher, Adam, Appel, Andrew W..  2017.  Verified Correctness and Security of mbedTLS HMAC-DRBG. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2007–2020.
We have formalized the functional specification of HMAC-DRBG (NIST 800-90A), and we have proved its cryptographic security-that its output is pseudorandom–using a hybrid game-based proof. We have also proved that the mbedTLS implementation (C program) correctly implements this functional specification. That proof composes with an existing C compiler correctness proof to guarantee, end-to-end, that the machine language program gives strong pseudorandomness. All proofs (hybrid games, C program verification, compiler, and their composition) are machine-checked in the Coq proof assistant. Our proofs are modular: the hybrid game proof holds on any implementation of HMAC-DRBG that satisfies our functional specification. Therefore, our functional specification can serve as a high-assurance reference.
Mikami, Kei, Ando, Daisuke, Kaneko, Kunitake, Teraoka, Fumio.  2016.  Verification of a Multi-Domain Authentication and Authorization Infrastructure Yamata-no-Orochi. Proceedings of the 11th International Conference on Future Internet Technologies. :69–75.

Yamata-no-Orochi is an authentication and authorization infrastructure across multiple service domains and provides Internet services with unified authentication and authorization mechanisms. In this paper, Yamata-no-Orochi is incorporated into a video distribution system to verify its general versatility as a multi-domain authentication and authorization infrastructure for Internet services. This paper also reduces the authorization time of Yamata-no-Orochi to fulfill the processing time constrains of the video distribution system. The evaluation results show that all the authentication and authorization processes work correctly and the performance of Yamata-no-Orochi is practical for the video distribution system.

Lacroix, Jesse, El-Khatib, Khalil, Akalu, Rajen.  2016.  Vehicular Digital Forensics: What Does My Vehicle Know About Me? Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications. :59–66.

A major component of modern vehicles is the infotainment system, which interfaces with its drivers and passengers. Other mobile devices, such as handheld phones and laptops, can relay information to the embedded infotainment system through Bluetooth and vehicle WiFi. The ability to extract information from these systems would help forensic analysts determine the general contents that is stored in an infotainment system. Based off the data that is extracted, this would help determine what stored information is relevant to law enforcement agencies and what information is non-essential when it comes to solving criminal activities relating to the vehicle itself. This would overall solidify the Intelligent Transport System and Vehicular Ad Hoc Network infrastructure in combating crime through the use of vehicle forensics. Additionally, determining the content of these systems will allow forensic analysts to know if they can determine anything about the end-user directly and/or indirectly.

Lira, Wallace, Gama, Fernando, Barbosa, Hivana, Alves, Ronnie, de Souza, Cleidson.  2016.  VCloud: Adding Interactiveness to Word Clouds for Knowledge Exploration in Large Unstructured Texts. Proceedings of the 31st Annual ACM Symposium on Applied Computing. :193–198.

The identification of relevant information in large text databases is a challenging task. One of the reasons is human beings' limitations in handling large volumes of data. A common solution for scavenging data from texts are word clouds. A word cloud illustrates word usage in a document by resizing individual words in documents proportionally to how frequently they appear. Even though word clouds are easy to understand, they are not particularly efficient, because they are static. In addition, the presented information lacks context, i.e., words are not explained and they may lead to radically erroneous interpretations. To tackle these problems we developed VCloud, a tool that allows the user to interact with word clouds, therefore allowing informative and interactive data exploration. Furthermore, our tool also allows one to compare two data sets presented as word clouds. We evaluated VCloud using real data about the evolution of gastritis research through the years. The papers indexed by Pubmed related to this medical context were selected for visualization and data analysis using VCloud. A domain expert explored these visualizations, being able to extract useful information from it. This illustrates how can VCloud be a valuable tool for visual text analytics.

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Aydeger, Abdullah, Saputro, Nico, Akkaya, Kemal.  2018.  Utilizing NFV for Effective Moving Target Defense Against Link Flooding Reconnaissance Attacks. MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM). :946—951.

Moving target defense (MTD) is becoming popular with the advancements in Software Defined Networking (SDN) technologies. With centralized management through SDN, changing the network attributes such as routes to escape from attacks is simple and fast. Yet, the available alternate routes are bounded by the network topology, and a persistent attacker that continuously perform the reconnaissance can extract the whole link-map of the network. To address this issue, we propose to use virtual shadow networks (VSNs) by applying Network Function Virtualization (NFV) abilities to the network in order to deceive attacker with the fake topology information and not reveal the actual network topology and characteristics. We design this approach under a formal framework for Internet Service Provider (ISP) networks and apply it to the recently emerged indirect DDoS attacks, namely Crossfire, for evaluation. The results show that attacker spends more time to figure out the network behavior while the costs on the defender and network operations are negligible until reaching a certain network size.

Al-Janabi, Mohammed, Quincey, Ed de, Andras, Peter.  2017.  Using Supervised Machine Learning Algorithms to Detect Suspicious URLs in Online Social Networks. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017. :1104–1111.

The increasing volume of malicious content in social networks requires automated methods to detect and eliminate such content. This paper describes a supervised machine learning classification model that has been built to detect the distribution of malicious content in online social networks (ONSs). Multisource features have been used to detect social network posts that contain malicious Uniform Resource Locators (URLs). These URLs could direct users to websites that contain malicious content, drive-by download attacks, phishing, spam, and scams. For the data collection stage, the Twitter streaming application programming interface (API) was used and VirusTotal was used for labelling the dataset. A random forest classification model was used with a combination of features derived from a range of sources. The random forest model without any tuning and feature selection produced a recall value of 0.89. After further investigation and applying parameter tuning and feature selection methods, however, we were able to improve the classifier performance to 0.92 in recall.

Chong, T., Anu, V., Sultana, K. Z..  2019.  Using Software Metrics for Predicting Vulnerable Code-Components: A Study on Java and Python Open Source Projects. 2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC). :98–103.

Software vulnerabilities often remain hidden until an attacker exploits the weak/insecure code. Therefore, testing the software from a vulnerability discovery perspective becomes challenging for developers if they do not inspect their code thoroughly (which is time-consuming). We propose that vulnerability prediction using certain software metrics can support the testing process by identifying vulnerable code-components (e.g., functions, classes, etc.). Once a code-component is predicted as vulnerable, the developers can focus their testing efforts on it, thereby avoiding the time/effort required for testing the entire application. The current paper presents a study that compares how software metrics perform as vulnerability predictors for software projects developed in two different languages (Java vs Python). The goal of this research is to analyze the vulnerability prediction performance of software metrics for different programming languages. We designed and conducted experiments on security vulnerabilities reported for three Java projects (Apache Tomcat 6, Tomcat 7, Apache CXF) and two Python projects (Django and Keystone). In this paper, we focus on a specific type of code component: Functions. We apply Machine Learning models for predicting vulnerable functions. Overall results show that software metrics-based vulnerability prediction is more useful for Java projects than Python projects (i.e., software metrics when used as features were able to predict Java vulnerable functions with a higher recall and precision compared to Python vulnerable functions prediction).

Schmid, Stefan, Arquint, Linard, Gross, Thomas R..  2016.  Using Smartphones As Continuous Receivers in a Visible Light Communication System. Proceedings of the 3rd Workshop on Visible Light Communication Systems. :61–66.
Visible Light Communication (VLC) allows to reuse a lighting infrastructure for communication while its main purpose of illumination can be carried out at the same time. Light sources based on Light Emitting Diodes (LEDs) are attractive as they are inexpensive, ubiquitous, and allow rapid modulation. This paper describes how to integrate smartphones into such a communication system that supports networking for a wide range of devices, such as toys with single LEDs as transmitter and receivers as well as interconnected LED light bulbs. The main challenge is how to employ the smartphone without any (hardware) modification as a receiver, using the integrated camera as a (slow) light sampling device. This paper presents a simple software-based solution, exploiting the rolling shutter effect and slow motion video capturing capabilities of latest smartphones to enable continuous reception and real-time integration into an existing VLC system. Evaluation results demonstrate a working prototype and report communication distances up to 3m and a maximum data throughput of more than 1200b/s, improving upon previous work.
Azriel, Leonid, Ginosar, Ran, Gueron, Shay, Mendelson, Avi.  2016.  Using Scan Side Channel for Detecting IP Theft. Proceedings of the Hardware and Architectural Support for Security and Privacy 2016. :1:1–1:8.

We present a process for detection of IP theft in VLSI devices that exploits the internal test scan chains. The IP owner learns implementation details in the suspect device to find evidence of the theft, while the top level function is public. The scan chains supply direct access to the internal registers in the device, thus making it possible to learn the logic functions of the internal combinational logic chunks. Our work introduces an innovative way of applying Boolean function analysis techniques for learning digital circuits with the goal of IP theft detection. By using Boolean function learning methods, the learner creates a partial dependency graph of the internal flip-flops. The graph is further partitioned using the SNN graph clustering method, and individual blocks of combinational logic are isolated. These blocks can be matched with known building blocks that compose the original function. This enables reconstruction of the function implementation to the level of pipeline structure. The IP owner can compare the resulting structure with his own implementation to confirm or refute that an IP violation has occurred. We demonstrate the power of the presented approach with a test case of an open source Bitcoin SHA-256 accelerator, containing more than 80,000 registers. With the presented method we discover the microarchitecture of the module, locate all the main components of the SHA-256 algorithm, and learn the module's flow control.

Saoji, Tejas, Austin, Thomas H., Flanagan, Cormac.  2017.  Using Precise Taint Tracking for Auto-sanitization. Proceedings of the 2017 Workshop on Programming Languages and Analysis for Security. :15–24.

Taint analysis has been used in numerous scripting languages such as Perl and Ruby to defend against various form of code injection attacks, such as cross-site scripting (XSS) and SQL-injection. However, most taint analysis systems simply fail when tainted information is used in a possibly unsafe manner. In this paper, we explore how precise taint tracking can be used in order to secure web content. Rather than simply crashing, we propose that a library-writer defined sanitization function can instead be used on the tainted portions of a string. With this approach, library writers or framework developers can design their tools to be resilient, even if inexperienced developers misuse these libraries in unsafe ways. In other words, developer mistakes do not have to result in system crashes to guarantee security. We implement both coarse-grained and precise taint tracking in JavaScript, and show how our precise taint tracking API can be used to defend against SQL injection and XSS attacks. We further evaluate the performance of this approach, showing that precise taint tracking involves an overhead of approximately 22%.

Demir, Mehmet özgÜn, Alp Topal, Ozan, Dartmann, Guido, Schmeink, Anke, Ascheid, Gerd, Kurt, GüneŞ, Pusane, Ali Emre.  2019.  Using Perfect Codes in Relay Aided Networks: A Security Analysis. 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). :1—6.

Cyber-physical systems (CPS) are state-of-the-art communication environments that offer various applications with distinct requirements. However, security in CPS is a nonnegotiable concept, since without a proper security mechanism the applications of CPS may risk human lives, the privacy of individuals, and system operations. In this paper, we focus on PHY-layer security approaches in CPS to prevent passive eavesdropping attacks, and we propose an integration of physical layer operations to enhance security. Thanks to the McEliece cryptosystem, error injection is firstly applied to information bits, which are encoded with the forward error correction (FEC) schemes. Golay and Hamming codes are selected as FEC schemes to satisfy power and computational efficiency. Then obtained codewords are transmitted across reliable intermediate relays to the legitimate receiver. As a performance metric, the decoding frame error rate of the eavesdropper is analytically obtained for the fragmentary existence of significant noise between relays and Eve. The simulation results validate the analytical calculations, and the obtained results show that the number of low-quality channels and the selected FEC scheme affects the performance of the proposed model.

Alrabaee, S., Bataineh, A., Khasawneh, F.A., Dssouli, R..  2014.  Using model checking for Trivial File Transfer Protocol validation. Communications and Networking (ComNet), 2014 International Conference on. :1-7.

This paper presents verification and model based checking of the Trivial File Transfer Protocol (TFTP). Model checking is a technique for software verification that can detect concurrency defects within appropriate constraints by performing an exhaustive state space search on a software design or implementation and alert the implementing organization to potential design deficiencies that are otherwise difficult to be discovered. The TFTP is implemented on top of the Internet User Datagram Protocol (UDP) or any other datagram protocol. We aim to create a design model of TFTP protocol, with adding window size, using Promela to simulate it and validate some specified properties using spin. The verification has been done by using the model based checking tool SPIN which accepts design specification written in the verification language PROMELA. The results show that TFTP is free of live locks.
 

Al-issa, Abdulaziz I., Al-Akhras, Mousa, ALsahli, Mohammed S., Alawairdhi, Mohammed.  2019.  Using Machine Learning to Detect DoS Attacks in Wireless Sensor Networks. 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT). :107–112.

Widespread use of Wireless Sensor Networks (WSNs) introduced many security threats due to the nature of such networks, particularly limited hardware resources and infrastructure less nature. Denial of Service attack is one of the most common types of attacks that face such type of networks. Building an Intrusion Detection and Prevention System to mitigate the effect of Denial of Service attack is not an easy task. This paper proposes the use of two machine learning techniques, namely decision trees and Support Vector Machines, to detect attack signature on a specialized dataset. The used dataset contains regular profiles and several Denial of Service attack scenarios in WSNs. The experimental results show that decision trees technique achieved better (higher) true positive rate and better (lower) false positive rate than Support Vector Machines, 99.86% vs 99.62%, and 0.05% vs. 0.09%, respectively.

Chakraborti, Asit, Amin, Syed Obaid, Azgin, Aytac, Misra, Satyajayant, Ravindran, Ravishankar.  2018.  Using ICN Slicing Framework to Build an IoT Edge Network. Proceedings of the 5th ACM Conference on Information-Centric Networking. :214–215.
We demonstrate 5G network slicing as a unique deployment opportunity for information centric networking (ICN), by using a generic service orchestration framework that operates on commodity compute, storage, and bandwidth resource pools to realize ICN service slices. In this demo, we specifically propose a service slice for the IoT Edge network. ICN has often been considered pertinent for IoT use due to its benefits like simpler stacks on resource constrained devices, in-network caching, and in-built data provenance. We use a lightweight ICN stack on IoT devices connected with sensors and actuators to build a network, where clients can set realistic policies using their legacy hand-held devices. We employ name based authentication protocols between the service end-points and IoT devices to allow secure onboarding. The IoT slice co-exists with other service slices that cater to different classes of applications (e.g., bandwidth intensive applications, such as video conferencing) allowing resource management flexibility. Our design creates orchestrated service Edge functions to which the clients connect, and these can in turn utilize in-network stateless functions to perform tasks, such as decision making and analytics using the available compute resources efficiently.