Nowadays, routing and the improvement of reliability along with the load balancing and congestion... more Nowadays, routing and the improvement of reliability along with the load balancing and congestion control are the most important and challenging concepts in ad-hoc networks. However, there are some constraints in the bandwidth and the communication range due to the different utility of routing in the Mobile Ad Hoc Network (MANET). These restrictions, in addition to the dynamic network topology, are causing more complexity of routing and data transmission. These problems make the use of conventional methods inefficient, especially in the congestion and traffic control. So, there is a need to propose new solutions for these kinds of networks. This study has used the multipath routing based on the original protocol Ad-Hoc On-Demand Multipath Distance Vector (AOMDV). It proposes an appropriate protocol for the congestion control and balances the favorable loads in the routes. The proposed algorithm is based on different parameters that prepare the fittest multipaths based on the most ef...
In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from ... more In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from both the agriculture industry as well as the research community. Altogether, SF and PA aim to help farmers use inputs (such as fertilizers and pesticides) more efficiently through using Internet of Things (IoT) devices, but in doing so, they create new security threats that can defeat this purpose in the absence of adequate awareness and proper countermeasures. A survey on different security-related challenges is required to raise awareness and pave they way for further research in this area. In this paper, we first itemize the security aspects of SF and PA. Next, we review the types of cyber attacks that can violate each of these aspects. Accordingly, we present a taxonomy on cyber-threats to SF and PA on the basis of their relations to different stages of Cyber-Kill Chain (CKC). Among cyber-threats, we choose Advanced Persistent Threats (APTs) for further study. Finally, we studied rel...
Success in machine learning has led to a wealth of Artificial Intelligence (AI) systems. A great ... more Success in machine learning has led to a wealth of Artificial Intelligence (AI) systems. A great deal of attention is currently being set on the development of advanced Machine Learning (ML)-based solutions for a variety of automated predictions and classification tasks in a wide array of industries. However, such automated applications may introduce bias in results, making it risky to use these ML models in security-and privacy-sensitive domains. The prediction should be accurate and models have to be interpretable/explainable to understand how they work. In this research, we conduct an empirical evaluation of two major explainer/interpretable methods called LIME and SHAP on two datasets using deep learning models, including Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). The results demonstrated that SHAP performs slightly better than LIME in terms of Identity, Stability, and Separability from two different datasets (Breast Cancer Wisconsin (Diagnostic) and NIH Chest X-Ray) that we used.
Deepfakes generally refers to a new breed of adversarial deep learning technology to create non-c... more Deepfakes generally refers to a new breed of adversarial deep learning technology to create non-consensual contents (mostly videos) for nefarious purposes. Most researches focus on the ‘detection’ of deepfakes using AI-assisted approaches to take on this problem. This has been the common method operandi used by researchers thus far. However, there is one missing aspect of the deepfake problem, which is ‘authentication’. Instead of attempting to detect what content is fake, in this paper, we focus on techniques to provide tamper-proof evidence of what content is real. Blockchain has been advocated to be helpful with the authentication aspect of many real-world scenarios. Despite the scattered efforts around such solutions, there are no studies that can shed light on where it makes sense to adopt blockchain technology to better take on the deepfake problem. This paper aims to provide a one-stop guide to using blockchain to navigate deepfake artificial intelligence. We discuss potentia...
A vision-based intelligent traffic control system is a robust framework that controls the traffic... more A vision-based intelligent traffic control system is a robust framework that controls the traffic flow in real-time by estimating the traffic density near traffic lights. In this paper, a traffic light control system based on fuzzy Qlearning is proposed according to the vehicle density and the pedestrian number estimated from the visual information. The aim of proposed approach is to minimize the pedestrian and the car waiting time and maximize throughput for an isolated 4-way traffic intersection. Also, the pedestrian traffic light is controlled based on the fuzzy logic. The states and actions of the Q-learning variables are set by a fuzzy algorithm which can be learned through environmental interactions. The system can detect the number of pedestrians and vehicles using visual information from cameras and machine vision algorithms. The fuzzy control system can adjust the sequence of green phases to decrease the total waiting time and the mean of the queue length. The proposed algo...
Traditional Internet of Things (IoT) system architectures are centralized. Data from the devices ... more Traditional Internet of Things (IoT) system architectures are centralized. Data from the devices are stored on the back-end, where they are processed and analyzed, and then reconnected to IoT devices. The scalability of centralized systems is very limited especially when an abundance of devices exist on an IoT network. Network security in IoT networks is another aspect at stake that could be compromised easily due to the unavailability of security in design mechanisms in most IoT networks. Blockchain technology is a distributed ledger without any intensive management that can store all transactions which leads to large amounts of data that increases over time. Large data amounts will be more pronounced with the increasing IoT devices and blockchain use cases involving IoT. IoT devices are for the most part constrained in both energy, storage, and computation, unlikely to be able to store all blockchain data. The current implementation of blockchain is not IoT friendly. Moreover, consensus on the blockchain using Proof of Work (PoW) is infeasible due to computational constraints. In this paper, we propose a Secure and Low latency Proof of Work (SLPoW) protocol. We also bring the computation of miners onto a Field-programmable gate array (FPGA) to improve the processing speeds of computation. We consider our resulting blockchain technology using SLPoW suitable for the evolving Green IoT setting.
Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchai... more Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchain systems such as Ethereum, Hyperledger Fabric, and Corda, have emerged with public and private accessibility. It has been widely acknowledged that no single blockchain network will fit all use cases. As a result, we have observed the increasing popularity of multi-blockchain ecosystem in which customers will move toward different blockchains based on their particular requirements. Hence, the efficiency and security requirements of interactions among these heterogeneous blockchains become critical. In realization of this multi-blockchain paradigm, initiatives in building Interoperability-Facilitating Platforms (IFPs) that aim at bridging different blockchains (a.k.a. blockchain interoperability) have come to the fore. Despite current efforts, it is extremely difficult for blockchain customers (organizations, governments, companies) to understand the trade-offs between different IFPs and ...
In recent years, there has been rapid growth in developing smart cities. Nearly 70% of the Earthâ... more In recent years, there has been rapid growth in developing smart cities. Nearly 70% of the Earth’s surface is covered by water and a large proportion of underwater environments are still unknown and have not been explored. In this context, Internet of things (IoT) is one of the most important technologies used in smart cities. Due to the growth of IoT and its influence in all areas of human life, including the underwater environment, a new class of IoT, called Internet of underwater things (IoUT) has emerged. IoUT includes a network of underwater smart devices that are connected to each other and has applications in environmental monitoring, underwater exploration, disaster prevention and military. In autonomous interactions of underwater devices, objects must be authenticated and securely interconnected to avoid security risks by malicious nodes. Most authentication methods and security mechanisms are centralized and often require a trustful third party in communications, which may well increase the computation cost and energy consumption due to the subsequent overhead, especially for underwater communications. On the other hand, there are restrictions on devices in the underwater environment, the most important of which are energy constraints. In this paper, we propose a robust, transparent, and energy-efficient decentralized authentication mechanism for IoUT using blockchain technology. We show through results that the proposed method is suitable for underwater devices with limited memory, energy, and computational power. The proposed model’s decentralized authentication in a cluster network has a significant effect on reducing the energy consumption of the devices by 74.63% compared to classic authentication methods. Moreover, using the proposed method allows a savings of more than 41.9% in end-to-end delay and increases delivery rate by 21.6%.
Abstract In recent years, cryptocurrency trades have increased dramatically, and this trend has a... more Abstract In recent years, cryptocurrency trades have increased dramatically, and this trend has attracted cyber-threat actors to exploit the existing vulnerabilities and infect their targets. The malicious actors use cryptocurrency malware to perform complex computational tasks using infected devices. Since cryptocurrency malware threats perform a legal process, it is a challenging task to detect this type of threat by a manual or heuristic method. In this paper, we propose a novel deep Recurrent Neural Network ( RNN ) learning model for hunting cryptocurrency malware threats. Specifically, our proposed model utilizes the RNN to analyze Windows applications’ operation codes (Opcodes) as a case study. We collect a real-world dataset that comprises of 500 cryptocurrency malware and 200 benign-ware samples, respectively. The proposed model trains with five different Long Short-Term Memory ( LSTM ) structures and is evaluated by a 10-fold cross-validation ( CV ) technique. The obtained results prove that a 3-layer configuration model gains 98% of detection accuracy, which is the highest rate among other current configurations. We also applied traditional machine learning ( ML ) classifiers to show the applicability of deep learners ( LSTM ) versus traditional models in dealing with cryptocurrency malware.
2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)
The architecture of current networks is static and nonprogrammable. In Software-Defined Networkin... more The architecture of current networks is static and nonprogrammable. In Software-Defined Networking (SDN) it is possible to have programmability and innovation within the network. In SDN, data plane and control plane are separated. So, the network operators can manage the network behavior using software. Some standardized interfaces such as OpenFlow are developed to enable the interaction among the controller and switches. OpenFlow switch manages the network traffic at the data plane. Packet parser is one of the main parts of OpenFlow switch. So far, some FPGA implementations have been presented for packet parsers for the SDN which lack required flexibility and programmability. These implementations support only one parse graph which causes limitations in creating new network protocols for new versions of the OpenFlow switch. To address this problem, in the present study the automatic generation of a programmable packet parser is presented for the OpenFlow switch. In addition to creating high flexibility in the switch, our proposed implementation is programmable and support different parse graph during the execution time. Simulation and implementation verify the appropriate performance of this programmable parser in OpenFlow Switch. Our implementation is able to improve the performance of the switch and enhance the flexibility of the data plane of SDN. The use of the programmable packet parser results in the increase in the switch speed, the reduction in wait time and service time, and the improvement in the Openflow switch performance.
There is currently widespread use of drones and drone technology due to their rising applications... more There is currently widespread use of drones and drone technology due to their rising applications that have come into fruition in the military, safety surveillance, agriculture, smart transportation, shipping, and delivery of packages in our Internet-of-Things global landscape. However, there are security-specific challenges with the authentication of drones while airborne. The current authentication approaches, in most drone-based applications, are subject to latency issues in real time with security vulnerabilities for attacks. To address such issues, we introduce a secure authentication model with low latency for drones in smart cities that looks to leverage blockchain technology. We apply a zone-based architecture in a network of drones, and use a customized decentralized consensus, known as drone-based delegated proof of stake (DDPOS), for drones among zones in a smart city that does not require reauthentication. The proposed architecture aims for positive impacts on increased security and reduced latency on the Internet of Drones (IoD). Moreover, we provide an empirical analysis of the proposed architecture compared to other peer models previously proposed for IoD to demonstrate its performance and security authentication capability. The experimental results clearly show that not only does the proposed architecture have low packet loss rate, high throughput, and low end-to-end delay in comparison to peer models but also can detect 97.5% of attacks by malicious drones while airborne.
Abstract Over the years, switches and network routers have been compromised frequently, and a lot... more Abstract Over the years, switches and network routers have been compromised frequently, and a lot of vulnerabilities have occurred in network infrastructure. Secure routing ( SR ) is one of the challenges that currently exists in computer networks. Software-defined networks ( SDN ) are designed by assuming that routers or switches are trustworthy. In SDN , untrusted devices have resulted in security issues such as traffic analysis, failure to receive information, packet change and removal, inaccurate routing, and network downtime. Using encryption methods is a possible solution to deal with some of these problems, but it requires additional infrastructure as well as significant overhead at runtime. One of the most trusted routing methods is through replicated devices (switches or routers). Recently we have seen less attention given to the number of replicated devices in SR . In this paper, the problem of SR is converted into a multi-objective optimization problem, considering the reliability of different manufacturers and SR with untrusted devices is performed. To this end, a mathematical model is provided to study the objectives of maximum reliability and cost minimization. The NSGA-II algorithm is applied to determine the optimal number of replicated devices in order to minimize the cost of implementing SR in spite of the presence of untrusted devices in SDN . Our simulation results show that our proposed method compared to the base method (without considering optimization) decreases implementation cost by 27% and increases the reliability from 70% to 93.2%.
Abstract The emergence of new network technologies and users' ever-increasing demand necessit... more Abstract The emergence of new network technologies and users' ever-increasing demand necessitates the introduction of highly programmable hardware with high flexibility and performance at the network data plane. The switches at the data plane need to be flexible enough to support protocols and test new ideas for increasing the abstraction of network programming. In most studies, Field Programmable Gate Arrays (FPGA) are applied in making switches flexible and reprogrammable; however, applying FPGAs alone does not meet the required flexibility. Next to applying FPGAs, it is necessary to provide an architecture that would allow developers to forego FPGA implementation hardware details and the complexity of hardware description language (HDL). In this paper, a new architecture of a programmable packet processor with high flexibility and programmability at the network data plane is presented, which supports all three operations required in switches: parsing, classification, and processing of packet data. To implement this architecture, the high-level P4 language is applied to allow the description of its register-transfer level (RTL) on the FPGA. In order to increase the processing speed, a pipeline approach within the proposed architecture is designed at the SDN data plane through pre-processing in the parse graph, identifying the traffic flow, and applying the hybrid control flow model in the data processing. The results show that our architecture operates at 320 MHz clock speed, which in comparison with NetFPGA-10G, NetFPGA-SUME, and ML605 peer architectures runs 2, 1.28, and 2.9 times faster in terms of processing speed, attesting to its efficiency. In addition, the evaluation on the Virtex-7 FPGA VC709 platform shows that our architecture consumes approximately 4.3% of lookup tables, 1.9% of flip-flops, and 1.3% of memory blocks, which are less than the hardware resource consumption of peer architectures.
In any interconnected healthcare system (e.g., those that are part of a smart city), interactions... more In any interconnected healthcare system (e.g., those that are part of a smart city), interactions between patients, medical doctors, nurses and other healthcare practitioners need to be secure and efficient. For example, all members must be authenticated and securely interconnected to minimize security and privacy breaches from within a given network. However, introducing security and privacy-preserving solutions can also incur delays in processing and other related services, potentially threatening patients lives in critical situations. A considerable number of authentication and security systems presented in the literature are centralized, and frequently need to rely on some secure and trusted third-party entity to facilitate secure communications. This, in turn, increases the time required for authentication and decreases throughput due to known overhead, for patients and inter-hospital communications. In this paper, we propose a novel decentralized authentication of patients in a distributed hospital network, by leveraging blockchain. Our notion of a healthcare setting includes patients and allied health professionals (medical doctors, nurses, technicians, etc), and the health information of patients. Findings from our in-depth simulations demonstrate the potential utility of the proposed architecture. For example, it is shown that the proposed architecture's decentralized authentication among a distributed affiliated hospital network does not require re-authentication. This improvement will have a considerable impact on increasing throughput, reducing overhead, improving response time, and decreasing energy consumption in the network. We also provide a comparative analysis of our model in relation to a base model of the network without blockchain to show the overall effectiveness of our proposed solution.
Internet of Things (IoT) is a disruptive technology in many aspects of our society, ranging from ... more Internet of Things (IoT) is a disruptive technology in many aspects of our society, ranging from communications to financial transactions to national security (e.g., Internet of Battlefield / Military Things), and so on. There are long-standing challenges in IoT, such as security, comparability, energy consumption, and heterogeneity of devices. Security and energy aspects play important roles in data transmission across IoT and edge networks, due to limited energy and computing (e.g., processing and storage) resources of networked devices. Whether malicious or accidental, interference with data in an IoT network potentially has real-world consequences. In this article, we explore the potential of integrating blockchain and software-defined networking (SDN) in mitigating some of the challenges. Specifically, we propose a secure and energy-efficient blockchain-enabled architecture of SDN controllers for IoT networks using a cluster structure with a new routing protocol. The architecture uses public and private blockchains for Peer to Peer (P2P) communication between IoT devices and SDN controllers, which eliminates Proof-of-Work (POW), as well as using an efficient authentication method with the distributed trust, making the blockchain suitable for resource-constrained IoT devices. The experimental results indicate that the routing protocol based on the cluster structure has higher throughput, lower delay, and lower energy consumption than EESCFD, SMSN, AODV, AOMDV, and DSDV routing protocols. In other words, our proposed architecture is demonstrated to outperform classic blockchain.
Abstract Security is one of the most challenging issues in software defined networking (SDN), and... more Abstract Security is one of the most challenging issues in software defined networking (SDN), and causes include the inability to detect the contents of the packets. In addition, file transferring to SDN is a potential attack vector that can be exploited at the network level. On the SDN data plane (i.e. the switch), packets are processed so that their behavior in the network can be determined. Packet parser (PP) acts as the main role of this operation on the switch. PP plays a very important role in identifying packets and supporting protocols and testing new ideas in SDN, which requires packet parsers on the data plane to provide the necessary flexibility and programmability. In recent times, cryptographic ledger technology (also referred to as Blockchain in the literature) has been applied to securely transfer transactions and files in the networks, mainly for crypto payments. In this paper, we propose a new packet parser architecture called Blockchain-enabled Packet Parser (BPP) based on the security characteristics of the blockchain and support for data processing functions with the description of Programming Protocol-Independent Packet Processors (P4) language that has the BPP-independent attribute of the protocol. In the proposed architecture, we provide a mathematical model based on a multivariate correlation approach for attack detection from the observed packet traffic. The implementation of BPP architecture is on Field Programmable Gate Array (FPGA), which is known for its higher processing speed, flexibility, and lower consumption resources. The result indicates that the proposed BPP is able to detect attacks and policy performed on the control plane in how to detect an attack from a packet structure efficiently. Furthermore, the impact of the bandwidth with and without the BPP in hardware environment is evaluated to demonstrate BPP's efficiency.
Nowadays, routing and the improvement of reliability along with the load balancing and congestion... more Nowadays, routing and the improvement of reliability along with the load balancing and congestion control are the most important and challenging concepts in ad-hoc networks. However, there are some constraints in the bandwidth and the communication range due to the different utility of routing in the Mobile Ad Hoc Network (MANET). These restrictions, in addition to the dynamic network topology, are causing more complexity of routing and data transmission. These problems make the use of conventional methods inefficient, especially in the congestion and traffic control. So, there is a need to propose new solutions for these kinds of networks. This study has used the multipath routing based on the original protocol Ad-Hoc On-Demand Multipath Distance Vector (AOMDV). It proposes an appropriate protocol for the congestion control and balances the favorable loads in the routes. The proposed algorithm is based on different parameters that prepare the fittest multipaths based on the most ef...
In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from ... more In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from both the agriculture industry as well as the research community. Altogether, SF and PA aim to help farmers use inputs (such as fertilizers and pesticides) more efficiently through using Internet of Things (IoT) devices, but in doing so, they create new security threats that can defeat this purpose in the absence of adequate awareness and proper countermeasures. A survey on different security-related challenges is required to raise awareness and pave they way for further research in this area. In this paper, we first itemize the security aspects of SF and PA. Next, we review the types of cyber attacks that can violate each of these aspects. Accordingly, we present a taxonomy on cyber-threats to SF and PA on the basis of their relations to different stages of Cyber-Kill Chain (CKC). Among cyber-threats, we choose Advanced Persistent Threats (APTs) for further study. Finally, we studied rel...
Success in machine learning has led to a wealth of Artificial Intelligence (AI) systems. A great ... more Success in machine learning has led to a wealth of Artificial Intelligence (AI) systems. A great deal of attention is currently being set on the development of advanced Machine Learning (ML)-based solutions for a variety of automated predictions and classification tasks in a wide array of industries. However, such automated applications may introduce bias in results, making it risky to use these ML models in security-and privacy-sensitive domains. The prediction should be accurate and models have to be interpretable/explainable to understand how they work. In this research, we conduct an empirical evaluation of two major explainer/interpretable methods called LIME and SHAP on two datasets using deep learning models, including Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). The results demonstrated that SHAP performs slightly better than LIME in terms of Identity, Stability, and Separability from two different datasets (Breast Cancer Wisconsin (Diagnostic) and NIH Chest X-Ray) that we used.
Deepfakes generally refers to a new breed of adversarial deep learning technology to create non-c... more Deepfakes generally refers to a new breed of adversarial deep learning technology to create non-consensual contents (mostly videos) for nefarious purposes. Most researches focus on the ‘detection’ of deepfakes using AI-assisted approaches to take on this problem. This has been the common method operandi used by researchers thus far. However, there is one missing aspect of the deepfake problem, which is ‘authentication’. Instead of attempting to detect what content is fake, in this paper, we focus on techniques to provide tamper-proof evidence of what content is real. Blockchain has been advocated to be helpful with the authentication aspect of many real-world scenarios. Despite the scattered efforts around such solutions, there are no studies that can shed light on where it makes sense to adopt blockchain technology to better take on the deepfake problem. This paper aims to provide a one-stop guide to using blockchain to navigate deepfake artificial intelligence. We discuss potentia...
A vision-based intelligent traffic control system is a robust framework that controls the traffic... more A vision-based intelligent traffic control system is a robust framework that controls the traffic flow in real-time by estimating the traffic density near traffic lights. In this paper, a traffic light control system based on fuzzy Qlearning is proposed according to the vehicle density and the pedestrian number estimated from the visual information. The aim of proposed approach is to minimize the pedestrian and the car waiting time and maximize throughput for an isolated 4-way traffic intersection. Also, the pedestrian traffic light is controlled based on the fuzzy logic. The states and actions of the Q-learning variables are set by a fuzzy algorithm which can be learned through environmental interactions. The system can detect the number of pedestrians and vehicles using visual information from cameras and machine vision algorithms. The fuzzy control system can adjust the sequence of green phases to decrease the total waiting time and the mean of the queue length. The proposed algo...
Traditional Internet of Things (IoT) system architectures are centralized. Data from the devices ... more Traditional Internet of Things (IoT) system architectures are centralized. Data from the devices are stored on the back-end, where they are processed and analyzed, and then reconnected to IoT devices. The scalability of centralized systems is very limited especially when an abundance of devices exist on an IoT network. Network security in IoT networks is another aspect at stake that could be compromised easily due to the unavailability of security in design mechanisms in most IoT networks. Blockchain technology is a distributed ledger without any intensive management that can store all transactions which leads to large amounts of data that increases over time. Large data amounts will be more pronounced with the increasing IoT devices and blockchain use cases involving IoT. IoT devices are for the most part constrained in both energy, storage, and computation, unlikely to be able to store all blockchain data. The current implementation of blockchain is not IoT friendly. Moreover, consensus on the blockchain using Proof of Work (PoW) is infeasible due to computational constraints. In this paper, we propose a Secure and Low latency Proof of Work (SLPoW) protocol. We also bring the computation of miners onto a Field-programmable gate array (FPGA) to improve the processing speeds of computation. We consider our resulting blockchain technology using SLPoW suitable for the evolving Green IoT setting.
Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchai... more Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchain systems such as Ethereum, Hyperledger Fabric, and Corda, have emerged with public and private accessibility. It has been widely acknowledged that no single blockchain network will fit all use cases. As a result, we have observed the increasing popularity of multi-blockchain ecosystem in which customers will move toward different blockchains based on their particular requirements. Hence, the efficiency and security requirements of interactions among these heterogeneous blockchains become critical. In realization of this multi-blockchain paradigm, initiatives in building Interoperability-Facilitating Platforms (IFPs) that aim at bridging different blockchains (a.k.a. blockchain interoperability) have come to the fore. Despite current efforts, it is extremely difficult for blockchain customers (organizations, governments, companies) to understand the trade-offs between different IFPs and ...
In recent years, there has been rapid growth in developing smart cities. Nearly 70% of the Earthâ... more In recent years, there has been rapid growth in developing smart cities. Nearly 70% of the Earth’s surface is covered by water and a large proportion of underwater environments are still unknown and have not been explored. In this context, Internet of things (IoT) is one of the most important technologies used in smart cities. Due to the growth of IoT and its influence in all areas of human life, including the underwater environment, a new class of IoT, called Internet of underwater things (IoUT) has emerged. IoUT includes a network of underwater smart devices that are connected to each other and has applications in environmental monitoring, underwater exploration, disaster prevention and military. In autonomous interactions of underwater devices, objects must be authenticated and securely interconnected to avoid security risks by malicious nodes. Most authentication methods and security mechanisms are centralized and often require a trustful third party in communications, which may well increase the computation cost and energy consumption due to the subsequent overhead, especially for underwater communications. On the other hand, there are restrictions on devices in the underwater environment, the most important of which are energy constraints. In this paper, we propose a robust, transparent, and energy-efficient decentralized authentication mechanism for IoUT using blockchain technology. We show through results that the proposed method is suitable for underwater devices with limited memory, energy, and computational power. The proposed model’s decentralized authentication in a cluster network has a significant effect on reducing the energy consumption of the devices by 74.63% compared to classic authentication methods. Moreover, using the proposed method allows a savings of more than 41.9% in end-to-end delay and increases delivery rate by 21.6%.
Abstract In recent years, cryptocurrency trades have increased dramatically, and this trend has a... more Abstract In recent years, cryptocurrency trades have increased dramatically, and this trend has attracted cyber-threat actors to exploit the existing vulnerabilities and infect their targets. The malicious actors use cryptocurrency malware to perform complex computational tasks using infected devices. Since cryptocurrency malware threats perform a legal process, it is a challenging task to detect this type of threat by a manual or heuristic method. In this paper, we propose a novel deep Recurrent Neural Network ( RNN ) learning model for hunting cryptocurrency malware threats. Specifically, our proposed model utilizes the RNN to analyze Windows applications’ operation codes (Opcodes) as a case study. We collect a real-world dataset that comprises of 500 cryptocurrency malware and 200 benign-ware samples, respectively. The proposed model trains with five different Long Short-Term Memory ( LSTM ) structures and is evaluated by a 10-fold cross-validation ( CV ) technique. The obtained results prove that a 3-layer configuration model gains 98% of detection accuracy, which is the highest rate among other current configurations. We also applied traditional machine learning ( ML ) classifiers to show the applicability of deep learners ( LSTM ) versus traditional models in dealing with cryptocurrency malware.
2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)
The architecture of current networks is static and nonprogrammable. In Software-Defined Networkin... more The architecture of current networks is static and nonprogrammable. In Software-Defined Networking (SDN) it is possible to have programmability and innovation within the network. In SDN, data plane and control plane are separated. So, the network operators can manage the network behavior using software. Some standardized interfaces such as OpenFlow are developed to enable the interaction among the controller and switches. OpenFlow switch manages the network traffic at the data plane. Packet parser is one of the main parts of OpenFlow switch. So far, some FPGA implementations have been presented for packet parsers for the SDN which lack required flexibility and programmability. These implementations support only one parse graph which causes limitations in creating new network protocols for new versions of the OpenFlow switch. To address this problem, in the present study the automatic generation of a programmable packet parser is presented for the OpenFlow switch. In addition to creating high flexibility in the switch, our proposed implementation is programmable and support different parse graph during the execution time. Simulation and implementation verify the appropriate performance of this programmable parser in OpenFlow Switch. Our implementation is able to improve the performance of the switch and enhance the flexibility of the data plane of SDN. The use of the programmable packet parser results in the increase in the switch speed, the reduction in wait time and service time, and the improvement in the Openflow switch performance.
There is currently widespread use of drones and drone technology due to their rising applications... more There is currently widespread use of drones and drone technology due to their rising applications that have come into fruition in the military, safety surveillance, agriculture, smart transportation, shipping, and delivery of packages in our Internet-of-Things global landscape. However, there are security-specific challenges with the authentication of drones while airborne. The current authentication approaches, in most drone-based applications, are subject to latency issues in real time with security vulnerabilities for attacks. To address such issues, we introduce a secure authentication model with low latency for drones in smart cities that looks to leverage blockchain technology. We apply a zone-based architecture in a network of drones, and use a customized decentralized consensus, known as drone-based delegated proof of stake (DDPOS), for drones among zones in a smart city that does not require reauthentication. The proposed architecture aims for positive impacts on increased security and reduced latency on the Internet of Drones (IoD). Moreover, we provide an empirical analysis of the proposed architecture compared to other peer models previously proposed for IoD to demonstrate its performance and security authentication capability. The experimental results clearly show that not only does the proposed architecture have low packet loss rate, high throughput, and low end-to-end delay in comparison to peer models but also can detect 97.5% of attacks by malicious drones while airborne.
Abstract Over the years, switches and network routers have been compromised frequently, and a lot... more Abstract Over the years, switches and network routers have been compromised frequently, and a lot of vulnerabilities have occurred in network infrastructure. Secure routing ( SR ) is one of the challenges that currently exists in computer networks. Software-defined networks ( SDN ) are designed by assuming that routers or switches are trustworthy. In SDN , untrusted devices have resulted in security issues such as traffic analysis, failure to receive information, packet change and removal, inaccurate routing, and network downtime. Using encryption methods is a possible solution to deal with some of these problems, but it requires additional infrastructure as well as significant overhead at runtime. One of the most trusted routing methods is through replicated devices (switches or routers). Recently we have seen less attention given to the number of replicated devices in SR . In this paper, the problem of SR is converted into a multi-objective optimization problem, considering the reliability of different manufacturers and SR with untrusted devices is performed. To this end, a mathematical model is provided to study the objectives of maximum reliability and cost minimization. The NSGA-II algorithm is applied to determine the optimal number of replicated devices in order to minimize the cost of implementing SR in spite of the presence of untrusted devices in SDN . Our simulation results show that our proposed method compared to the base method (without considering optimization) decreases implementation cost by 27% and increases the reliability from 70% to 93.2%.
Abstract The emergence of new network technologies and users' ever-increasing demand necessit... more Abstract The emergence of new network technologies and users' ever-increasing demand necessitates the introduction of highly programmable hardware with high flexibility and performance at the network data plane. The switches at the data plane need to be flexible enough to support protocols and test new ideas for increasing the abstraction of network programming. In most studies, Field Programmable Gate Arrays (FPGA) are applied in making switches flexible and reprogrammable; however, applying FPGAs alone does not meet the required flexibility. Next to applying FPGAs, it is necessary to provide an architecture that would allow developers to forego FPGA implementation hardware details and the complexity of hardware description language (HDL). In this paper, a new architecture of a programmable packet processor with high flexibility and programmability at the network data plane is presented, which supports all three operations required in switches: parsing, classification, and processing of packet data. To implement this architecture, the high-level P4 language is applied to allow the description of its register-transfer level (RTL) on the FPGA. In order to increase the processing speed, a pipeline approach within the proposed architecture is designed at the SDN data plane through pre-processing in the parse graph, identifying the traffic flow, and applying the hybrid control flow model in the data processing. The results show that our architecture operates at 320 MHz clock speed, which in comparison with NetFPGA-10G, NetFPGA-SUME, and ML605 peer architectures runs 2, 1.28, and 2.9 times faster in terms of processing speed, attesting to its efficiency. In addition, the evaluation on the Virtex-7 FPGA VC709 platform shows that our architecture consumes approximately 4.3% of lookup tables, 1.9% of flip-flops, and 1.3% of memory blocks, which are less than the hardware resource consumption of peer architectures.
In any interconnected healthcare system (e.g., those that are part of a smart city), interactions... more In any interconnected healthcare system (e.g., those that are part of a smart city), interactions between patients, medical doctors, nurses and other healthcare practitioners need to be secure and efficient. For example, all members must be authenticated and securely interconnected to minimize security and privacy breaches from within a given network. However, introducing security and privacy-preserving solutions can also incur delays in processing and other related services, potentially threatening patients lives in critical situations. A considerable number of authentication and security systems presented in the literature are centralized, and frequently need to rely on some secure and trusted third-party entity to facilitate secure communications. This, in turn, increases the time required for authentication and decreases throughput due to known overhead, for patients and inter-hospital communications. In this paper, we propose a novel decentralized authentication of patients in a distributed hospital network, by leveraging blockchain. Our notion of a healthcare setting includes patients and allied health professionals (medical doctors, nurses, technicians, etc), and the health information of patients. Findings from our in-depth simulations demonstrate the potential utility of the proposed architecture. For example, it is shown that the proposed architecture's decentralized authentication among a distributed affiliated hospital network does not require re-authentication. This improvement will have a considerable impact on increasing throughput, reducing overhead, improving response time, and decreasing energy consumption in the network. We also provide a comparative analysis of our model in relation to a base model of the network without blockchain to show the overall effectiveness of our proposed solution.
Internet of Things (IoT) is a disruptive technology in many aspects of our society, ranging from ... more Internet of Things (IoT) is a disruptive technology in many aspects of our society, ranging from communications to financial transactions to national security (e.g., Internet of Battlefield / Military Things), and so on. There are long-standing challenges in IoT, such as security, comparability, energy consumption, and heterogeneity of devices. Security and energy aspects play important roles in data transmission across IoT and edge networks, due to limited energy and computing (e.g., processing and storage) resources of networked devices. Whether malicious or accidental, interference with data in an IoT network potentially has real-world consequences. In this article, we explore the potential of integrating blockchain and software-defined networking (SDN) in mitigating some of the challenges. Specifically, we propose a secure and energy-efficient blockchain-enabled architecture of SDN controllers for IoT networks using a cluster structure with a new routing protocol. The architecture uses public and private blockchains for Peer to Peer (P2P) communication between IoT devices and SDN controllers, which eliminates Proof-of-Work (POW), as well as using an efficient authentication method with the distributed trust, making the blockchain suitable for resource-constrained IoT devices. The experimental results indicate that the routing protocol based on the cluster structure has higher throughput, lower delay, and lower energy consumption than EESCFD, SMSN, AODV, AOMDV, and DSDV routing protocols. In other words, our proposed architecture is demonstrated to outperform classic blockchain.
Abstract Security is one of the most challenging issues in software defined networking (SDN), and... more Abstract Security is one of the most challenging issues in software defined networking (SDN), and causes include the inability to detect the contents of the packets. In addition, file transferring to SDN is a potential attack vector that can be exploited at the network level. On the SDN data plane (i.e. the switch), packets are processed so that their behavior in the network can be determined. Packet parser (PP) acts as the main role of this operation on the switch. PP plays a very important role in identifying packets and supporting protocols and testing new ideas in SDN, which requires packet parsers on the data plane to provide the necessary flexibility and programmability. In recent times, cryptographic ledger technology (also referred to as Blockchain in the literature) has been applied to securely transfer transactions and files in the networks, mainly for crypto payments. In this paper, we propose a new packet parser architecture called Blockchain-enabled Packet Parser (BPP) based on the security characteristics of the blockchain and support for data processing functions with the description of Programming Protocol-Independent Packet Processors (P4) language that has the BPP-independent attribute of the protocol. In the proposed architecture, we provide a mathematical model based on a multivariate correlation approach for attack detection from the observed packet traffic. The implementation of BPP architecture is on Field Programmable Gate Array (FPGA), which is known for its higher processing speed, flexibility, and lower consumption resources. The result indicates that the proposed BPP is able to detect attacks and policy performed on the control plane in how to detect an attack from a packet structure efficiently. Furthermore, the impact of the bandwidth with and without the BPP in hardware environment is evaluated to demonstrate BPP's efficiency.
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