Junaid Qadir | University of Genoa (original) (raw)

Papers by Junaid Qadir

Springer Nature, 2022

The realm of Low Power Wide Area Network (LPWAN) has a paramount influence on the way we work and... more The realm of Low Power Wide Area Network (LPWAN) has
a paramount influence on the way we work and live. For instance, realtime applications and rapid packet transiting for long-range have now
come into practice that was previously considered mysterious. However,
euphoria becomes a problem when it comes to security considerations, as
low-power devices possess limited processing units that are unable to elucidate robust security algorithms. In this case, the Low Power Wide Area
Network (LoRaWAN) stepped into a technological competition that filled
the gap by adopting the end-to-end security feature. Though, LoRaWAN
protocol entails fundamental security requirements but the implementation matters. This paper presents cybersecurity evaluation in LoRaWAN
implementation. In addition, we provide a bibliometric overview of security considerations in LoRaWAN that helps researchers for thorough
insights and implementation.

IEEE ACCESS, 2023

Owing to the geographically scattered end devices (EDs) in long-range wide area networks (LoRaWAN... more Owing to the geographically scattered end devices (EDs) in long-range wide area networks (LoRaWAN), devices that combat challenging cyber threats and attacks are of critical significance. In this perspective, LoRa Alliance® is continuously evolving the security of LoRaWAN and recently introduced a new version i.e., LoRaWAN 1.1x that is featured with security improvement. However, the wireless nature of LoRaWAN implementation still leaves it vulnerable to security breaches that compromise its integrity.
Several problems have been pinpointed in the newer version such as one issue with key distribution in LoRaWAN 1.1 is that the keys are often pre-installed on the devices at the time of manufacturing. It can introduce security risks if the keys are not adequately protected or if the devices are compromised before they are deployed. In other words, the pre-installed keys may not be updated regularly, which can also introduce security risks. Thus, the keys need to be handled securely to maintain the security of the network and the over-the-air firmware updates feature could introduce new security challenges for the key distribution. This paper presents a key generation and distribution (KGD) mechanism that securely exchanges the root key between the ED and the application server (AS). The KGD protocol provides authentication by integrating Advanced Encryption Standard (AES-128) in addition to a secure hash function known as Argon2. The
proposed protocol utilizes Elliptic-Curve Diffie-Hellman (ECDH) key exchange method that makes the protocol resilient to cyber threats. The ECDH algorithm exchanges the keys on the insecure channels and is,
therefore, vulnerable to Man-in-the-Middle (MITM) attacks in the network. Therefore, to validate the key agreement and avoid adversaries, the KGD protocol considers the Elliptic Curve Digital Signature Algorithm (ECDSA) that authenticates and allows legitimate instances in the network. In last, a formal security analysis using the Scyther tool validates the security enhancement of the KGD protocol.

Advances in Intelligent Systems and Computing, 2018

Recently, the underwater wireless sensor networks (UWSNs) have been proposed for exploration of t... more Recently, the underwater wireless sensor networks (UWSNs) have been proposed for exploration of the underwater resources and to obtain information about the aquatic environment. The noise in UWSNs challenges the successful transmission of packets from a sender to a receiver. There are many protocols in literature that address noise reduction/avoidance during underwater communication. However, they require localization information of each sensor nodes that itself is a challenging issue. In this paper, the minimum channel noise is considered and the depth and noise aware routing (DNAR) protocol is proposed to send the packets reliably from a sender node to a surface sink. In the DNAR protocol, more energy is assigned to the sensor nodes that have depth level \(\le \)150 m. Therefore, the sensor nodes that deployed are nearby to the sink node have more capability of transmission and will not die quickly. Also, the proposed protocol selects the forwarder candidate that have lowest depth and minimum channel noise at the receiver. As compared to some existing schemes, the proposed scheme requires no geographical information of the nodes for data routing. The DNAR protocol is validated by Matlab simulation and compared it with the DBR scheme. The simulation results show that the DNAR has better results in-terms of packet delivery ratio (PDR), total energy consumption, and the network lifetime.

Energies, 2019

Owing to the harsh and unpredictable behavior of the sea channel, network protocols that combat t... more Owing to the harsh and unpredictable behavior of the sea channel, network protocols that combat the undesirable and challenging properties of the channel are of critical significance. Protocols addressing such challenges exist in literature. However, these protocols consume an excessive amount of energy due to redundant packets transmission or have computational complexity by being dependent on the geographical positions of nodes. To address these challenges, this article designs two protocols for underwater wireless sensor networks (UWSNs). The first protocol, depth and noise-aware routing (DNAR), incorporates the extent of link noise in combination with the depth of a node to decide the next information forwarding candidate. However, it sends data over a single link and is, therefore, vulnerable to the harshness of the channel. Therefore, routing in a cooperative fashion is added to it that makes another scheme called cooperative DNAR (Co-DNAR), which uses source-relay-destination...

IEEE Access, 2021

At present, with the growing number of Web 2.0 platforms such as Instagram, Facebook, and Twitter... more At present, with the growing number of Web 2.0 platforms such as Instagram, Facebook, and Twitter, users honestly communicate their opinions and ideas about events, services, and products. Owing to this rise in the number of social platforms and their extensive use by people, enormous amounts of data are produced hourly. However, sentiment analysis or opinion mining is considered as a useful tool that aims to extract the emotion and attitude from the user-posted data on social media platforms by using different computational methods to linguistic terms and various Natural Language Processing (NLP). Therefore, enhancing text sentiment classification accuracy has become feasible, and an interesting research area for many community researchers. In this study, a new Fuzzy Deep Learning Classifier (FDLC) is suggested for improving the performance of data-sentiment classification. Our proposed FDLC integrates Convolutional Neural Network (CNN) to build an effective automatic process for extracting the features from collected unstructured data and Feedforward Neural Network (FFNN) to compute both positive and negative sentimental scores. Then, we used the Mamdani Fuzzy System (MFS) as a fuzzy classifier to classify the outcomes of the two used deep (CNN+FFNN) learning models in three classes, which are: Neutral, Negative, and Positive. Also, to prevent the long execution time taking by our hybrid proposed FDLC, we have implemented our proposal under the Hadoop cluster. An experimental comparative study between our FDLC and some other suggestions from the literature is performed to demonstrate our offered classifier's effectiveness. The empirical result proved that our FDLC performs better than other classifiers in terms of true positive rate, true negative rate, false positive rate, false negative rate, error rate, precision, classification rate, kappa statistic, F1-score and time consumption, complexity, convergence, and stability. INDEX TERMS Deep learning, convolutional neural network (CNN), sentiment analysis, feedforward neural network (FFNN), fuzzy logic, Hadoop framework, MapReduce, Hadoop Distributed File System (HDFS). I. INTRODUCTION Social network platforms like Instagram, Twitter, Youtube, LinkedIn, and Facebook have been considered essential and indispensable in our daily activities. Day-today , billions of social media users disseminate billions of personal or professional posts [1]. For example, Marketers use social media to spread professional posts that endeavor to present, promote, advertise, and market their products, services, events, and brand names. On the other hand, the customers interact The associate editor coordinating the review of this manuscript and approving it for publication was Jing Bi. with the marketers' posts by express their feelings, opinions, ideas, attitudes about the presented products or services [2]. Further, the marketers gather the customer's feedback, study, and analyze it using the sentiment analysis tool. The main objective from they are doing these operations is to improve the quality of their products and services, enhance their offerings by adding other privileges, and improve their brand performance [1], [2]. Sentiment Analysis (SA) plays a significant role in Business Intelligence (BI). In BI, it uses to get responses for questions such as, 'Why is product sales so low?', 'Have customer's needs are fully satisfied by utilizing our products?',

IEEE Access, 2021

Opinion Mining (OM) is a field of Natural Language Processing (NLP) that aims to capture human se... more Opinion Mining (OM) is a field of Natural Language Processing (NLP) that aims to capture human sentiment in the given text. With the ever-spreading of online purchasing websites, micro-blogging sites, and social media platforms, OM in online social media platforms has picked the interest of thousands of scientific researchers. Because the reviews, tweets and blogs acquired from these social media networks, act as a significant source for enhancing the decision making process. The obtained textual data (reviews, tweets, or blogs) are classified into three different class labels which are negative, neutral and positive for analyzing and extracting relevant information from the given dataset. In this contribution, we introduce an innovative MapReduce improved weighted ID3 decision tree classification approach for OM, which consists mainly of three aspects: Firstly We have used several feature extractors to efficiently detect and capture the relevant data from the given tweets, including N-grams or character-level, Bag-Of-Words, word embedding (GloVe, Word2Vec), FastText, and TF-IDF. Secondly, we have applied a multiple feature selector to reduce the high feature's dimensionality, including Chi-square, Gain Ratio, Information Gain, and Gini Index. Finally, we have employed the obtained features to carry out the classification task using an improved ID3 decision tree classifier, which aims to calculate the weighted information gain instead of information gain used in traditional ID3. In other words, to measure the weighted information gain for the current conditioned feature, we follow two steps: First, we compute the weighted correlation function of the current conditioned feature. Second, we multiply the obtained weighted correlation function by the information gain of this current conditioned feature. This work is implemented in a distributed environment using the Hadoop framework, with its programming framework MapReduce and its distributed file system HDFS. Its primary goal is to enhance the performance of a well-known ID3 classifier in terms of accuracy, execution time, and ability to handle the massive datasets. We have carried out several experiences that aims to assess the effectiveness of our suggested classifier compared to some other contributions chosen from the literature. The experimental results demonstrated that our ID3 classifier works better on COVID-19_Sentiments dataset than other classifiers in terms of Recall (85.72 %), specificity (86.51 %), error rate (11.18 %), false-positive rate (13.49 %), execution time (15.95s), kappa statistic (87.69 %), F1-score (85.54 %), classification rate (88.82 %), false-negative rate (14.28 %), precision rate (86.67 %), convergence (it convergent towards the iteration 90), stability (it is more stable with mean deviation standard equal to 0.12 %), and complexity (it requires much lower time and space computational complexity).

IEEE Access, 2021

Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms, 2020

The realm of cloud computing has revolutionized access to cloud resources and their utilization a... more The realm of cloud computing has revolutionized access to cloud resources and their utilization and applications over the Internet. However, deploying cloud computing for delay critical applications and reducing the delay in access to the resources are challenging. The Mobile Edge Computing (MEC) paradigm is one of the effective solutions, which brings the cloud computing services to the proximity of the edge network and leverages the available resources. This paper presents a survey of the latest and state-of-the-art algorithms, techniques, and concepts of MEC. The proposed work is unique in that the most novel algorithms are considered, which are not considered by the existing surveys. Moreover, the chosen novel literature of the existing researchers is classified in terms of performance metrics by describing the realms of promising performance and the regions where the margin of improvement exists for future investigation for the future researchers. This also eases the choice of a particular algorithm for a particular application. As compared to the existing surveys, the bibliometric overview is provided, which is further helpful for the researchers, engineers, and scientists for a thorough insight, application selection, and future consideration for improvement. In addition, applications related to the MEC platform are presented. Open research challenges, future directions, and lessons learned in area of the MEC are provided for further future investigation. INDEX TERMS Mobile edge computing, cloud servers, networks, edge device, smart cities, latency, energy. NOMENCLATURE APs Access points BS Base station CCBM Computational capability based matching DRL Deep reinforcement learning D2D Device-to-device E2E End-to-end ECIPs Edge computing infrastructure providers IoT Internet-of-Things IPDC Interior penalty with D.C IA Iterative algorithms JCOS Joint cache offloading solution KKT Karush-Kuhn-Tucker

IEEE ACCESS, 2020

In underwater wireless sensor networks (UWSNs), protocols with efficient energy and reliable comm... more In underwater wireless sensor networks (UWSNs), protocols with efficient energy and reliable communication are challenging, due to the unpredictable aqueous environment. The sensor nodes deployed in the specific region can not last for a long time communicating with each other because of limited energy. Also, the low speed of the acoustic waves and the small available bandwidth produce high latency as well as high transmission loss, which affects the network reliability. To address such problems, several protocols exist in literature. However, these protocols lose energy efficiency and reliability, as they calculate the geographical coordinates of the node or they do not avoid unfavorable channel conditions. To tackle these challenges, this article presents the two novel routing protocol for UWSNs. The first one energy path and channel aware (EPACA) protocol transmits data from a bottom of the water to the surface sink by taking node's residual energy (R e), packet history (H p), distance (d) and bit error rate (BER). In EPACA protocol, a source node computes a function value for every neighbor node. The most prior node in terms of calculated function is considered as the target destination. However, the EPACA protocol may not always guarantee packet reliability, as it delivers packets over a single path. To maintain the packet reliability in the network, the cooperative-energy path and channel aware (CoEPACA) routing scheme is added which uses relay nodes in packet advancement. In the CoEPACA protocol, the destination node receives various copies from the source and relay(s). The received data at the destination from multiple routes make the network more reliable due to avoiding the erroneous data. The MATLAB simulations results validated the performance of the proposed algorithms. The EPACA protocol consumed 29.01% and the CoEPACA protocol 19.04% less energy than the counterpart scheme. In addition, the overall 12.40% improvement is achieved in the packet's reliability. Also, the EPACA protocol outperforms for packets' latency and network lifetime.

2019 22nd International Multitopic Conference (INMIC), IEEE., Mar 5, 2020

In acoustic wireless sensor networks (AWSNs), cooperative routing extenuates the contrary channel... more In acoustic wireless sensor networks (AWSNs), cooperative routing extenuates the contrary channel effects (noise, attenuation, and fading). In critical mission applications, reliability and efficient energy are the fundamental parameters. The adverse channel affects corrupt the data packet and makes the network very hard to ensures error-free communication. To overcomes these challenges, we introduce a cooperative stability aware routing (CSAR) scheme for acoustic sensor networks. The CSAR provides a better network lifetime by consuming the minimum amount of energy and improves network reliability. In the proposed scheme, the relay and destination nodes (DNN) are chosen on the base of the desire function parameters (lowest depth, residual energy, and lowest noise). The node which has the best function parameters is considered the destination. While the relay node is the second-highest priority node. The destination node cooperates with a single relay and frontward the packet towards the sink node positioned at the ocean surface by using multi-hoping. The proposed protocol renders prominent outcomes in terms of energy consumption, packet acceptance ratio, dead nodes, and packet received successfully at the sink.

IEEE Access, 2019

Owning to the vital resources in a harsh and unforeseeable aqueous environment, the network stabi... more Owning to the vital resources in a harsh and unforeseeable aqueous environment, the network stability and reliability in underwater acoustic wireless sensor networks (UAWSNs) have paramount
significance. Stability guarantees the consistent performance of the network node’s energy consumption, avoids data loss, packets reception time and network lifetime. The reliability of the packet ensures the selection of the favorable channel and avoid adverse channel effects, and the vital information is easily obtained from data packets. This paper introduces two new routing schemes for UAWSNs; stable and reliable short-path routing (RSPR) scheme, and cooperative reliable short-path routing (CoRSPR). In RSPR routing, the destination node is selected by considering the weighting function parameters of the highest residual energy, highest SNR, lowest euclidean distance, and least number of neighbor nodes. The scheme reduces the energy consumption due to less number of nodes contribution in the packet advancement process. The RSPR protocol is a non-cooperative technique, where the packets are delivered using a single-path link, which may not be consistently reliable. To cope with this issue, the CoRSPR protocol is proposed, which takes cooperative routing into account, for stable and reliable data delivery. In cooperative routing, the reception of more than one copy of the data packet is involved by the destination node. This reduces the unfavorable channel effects during data delivery. The simulation results show that the proposed schemes achieve better performance in terms of dead nodes, energy left in the battery, packet acceptance ratio, successful receiving of packets at the sink and E-2-E delay.

MDPI-energies, 2019

Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham, 2018

Recently, the underwater wireless sensor networks (UWSNs) have been proposed for exploration of t... more Recently, the underwater wireless sensor networks (UWSNs)
have been proposed for exploration of the underwater resources and
to obtain information about the aquatic environment. The noise in
UWSNs challenges the successful transmission of packets from a sender
to a receiver. There are many protocols in literature that address noise
reduction/avoidance during underwater communication. However, they
require localization information of each sensor nodes that itself is a challenging issue. In this paper, the minimum channel noise is considered
and the depth and noise aware routing (DNAR) protocol is proposed
to send the packets reliably from a sender node to a surface sink. In
the DNAR protocol, more energy is assigned to the sensor nodes that
have depth level ≤150 m. Therefore, the sensor nodes that deployed are
nearby to the sink node have more capability of transmission and will
not die quickly. Also, the proposed protocol selects the forwarder candidate that have lowest depth and minimum channel noise at the receiver.
As compared to some existing schemes, the proposed scheme requires no
geographical information of the nodes for data routing. The DNAR protocol is validated by Matlab simulation and compared it with the DBR
scheme. The simulation results show that the DNAR has better results
in-terms of packet delivery ratio (PDR), total energy consumption, and
the network lifetime.

Conference Presentations by Junaid Qadir

2022 IEEE Zooming Innovation in Consumer Technologies Conference (ZINC), 2022

The proliferation of monitoring in unpredictable environments has aided the world in solving chal... more The proliferation of monitoring in unpredictable
environments has aided the world in solving challenges that were
previously thought to be insurmountable. Drastic advancement
has been pinpointed in the way we live, work, and play; however,
the data odyssey has yet started. From sensing to monitoring,
the endless possibility enabled by LoRa, the long-range low
power solution has made its mark on the technological world.
With the adoption of the LoRaWAN, the long-range low power
wide area network has appeared in existence to cope with the
constraints associated with the Internet of Things (IoT) infrastructure. This paper presents a practical experiment for sensing
the environmental condition using the LoRaWAN solution. The
proposed work allows the users to check the environmental
effects (temperature, and humidity) online. Furthermore, the
signal behavior has been recorded and cross-verified by using
MATLAB software implementation.

Springer Nature, 2022

IEEE ACCESS, 2023

Advances in Intelligent Systems and Computing, 2018

Energies, 2019

IEEE Access, 2021

Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms, 2020

IEEE ACCESS, 2020

2019 22nd International Multitopic Conference (INMIC), IEEE., Mar 5, 2020

IEEE Access, 2019

MDPI-energies, 2019

Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham, 2018

Recently, the underwater wireless sensor networks (UWSNs) have been proposed for exploration of t... more Recently, the underwater wireless sensor networks (UWSNs)
have been proposed for exploration of the underwater resources and
to obtain information about the aquatic environment. The noise in
UWSNs challenges the successful transmission of packets from a sender
to a receiver. There are many protocols in literature that address noise
reduction/avoidance during underwater communication. However, they
require localization information of each sensor nodes that itself is a challenging issue. In this paper, the minimum channel noise is considered
and the depth and noise aware routing (DNAR) protocol is proposed
to send the packets reliably from a sender node to a surface sink. In
the DNAR protocol, more energy is assigned to the sensor nodes that
have depth level ≤150 m. Therefore, the sensor nodes that deployed are
nearby to the sink node have more capability of transmission and will
not die quickly. Also, the proposed protocol selects the forwarder candidate that have lowest depth and minimum channel noise at the receiver.
As compared to some existing schemes, the proposed scheme requires no
geographical information of the nodes for data routing. The DNAR protocol is validated by Matlab simulation and compared it with the DBR
scheme. The simulation results show that the DNAR has better results
in-terms of packet delivery ratio (PDR), total energy consumption, and
the network lifetime.

2022 IEEE Zooming Innovation in Consumer Technologies Conference (ZINC), 2022