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Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges

Computer Systems Science & Engineering 2022年第1期40卷 87-112页

作者： Salam Al-E’mari Mohammed Anbar Yousef Sanjalawe selvakumar manickam Iznan Hasbullah National Advanced IPv6 Centre of Excellence(NAv6) Universiti Sains Malaysia11800 USMPenangMalaysia Computer Sciences Department Northern Border University(NBU)9280 NBUAr’arthe Kingdom of Saudi Arabia

Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches.However,the current approaches have challenges in detecting intrusions,which may affect the performance of the overall detection system as well as network performance.For the time being,one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology.Blockchain technology moves in the direction of persistent revolution and change.It is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they are.Recently,blockchain was integrated into intrusion detection systems to enhance their overall performance.Blockchain has also been adopted in health-care,supply chain management,and the Internet of Things.Blockchain uses robust cryptography with private and public keys,and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third party.To explore and highlight the importance of integrating blockchain with intrusion detection systems,this paper provides a comprehensive background of intrusion detection systems and blockchain technology.Furthermore,a comprehensive review of emerging intrusion detection systems based on blockchain technology is presented.Finally,this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology.

关键词： Blockchain intrusiondetectionsystem networksecurity maliciousattacks

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Monitoring Peer-to-Peer Botnets:Requirements,Challenges,and Future Works

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Computers, Materials & Continua 2023年第5期75卷 3375-3398页

作者： Arkan Hammoodi Hasan Kabla Mohammed Anbar selvakumar manickam Alwan Ahmed Abdulrahman Alwan Shankar Karuppayah National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPulau Pinang11800Malaysia

The cyber-criminal compromises end-hosts(bots)to configure a network of bots(botnet).The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as Peer-to-Peer(P2P)networks.The P2P botnets leverage the privileges of the decentralized nature of P2P networks.Consequently,the P2P botnets exploit the resilience of this architecture to be arduous against take-down procedures.Some P2P botnets are smarter to be stealthy in their Commandand-Control mechanisms(C2)and elude the standard discovery mechanisms.Therefore,the other side of this cyberwar is the monitor.The P2P botnet monitoring is an exacting mission because the monitoring must care about many aspects simultaneously.Some aspects pertain to the existing monitoring approaches,some pertain to the nature of P2P networks,and some to counter the botnets,i.e.,the anti-monitoring mechanisms.All these challenges should be considered in P2P botnet monitoring.To begin with,this paper provides an anatomy of P2P botnets.Thereafter,this paper exhaustively reviews the existing monitoring approaches of P2P botnets and thoroughly discusses each to reveal its advantages and disadvantages.In addition,this paper groups the monitoring approaches into three groups:passive,active,and hybrid monitoring approaches.Furthermore,this paper also discusses the functional and non-functional requirements of advanced monitoring.In conclusion,this paper ends by epitomizing the challenges of various aspects and gives future avenues for better monitoring of P2P botnets.

关键词： P2P networks botnet P2P botnet botnet monitoring honeypot crawlers

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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Computer Systems Science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi selvakumar manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration Scheme.IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications.Therefore,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of features.This paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential features.Moreover,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios.The results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)features.The proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Can propensity score matching replace randomized controlled trials?

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World Journal of Methodology 2024年第1期14卷 58-70页

作者： Matthias Yi Quan Liau En Qi Toh Shamir Muhamed Surya Varma selvakumar Vishalkumar Girishchandra Shelat Lee Kong Chian School of Medicine Nanyang Technological UniversitySingapore 308232Singapore Department of General Surgery Tan Tock Seng HospitalSingapore 308433Singapore Surgical Science Training Centre Tan Tock Seng HospitalSingapore 308433Singapore

Randomized controlled trials(RCTs)have long been recognized as the gold standard for establishing causal relationships in clinical research.Despite that,various limitations of RCTs prevent its widespread implementation,ranging from the ethicality of withholding potentially-lifesaving treatment from a group to relatively poor external validity due to stringent inclusion criteria,amongst others.However,with the introduction of propensity score matching(PSM)as a retrospective statistical tool,new frontiers in establishing causation in clinical research were opened up.PSM predicts treatment effects using observational data from existing sources such as registries or electronic health records,to create a matched sample of participants who received or did not receive the intervention based on their propensity scores,which takes into account characteristics such as age,gender and comorbidities.Given its retrospective nature and its use of observational data from existing sources,PSM circumvents the aforementioned ethical issues faced by RCTs.Majority of RCTs exclude elderly,pregnant women and young children;thus,evidence of therapy efficacy is rarely proven by robust clinical research for this population.On the other hand,by matching study patient characteristics to that of the population of interest,including the elderly,pregnant women and young children,PSM allows for generalization of results to the wider population and hence greatly increases the external validity.Instead of replacing RCTs with PSM,the synergistic integration of PSM into RCTs stands to provide better research outcomes with both methods complementing each other.For example,in an RCT investigating the impact of mannitol on outcomes among participants of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial,the baseline characteristics of comorbidities and current medications between treatment and control arms were significantly different despite the randomization protocol.Therefore,PSM was incorporated in its analysis to create sam

关键词： Propensity score matching Randomized controlled trials Randomization Clinical practice Validity Ethics

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An Improved Lifetime and Energy Consumption with Enhanced Clustering in WSNs

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Intelligent Automation & Soft Computing 2023年第2期35卷 1939-1956页

作者： I.Adumbabu K.selvakumar Department of Electronics&Communication Engineering Annamalai UniversityChidambaram608002India Department of Information Technology Annamalai UniversityChidambaram608002TamilnaduIndia

Awireless sensor network(WSN)is made up of sensor nodes that communicate via radio waves in order to conduct sensing functions.In WSN,the location of the base station is critical.Although base stations are fixed,they may move in response to data received from sensor nodes under specific conditions.Clustering is a highly efficient approach of minimising energy use.The issues of extending the life of WSNs and optimising their energy consumption have been addressed in this paper.It has been established that integrating mobile sinks into wireless sensor networks extends their longevity.Thus,this research proposes an optimal clustering and routing technique for optimising the energy usage and lifetime of WSNs.To minimise energy consumption,this research employs movable and stationary sink nodes.The K-Medoid clustering model is used to generate the initial number of nodes in the various clusters.After that,the cluster head is chosen using a hybrid Interval Type-2 Fuzzy technique that takes three aspects into account:residual energy,node centrality,and neighbourhood.A highly efficient backup cluster head(CH)collecting system can provide in significant energy savings while also prolonging the system’s life.Finally,better Reinforcement learning combined with a Genetic algorithm routing protocol is used to ensure effective data delivery.The suggested approach’s efficacy is evaluated in comparison to earlier approaches utilising residual node energy,delay or average delay,packet delivery ratio,throughput,network longevity,average energy consumption,and multiple alive nodes.In experiments,the proposed strategy outperforms existing strategies.

关键词： Fuzzy logic genetic algorithm wireless sensor networks routing

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High-Velocity Projectile Impact Behaviour of Friction Stir Welded AA7075 Thick Plates

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Defence Technology（防务技术） 2023年第11期29卷 153-163页

作者： R.Praveen S.R.Koteswara Rao G.selvakumar R.Damodaram Department of Robotics and Automation Karpaga Vinayaga College of Engineering and TechnologyChengalpattu603308TamilNaduIndia Department of Mechanical Engineering Sri Sivasubramaniya Nadar College of EngineeringChennai603110TamilNaduIndia

In this study, high velocity impact behaviour of friction stir welded AA7075-T651 25 mm thick plates were investigated using a 7.62 mm × 51 mm lead core and 7.62 mm × 39 mm steel core projectiles. Prior to ballistic trails, mechanical and metallurgical properties of friction stir welded AA 7075-T651 25 mm thick plates were studied. Microstructural and hardness studies revealed that friction stir welds constituted three distinct regions namely Weld Nugget(WN), Thermo-Mechanically Affected Zone(TMAZ) and Heat Affected Zone(HAZ). Base Material(BM) and all three weld regions were ballistically tested as per military standard NIJ.0108.01 using lead and steel core bullets at maximum permissible velocities of 830 ± 20 and 700 ± 30 m/s, respectively. It has been found that base material(AA7075-T651)and all three weld regions of 25 mm thick plates were able to resist perforation by both types of projectiles used. However depth of penetration has been found to increase from BM to WN, HAZ and TMAZ for both types of projectiles. In all cases steel core projectiles caused higher depth of penetration compared to those caused by lead core projectiles. TMAZs of the friction stir welds were found to be the weakest zone. The fracture that occurred in the base material was spall fragmentation indicating brittle failure, whereas all zones of friction stir welded AA7075-T651 targets with a front petalling, indicating ductile failure. The post-ballistic tested samples showed no significant change in the microstructure of the BM and WN. On the other hand, TMAZ and HAZ showed severe grain deformation in the direction of projectile penetration, and the formation of adiabatic shear bands(ASB). This work showed that 25 mm thick friction stir welded AA7075-T651 joints responded well to ballistic impact loads, making them a good choice for light combat vehicles.

关键词： Aluminum alloy Thick plate Friction stir welding Ballistic performance Depth of penetration

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Latency Minimization Using an Adaptive Load Balancing Technique in Microservices Applications

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Computer Systems Science & Engineering 2023年第7期46卷 1215-1231页

作者： G.selvakumar L.S.Jayashree S.Arumugam Department of Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Computer Science and Engineering PSG College of TechnologyCoimbatore641004India Department of Computer Science and Engineering Nandha College of EngineeringErode638052India

Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex systems.Microservices Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed independently.This methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,etc.and the advantages;Microservices bring some challenges too.Multiple microservices need to be invoked one by one as a chain.In most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s request.It results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of requests.The communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting time.Experiments were done for both interactive as well as non interactive workloads to test the effectiveness of the solution.The approach has been proved to be very effective in reducing latency in the case of long service chains.

关键词： Microservices load balancing cloud computing latency optimization netflix

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An advanced cost-efficient IoT method for stroke rehabilitation using smart gloves

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Nanotechnology and Precision Engineering 2023年第4期6卷 40-54页

作者： A.Arivarasi D.Thiripurasundari A.Arockia selvakumar Bhuvan Kumaar T.Aghil S.Rahul Ramani Kannan Vellore Institute of Technology ChennaiIndia Universiti Tecknologi Petronas Kuala LumpurMalaysia

Stroke represents a severe,widespread,and widely acknowledged health crisis on both national and international levels.It is one of the most prevalent life-threatening conditions.Despite impressive advances in treating stroke,in addition to a need for effective patient care services,many sufferers still rely solely on physical interventions.The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers.This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist.Gamification methodology is used to encourage patients to become involved in the process of rehabilitation.The device also has sensors that take information and transmit it to an app through an ESP32 connection.This enables physicians to view glove usage information remotely and keep track of an individual patient’s health.Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT.With the robotic glove presented here,the recovery rate is found to be 90.23%over four weeks’duration,which represents a significant improvement compared with existing hospital-based rehabilitation techniques.

关键词： Stroke rehabilitation Smart glove ESP32 AWS cloud

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Local outlier factor and stronger one class classifier based hierarchical model for detection of attacks in network intrusion detection dataset

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Frontiers of Computer Science 2016年第4期10卷 755-766页

作者： Alampallam Ramaswamy VASUDEVAN Subramanian selvakumar CDBR-SSE Lab Department of Computer Science and Engineering National Institute of Technology Tiruchirappalli (NITT) Tiruchirappalli 620015 India

Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted. These rules are used to detect such attacks in future, but in anomaly or outlier detection system, the normal network traffic is modeled. Any deviation from the normal model is deemed to be an outlier/attack. Data mining and machine learning techniques are widely used in offline NIDS. Unsupervised and supervised learning techniques differ the way NIDS dataset is treated. The characteristic features of unsupervised and supervised learning are finding patterns in data, detecting outliers, and determining a learned function for input features, generalizing the data instances respectively. The intuition is that if these two techniques are combined, better performance may be obtained. Hence, in this paper the advantages of unsupervised and supervised techniques are inherited in the proposed hierarchical model and devised into three stages to detect attacks in NIDS dataset. NIDS dataset is clustered using Dirichiet process （DP） clustering based on the underlying data distribution. Iteratively on each cluster, local denser areas are identified using local outlier factor （LOF） which in turn is discretized into four bins of separation based on LOF score. Further, in each bin the normal data instances are modeled using one class classifier （OCC）. A combination of Density Estimation method, Reconstruction method, and Boundary methods are used for OCC model. A product rule combination of the three methods takes into consideration the strengths of each method in building a stronger OCC model. Any deviation from this model is considered as an attack. Experiments are conducted on KDD CUP＇99 and SSENet-2011 datasets. The results show that the proposed model is able to identify attacks with higher detection rate and low false alarms.

关键词： hierarchical model DP clustering LOF Dis-cretizer one class classifier NIDS

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Fatigue crack growth behavior of a 170 mm diameter stainless steel straight pipe subjected to combined torsion and bending load

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Frontiers of Structural and Civil Engineering 2021年第4期15卷 905-913页

作者： selvakumar VEERARAJAN Dakshinamurthy PUKAZHENDHI Palla GANDHI Department of Civil Engineering Taipei University of TechnologyTaipei106-08China Fatigue&Fracture Laboratory CSIR-Structural Engineering Research CentreChennai600113India

In a nuclear powerplant,the rotary equipment,such as a pump directly fitted with hanger in the piping system,experiences torsional and bending loads.Higher crack growth rate occurs because of this torsional load in addition to the bending load.Hence,it is necessary to study the fatigue behavior of piping components under the influence of combined torsional and bending load.In this study,experimental fatigue life evaluation was conducted on a notched stainless steel SA312 Type 304LN straight pipe having an outer diameter of 170 mm.The experimental crack depth was measured using alternating current potential drop technique.The fatigue life of the stainless steel straight pipe was predicted using experiments,Delale and Erdogan method,and area-averaged root mean square-stress intensity factor approach at the deepest and surface points of the notch.Afterward,the fatigue crack growth and crack pattern were discussed.As a result,fatigue crack growth predicted using analytical methods are in good agreement with experimental results.

关键词： fatigue life Delale and Erdogan method RMS-SIF approach stainless steel torsion and bending load fatigue crack growth

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