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International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-9 Issue-45 November-2019
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Paper Title : A survey of IoT security threats and defenses
Author Name : Hassan I. Ahmed, Abdurrahman A. Nasr, Salah Abdel-Mageid and Heba K. Aslan
Abstract :

Internet of Things (IoT) plays a well-known role in the interconnection of the physical and virtual objects for the purpose of exchanging information. IoT environment can connect billions of devices or objects, each one has an ID for identification proof. The IoT system is considered one of the most important technologies in recent decades, and the focus of attention in many fields including healthcare, industry, agriculture, military applications, and space science. Thus, it is more attractive for cyber-attacks. The IoT requires multi-dimensional security solutions such as confidentiality, integrity, and authentication services. In this paper, we address different security challenges, threats, and defenses in the layers of IoT systems. It is known that the IoT system architecture consists of three layers: physical/sensor layer, network layer, and application layer. To be comprehensive and to facilitate comparative methods, the security problems of each layer separately and the suggested solutions have been analyzed. Moreover, the challenges of the IoT especially big data and also the evaluation strategies of the IoT system and their effects on the security operations have been evaluated.
Keywords : Internet of things (IoT), Radio frequency identification (RFID), Big data analytics, Distributed denial of services (DDoS).
Cite this article : Ahmed HI, Nasr AA, Abdel-Mageid S, Aslan HK. A survey of IoT security threats and defenses. International Journal of Advanced Computer Research. 2019; 9(45):325-350. DOI:10.19101/IJACR.2019.940088.
References :
[1]Tsai CW, Lai CF, Vasilakos AV. Future internet of things: open issues and challenges. Wireless Networks. 2014; 20(8):2201-17.
[Crossref] [Google Scholar]
[2]https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide. Accessed 27 December 2018.
[3]http://www.cisco.com/web/about/ac79/index.html. Accessed 13 March 2018.
[4]Jing Q, Vasilakos AV, Wan J, Lu J, Qiu D. Security of the internet of things: perspectives and challenges. Wireless Networks. 2014; 20(8):2481-501.
[Crossref] [Google Scholar]
[5]Sonar K, Upadhyay H. A survey: DDOS attack on internet of things. International Journal of Engineering Research and Development. 2014; 10(11):58-63.
[Google Scholar]
[6]Suo H, Wan J, Zou C, Liu J. Security in the internet of things: a review. In international conference on computer science and electronics engineering 2012 (pp. 648-51). IEEE.
[Crossref] [Google Scholar]
[7]Alansari Z, Anuar NB, Kamsin A, Soomro S, Belgaum MR, Miraz MH, et al. Challenges of internet of things and big data integration. In international conference for emerging technologies in computing 2018 (pp. 47-55). Springer, Cham.
[Crossref] [Google Scholar]
[8]Weber RH. Internet of things–new security and privacy challenges. Computer Law & Security Review. 2010; 26(1):23-30.
[Crossref] [Google Scholar]
[9]http://www.centrenational-rfid.com/introduction-to-the-rfid-article-15-gb-ruid-202.html. Accessed 17 April 2018.
[10]Liu Y, Zhou G. Key technologies and applications of internet of things. In fifth international conference on intelligent computation technology and automation 2012 (pp. 197-200). IEEE.
[Crossref] [Google Scholar]
[11]Oracevic A, Dilek S, Ozdemir S. Security in internet of things: a survey. In international symposium on networks, computers and communications (ISNCC) 2017 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[12]Li S, Tryfonas T and Li H. The internet of things: a security point of view. Internet Research. 2016; 26(2):337-59.
[Crossref] [Google Scholar]
[13]Yousuf T, Mahmoud R, Aloul F, Zualkernan I. Internet of things (IoT) security: current status, challenges and countermeasures. International Journal for Information Security Research. 2015; 5(4):608-16.
[Google Scholar]
[14]Cai H, Da Xu L, Xu B, Xie C, Qin S, Jiang L. IoT-based configurable information service platform for product lifecycle management. IEEE Transactions on Industrial Informatics. 2014; 10(2):1558-67.
[Crossref] [Google Scholar]
[15]Atzori L, Iera A, Morabito G. The internet of things: a survey. Computer Networks. 2010; 54(15):2787-805.
[Crossref] [Google Scholar]
[16]Trappe W, Howard R, Moore RS. Low-energy security: limits and opportunities in the internet of things. IEEE Security & Privacy. 2015; 13(1):14-21.
[Crossref] [Google Scholar]
[17]Lin J, Yu W, Zhang N, Yang X, Zhang H, Zhao W. A survey on internet of things: architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal. 2017; 4(5):1125-42.
[Crossref] [Google Scholar]
[18]Shafagh H, Hithnawi A, Droescher A, Duquennoy S, Hu W. Talos: encrypted query processing for the internet of things. In proceedings of the ACM conference on embedded networked sensor systems 2015 (pp. 197-210). ACM.
[Crossref] [Google Scholar]
[19]Stephen E. Internet protocol, version 6 (IPv6) specification. RFC2460. 1998.
[Google Scholar]
[20]Kushalnagar N, Montenegro G, Schumacher C. IPv6 over low-power wireless personal area networks (6LoWPANs): overview, assumptions, problem statement, and goals.2007.
[Google Scholar]
[21]Ning H, Liu H, Yang LT. Cyberentity security in the internet of things. Computer. 2013; 46(4):46-53.
[Crossref] [Google Scholar]
[22]Yang Y, Wu L, Yin G, Li L, Zhao H. A survey on security and privacy issues in Internet-of-Things. IEEE Internet of Things Journal. 2017; 4(5):1250-8.
[Crossref] [Google Scholar]
[23]http://www.internet-of-things-research.eu/. Accessed 17 April 2018.
[24]Singh S, Singh N. Internet of things (IoT): security challenges, business opportunities & reference architecture for e-commerce. In international conference on green computing and internet of things (ICGCIoT) 2015 (pp. 1577-81). IEEE.
[Crossref] [Google Scholar]
[25]Borgohain T, Kumar U, Sanyal S. Survey of security and privacy issues of internet of things. arXiv preprint arXiv:1501.02211. 2015.
[Google Scholar]
[26]Gavrilut D, Cimpoesu M, Anton D, Ciortuz L. Malware detection using perceptrons and support vector machines. In computation world: future computing, service computation, cognitive, adaptive, content, patterns 2009 (pp. 283-8). IEEE.
[Crossref] [Google Scholar]
[27]Kolter JZ, Maloof MA. Learning to detect and classify malicious executables in the wild. Journal of Machine Learning Research. 2006:2721-44.
[Crossref] [Google Scholar]
[28]More SS, Gaikwad PP. Trust-based voting method for efficient malware detection. Procedia Computer Science. 2016; 79:657-67.
[Crossref] [Google Scholar]
[29]Loukas G, Öke G. Protection against denial of service attacks: a survey. The Computer Journal. 2010; 53(7):1020-37.
[Crossref] [Google Scholar]
[30]Chandola V, Banerjee A, Kumar V. Anomaly detection: a survey. ACM Computing Surveys. 2009; 41(3).
[Crossref] [Google Scholar]
[31]Medaglia CM, Serbanati A. An overview of privacy and security issues in the internet of things. In the internet of things 2010 (pp. 389-95). Springer, New York, NY.
[Crossref] [Google Scholar]
[32]Bugenhagen MK, Wiley WL. Pin-hole firewall for communicating data packets on a packet network. United States Patent US 8,015,294. 2011.
[Google Scholar]
[33]Shin Y, Meneely A, Williams L, Osborne JA. Evaluating complexity, code churn, and developer activity metrics as indicators of software vulnerabilities. IEEE Transactions on Software Engineering. 2010; 37(6):772-87.
[Crossref] [Google Scholar]
[34]Abomhara M. Cyber security and the internet of things: vulnerabilities, threats, intruders and attacks. Journal of Cyber Security and Mobility. 2015; 4(1):65-88.
[Crossref] [Google Scholar]
[35]Zhou W, Jia Y, Peng A, Zhang Y, Liu P. The effect of IoT new features on security and privacy: new threats, existing solutions, and challenges yet to be solved. IEEE Internet of Things Journal. 2018; 6(2):1606-16.
[Crossref] [Google Scholar]
[36]Guo L, Dong M, Ota K, Li Q, Ye T, Wu J, et al. A secure mechanism for big data collection in large scale internet of vehicle. IEEE Internet of Things Journal. 2017; 4(2):601-10.
[Crossref] [Google Scholar]
[37]https://www.veracode.com/security/buffer-overflow. Accessed 26 May 2018.
[38]https://resources.altium.com/pcb-design-blog/internet-of-things-security-vulnerabilities-all-about-buffer-overflow. Accessed 26 May 2018.
[39]https://www.techrepublic.com/blog/it-security/what-is-cross-site-scripting. Accessed 29 May 2018.
[40]Millar S. Network security issues in the Internet of Things (IoT). Queens University Belfast. 2016.
[Google Scholar]
[41]Uke SN, Mahajan AR, Thool RC. UML modeling of physical and data link layer security attacks in WSN. International Journal of Computer Applications. 2013; 70(11).
[Crossref] [Google Scholar]
[42]Ahemd MM, Shah MA, Wahid A. IoT security: a layered approach for attacks & defenses. In international conference on communication technologies 2017 (pp. 104-10). IEEE.
[Crossref] [Google Scholar]
[43]Pongle P, Chavan G. A survey: attacks on RPL and 6LoWPAN in IoT. In international conference on pervasive computing 2015 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[44]Sharmila S, Umamaheswari G. Detection of sinkhole attack in wireless sensor networks using message digest algorithms. In international conference on process automation, control and computing 2011 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[45]Stephen R, Arockiam L. Intrusion detection system to detect sinkhole attack on RPL protocol in internet of things. International Journal of Electrical Electronics and Computer Science. 2017; 4(4):16-20.
[Google Scholar]
[46]Kaur P, Gurm JS. Detect and prevent HELLO FLOOD attack using centralized technique in WSN. International Journal of Computer Science & Engineering Technology. 2016;7(8):379-81.
[Google Scholar]
[47]Magotra S, Kumar K. Detection of HELLO flood attack on LEACH protocol. In international advance computing conference 2014 (pp. 193-8). IEEE.
[Crossref] [Google Scholar]
[48]Aljumah A, Ahanger TA. Futuristic method to detect and prevent blackhole attack in wireless sensor networks. International Journal of Computer Science and Network Security. 2017; 17(2):194-201.
[Google Scholar]
[49]Zandiyan S, Fotohi R, Koravand M. P-method: improving AODV routing protocol for against network layer attacks in mobile ad-hoc networks. International Journal of Computer Science and Information Security. 2016; 14(6):95-103.
[Google Scholar]
[50]Nisha SK, Arora SK. Analysis of black hole effect and prevention through IDs in manet. American Journal of Engineering Research. 2013; 2(10):214-20.
[Google Scholar]
[51]Cekerevac Z, Dvorak Z, Prigoda L, Cekerevac P. Internet of things and the man-in-the-middle attacks–security and economic risks. MEST Journal. 2017; 5(2):15-25.
[Google Scholar]
[52]https://www.globalsign.com/en/blog/man-in-the-middle-attacks-iot/. Accessed 04 July 2018.
[53]Balachandran N, Sanyal S. A review of techniques to mitigate sybil attacks. IJANA. 2012.
[Google Scholar]
[54]Dhamodharan US, Vayanaperumal R. Detecting and preventing sybil attacks in wireless sensor networks using message authentication and passing method. The Scientific World Journal. 2015.
[Google Scholar]
[55]Li H, Chen Y, He Z. The survey of RFID attacks and defenses. In international conference on wireless communications, networking and mobile computing 2012 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[56]Raymond DR, Midkiff SF. Denial-of-service in wireless sensor networks: attacks and defenses. IEEE Pervasive Computing. 2008; 7(1):74-81.
[Crossref] [Google Scholar]
[57]https://www.spamlaws.com/jamming-attacks.html. Accessed 17 July 2018.
[58]Panyim K, Hayajneh T, Krishnamurthy P, Tipper D. On limited-range strategic/random jamming attacks in wireless ad hoc networks. In conference on local computer networks 2009 (pp. 922-9). IEEE.
[Crossref] [Google Scholar]
[59]Xu W, Ma K, Trappe W, Zhang Y. Jamming sensor networks: attack and defense strategies. IEEE Network. 2006; 20(3):41-7.
[Crossref] [Google Scholar]
[60]Tang X, Ren P, Han Z. Jamming mitigation via hierarchical security game for IoT communications. IEEE Access. 2018; 6:5766-79.
[Crossref] [Google Scholar]
[61]Millar S. Network security issues in the Internet of Things (IoT). Queen s University Belfast. 2016.
[Google Scholar]
[62]Sunitha K, Chandrakanth H. A survey on security attacks in wireless sensor network. International Journal of Engineering Research and Applications. 2012; 2(4):1684-91.
[Google Scholar]
[63]Liu AX, Bailey LA. PAP: a privacy and authentication protocol for passive RFID tags. Computer Communications. 2009; 32(7-10):1194-9.
[Crossref] [Google Scholar]
[64]Tehranipoor M, Koushanfar F. A survey of hardware trojan taxonomy and detection. IEEE Design & Test of Computers. 2010; 27(1):10-25.
[Crossref] [Google Scholar]
[65]Deogirikar J, Vidhate A. Security attacks in IoT: a survey. In international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) 2017 (pp. 32-7). IEEE.
[Crossref] [Google Scholar]
[66]https://www.guru99.com/learn-everything-about-trojans-viruses-and-worms.html. Accessed 13 August 2018.
[67]Yatagai T, Isohara T, Sasase I. Detection of HTTP-GET flood attack based on analysis of page access behavior. In pacific RIM conference on communications, computers and signal processing 2007 (pp. 232-5). IEEE.
[Crossref] [Google Scholar]
[68]Xie Y, Yu SZ. A large-scale hidden semi-Markov model for anomaly detection on user browsing behaviors. IEEE/ACM Transactions on Networking. 2008; 17(1):54-65.
[Crossref] [Google Scholar]
[69]Devi SR, Yogesh P. Detection of application layer DDoS attacks using information theory based metrics. CS & IT-CSCP. 2012; 10:217-23.
[Crossref] [Google Scholar]
[70]Ye C, Zheng K, She C. Application layer DDoS detection using clustering analysis. In proceedings of international conference on computer science and network technology 2012 (pp. 1038-41). IEEE.
[Crossref] [Google Scholar]
[71]Li P, Cui B. A comparative study on software vulnerability static analysis techniques and tools. In international conference on information theory and information security 2010 (pp. 521-4). IEEE.
[Crossref] [Google Scholar]
[72]Amankwah R, Kudjo PK, Antwi SY. Evaluation of software vulnerability detection methods and tools: a review. International Journal of Computer Applications. 2017; 169(8):22-7.
[Google Scholar]
[73]Freitez WR, Mammar A, Cavalli AR. Software vulnerabilities, prevention and detection methods: a review. SEC-MDA 2009 (pp. 1-11).
[Google Scholar]
[74]https://www.cso.com.au/article/575407/internet-things-iot-threats-countermeasures/. Accessed 16 September 2018.
[75]Teixeira FA, Pereira FM, Wong HC, Nogueira JM, Oliveira LB. SIoT: securing internet of things through distributed systems analysis. Future Generation Computer Systems. 2019; 92:1172-86.
[Google Scholar]
[76]Chun S, Jing C, ChangZhen H, JingFeng X, Hao W, Raphael M. A XSS attack detection method based on skip list. International Journal of Security and its Applications. 2008; 10(5):95-106.
[Crossref] [Google Scholar]
[77]Khin SL. Mitigating SQL injection and cross site scripting vulnerabilities using program analysis and data mining techniques (Doctoral Dissertation). 2013.
[Google Scholar]
[78]Athanasopoulos E, Krithinakis A, Markatos EP. Hunting cross-site scripting attacks in the network. In proceedings of the workshop on web 2010 (pp. 1-8).
[Google Scholar]
[79]Caselli M, Kargl F. A security assessment methodology for critical infrastructures. In international conference on critical information infrastructures security 2014 (pp. 332-43). Springer, Cham.
[Crossref] [Google Scholar]
[80]Wurzinger P, Platzer C, Ludl C, Kirda E, Kruegel C. SWAP: mitigating XSS attacks using a reverse proxy. In proceedings of the ICSE workshop on software engineering for secure systems 2009 (pp. 33-9). IEEE Computer Society.
[Crossref] [Google Scholar]
[81]Chakravarty S. Traffic analysis attacks and defenses in low latency anonymous communication (Doctoral Dissertation, Columbia University). 2014.
[Google Scholar]
[82]Devi PK, Manavalan R. Spoofing attack detection and localization in wireless sensor network: a review. International Journal of Computer Science & Engineering Technology. 2014; 5(9): 877–86, 2014.
[Google Scholar]
[83]Cervantes C, Poplade D, Nogueira M, Santos A. Detection of sinkhole attacks for supporting secure routing on 6LoWPAN for internet of things. In international symposium on integrated network management 2015 (pp. 606-11). IEEE.
[Crossref] [Google Scholar]
[84]Raza S, Wallgren L, Voigt T. SVELTE: real-time intrusion detection in the internet of things. Ad HOC Networks. 2013; 11(8):2661-74.
[Crossref] [Google Scholar]
[85]Dvir A, Buttyan L. VeRA-version number and rank authentication in RPL. In international conference on mobile Ad-Hoc and sensor systems 2011 (pp. 709-14). IEEE.
[Crossref] [Google Scholar]
[86]Le A, Loo J, Chai K, Aiash M. A specification-based IDS for detecting attacks on RPL-based network topology. Information. 2016; 7(2):1-19.
[Crossref] [Google Scholar]
[87]Singh VP, Ukey AS, Jain S. Signal strength based hello flood attack detection and prevention in wireless sensor networks. International Journal of Computer Applications. 2013; 62(15):1-6.
[Google Scholar]
[88]Khosravi H, Azmi R, Sharghi M. Adaptive detection of hello flood attack in wireless sensor networks. International Journal of Future Computer and Communication. 2016; 5(2):99-103.
[Crossref] [Google Scholar]
[89]Sherasiya T, Upadhyay H. Intrusion detection system for internet of things. International Journal of Advance Research and Innovative Ideas in Education. 2016; 2(3):2244-9.
[Google Scholar]
[90]Raj PN, Swadas PB. Dpraodv: a dyanamic learning system against blackhole attack in AODV based MANET. International Journal of Computer Science. 2009; 2:54-9.
[Google Scholar]
[91]Baghel L, Mishra P, Samvatsar M, Singh U. Detection of black hole attack in mobile ad hoc network using adaptive approach. In international conference of electronics, communication and aerospace technology 2017 (pp. 626-30). IEEE.
[Crossref] [Google Scholar]
[92]Panos C, Ntantogian C, Malliaros S, Xenakis C. Analyzing, quantifying, and detecting the blackhole attack in infrastructure-less networks. Computer Networks. 2017; 113:94-110.
[Crossref] [Google Scholar]
[93]Chauhan RK. An assessment based approach to detect black hole attack in MANET. In international conference on computing, communication & automation 2015 (pp. 552-7). IEEE.
[Crossref] [Google Scholar]
[94]Lee J, Tu C, Jung S. Man-in-the-middle attacks detection scheme on smartphone using 3G network. In the fourth international conference on evolving internet 2012 (pp. 65-70).
[Google Scholar]
[95]Zhang K, Liang X, Lu R, Shen X. Sybil attacks and their defenses in the internet of things. IEEE Internet of Things Journal. 2014; 1(5):372-83.
[Crossref] [Google Scholar]
[96]Evangelista D, Mezghani F, Nogueira M, Santos A. Evaluation of sybil attack detection approaches in the internet of things content dissemination. In wireless days 2016 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[97]Shaikh M, Syed AH. A survey on jamming attacks, detection and defending strategies in wireless sensor networks. International Journal of Research in Engineering and Technology. 2014; 3(3): 558-61.
[98]King A, Brown J, Roedig U. DCCA: differentiating clear channel assessment for improved 802.11/802.15. 4 coexistence. In international conference on wireless and mobile computing, networking and communications 2014 (pp. 45-50). IEEE.
[Crossref] [Google Scholar]
[99]Sparber T, Boano CA, Kanhere SS, Römer K. Mitigating radio interference in large IoT networks through dynamic CCA adjustment. Open Journal of Internet of Things. 2017; 3(1):103-13.
[Google Scholar]
[100]Elngar AA. IoT-based efficient tamper detection mechanism for healthcare application. IJ Network Security. 2018; 20(3):489-95.
[Crossref] [Google Scholar]
[101]Aman MN, Javed K, Sikdar B, Chua KC. Detecting data tampering attacks in synchrophasor networks using time hopping. In PES innovative smart grid technologies conference Europe (ISGT-Europe) 2016 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[102]Sei Y, Honiden S. Distributed detection of node replication attacks resilient to many compromised nodes in wireless sensor networks. In proceedings of the international conference on wireless internet 2008.
[Google Scholar]
[103]Khan WZ, Aalsalem MY, Saad MN, Xiang Y. Detection and mitigation of node replication attacks in wireless sensor networks: a survey. International Journal of Distributed Sensor Networks. 2013; 9(5):1-22.
[Crossref] [Google Scholar]
[104]Ku Z, Hu Z. Camouflage attack detection based on KMOD kernel function. In international conference on computer science and software engineering 2008 (pp. 1031-4). IEEE.
[Crossref] [Google Scholar]
[105]Gu Z, Pei K, Wang Q, Si L, Zhang X, Xu D. Leaps: detecting camouflaged attacks with statistical learning guided by program analysis. In international conference on dependable systems and networks 2015 (pp. 57-68). IEEE.
[Crossref] [Google Scholar]
[106]Yimin G, Shundong L, Jiawei D, Sufang Z. Deterministic cloned tag detection protocol for anonymous radio-frequency identification systems. IET Information Security. 2016; 10(1):28-32.
[Crossref] [Google Scholar]
[107]Bu K, Xu M, Liu X, Luo J, Zhang S, Weng M. Deterministic detection of cloning attacks for anonymous RFID systems. IEEE Transactions on Industrial Informatics. 2015; 11(6):1255-66.
[Crossref] [Google Scholar]
[108]Bu K, Liu X, Luo J, Xiao B, Wei G. Unreconciled collisions uncover cloning attacks in anonymous RFID systems. IEEE Transactions on Information Forensics and Security. 2013; 8(3):429-39.
[Crossref] [Google Scholar]
[109]Huang J, Li X, Xing CC, Wang W, Hua K, Guo S. DTD: a novel double-track approach to clone detection for RFID-enabled supply chains. IEEE Transactions on Emerging Topics in Computing. 2015; 5(1):134-40.
[Crossref] [Google Scholar]
[110]Sui Q, Wu Z, Li J, Li S. A detection method of hardware Trojan based on two-dimension calibration. In international conference on computer and communications 2016 (pp. 2795-9). IEEE.
[Crossref] [Google Scholar]
[111]Kulkarni A, Pino Y, Mohsenin T. SVM-based real-time hardware Trojan detection for many-core platform. In international symposium on quality electronic design 2016 (pp. 362-7). IEEE.
[Crossref] [Google Scholar]
[112]Hasegawa K, Yanagisawa M, Togawa N. Trojan-feature extraction at gate-level netlists and its application to hardware-Trojan detection using random forest classifier. In international symposium on circuits and systems 2017 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[113]Kasinathan P, Pastrone C, Spirito MA, Vinkovits M. Denial-of-service detection in 6LoWPAN based Internet of Things. In international conference on wireless and mobile computing, networking and communications 2013 (pp. 600-7). IEEE.
[Crossref] [Google Scholar]
[114]Amaral JP, Oliveira LM, Rodrigues JJ, Han G, Shu L. Policy and network-based intrusion detection system for IPv6-enabled wireless sensor networks. In international conference on communications 2014 (pp. 1796-801). IEEE.
[Crossref] [Google Scholar]
[115]Pongle P, Chavan G. Real time intrusion and wormhole attack detection in internet of things. International Journal of Computer Applications. 2015; 121(9):1-9.
[Google Scholar]
[116]Brown J, Du X. Detection of selective forwarding attacks in heterogeneous sensor networks. In international conference on communications 2008 (pp. 1583-7). IEEE.
[Crossref] [Google Scholar]
[117]Ghorbani HR, Ahmadzadegan MH. Security challenges in internet of things: survey. In conference on wireless sensors 2017 (pp. 1-6). IEEE.
[Crossref] [Google Scholar]
[118]Marjani M, Nasaruddin F, Gani A, Karim A, Hashem IA, Siddiqa A, et al. Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access. 2017; 5:5247-61.
[Crossref] [Google Scholar]
[119]Kumar MP, Santhoshkumar SP, Gowdhaman T, Shajahaan SS. A survey on IoT performances in big data. International Journal of Computer Science and Mobile Computing. 2017; 6(10):26-34.
[Google Scholar]
[120]https://azure.microsoft.com/en-us/overview/iot/?site=mscom_iot. Accessed 13 June 2018.
[121]Kumar G. Evaluation metrics for intrusion detection systems-a study. Evaluation. 2014; 2(11):11-7.
[Google Scholar]