survey

A Systematic Review of IoT Security: Research Potential, Challenges, and Future Directions

Authors:

Srinivas SampalliAuthors Info & Claims

ACM Computing Surveys, Volume 56, Issue 5

Article No.: 111, Pages 1 - 40

https://doi.org/10.1145/3625094

Published: 25 November 2023 Publication History

Abstract

The Internet of Things (IoT) encompasses a network of physical objects embedded with sensors, software, and data processing technologies that can establish connections and exchange data with other devices and systems via the Internet. IoT devices are incorporated into various products, ranging from ordinary household items to complex industrial appliances. Despite the increasing demand for IoT, security concerns have impeded its development. This article systematically reviews IoT security research, focusing on vulnerabilities, challenges, technologies, and future directions. It surveys 171 recent publications in the field, providing a comprehensive discussion on the development status, challenges, and solutions in IoT. The article outlines IoT architecture patterns and typical features, evaluates existing limitations, and explores strategies for enhancing IoT security. Additionally, the article delves into known IoT attacks and discusses the security countermeasures and mechanisms to address these challenges. It explores the functional requirements of IoT security and explores related technologies and standards. Finally, the article discusses potential future research directions in IoT security.

References

[1]

S. Narang, T. Nalwa, T. Choudhury, and N. Kashyap. 2019. An efficient method for security measurement in internet of things. In International Conference on Communication, Computing and Internet of Things. 319–323. DOI:

[2]

K. Shafique, B. A. Khawaja, F. Sabir, S. Qazi, and M. Mustaqim. 2020. Internet of things (IoT) for next-generation smart systems: A review of current challenges, future trends and prospects for emerging 5G-IoT scenarios. IEEE Access 8 (2020), 23022–23040. DOI:

[3]

C. Wheelus and X. Zhu. 2020. IoT network security: Threats, risks, and a data-driven defense framework. Internet Things 1, 2 (2020), 259–285. DOI:

[4]

Somayya Madakam, R. Ramaswamy, and Siddharth Tripathi. 2015. Internet of things (IoT): A literature review. J. Comput. Commun. 03, 05 (2015), 164–173. DOI:

[5]

J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami. 2013. Internet of things (IoT): A vision, architectural elements, and future directions. Fut. Gen. Comput. Syst. 29, 7 (2013), 1645–1660. DOI:

Digital Library

[6]

M. binti Mohamad Noor and W. H. Hassan. 2019. Current research on internet of things (IoT) security: A survey. Comput. Netw. 148 (2019), 283–294. DOI:

[7]

M. M. Sadeeq, N. M. Abdulkareem, S. R. M. Zeebaree, D. M. Ahmed, A. S. Sami, and R. R. Zebari. 2021. IoT and cloud computing issues, challenges and opportunities: A review. Qubahan Acad. J. 1, 2 (2021), 1–7. DOI:

[8]

L. Yao, X. Wang, Q. Z. Sheng, S. Dustdar, and S. Zhang. 2019. Recommendations on the internet of things: Requirements, challenges, and directions. IEEE Internet Comput. 23, 3 (2019), 46–54. DOI:

[9]

A. A. A. Sen and M. Yamin. 2020. Advantages of using fog in IoT applications. Int. J. Inf. Technol. 13, 3 (2020), 829–837. DOI:

[10]

A. Tiwary, M. Mahato, A. Chidar, M. Kumar Chandrol, M. Shrivastava, and M. Tripathi. 2018. View of internet of things (IoT): Research, architectures and applications. Int. J. Fut. Revolut. Comput. Sci. Commun. Eng. 4, 3 (2018), 23–27.

[11]

J. Xu and W. Lu. Smart construction from head to toe: A closed-loop lifecycle management system based on IoT. Construction Research Congress 2018. DOI:

[12]

F. Firouzi and B. Farahani. 2020. Architecting IoT cloud. Intell. Internet Things (2020), 173–241. DOI:

[13]

M. A. Obaidat, S. Obeidat, J. Holst, A. Al Hayajneh, and J. Brown. 2020. A comprehensive and systematic survey on the internet of things: Security and privacy challenges, security frameworks, enabling technologies, threats, vulnerabilities and countermeasures. Comput. 9, 2 (2020), 44. DOI:

[14]

H. Wu, H. Han, X. Wang, and S. Sun. 2020. Research on artificial intelligence enhancing internet of things security: A survey. IEEE Access 8 (2020), 153826–153848. DOI:

[15]

B. K. Mohanta, D. Jena, U. Satapathy, and S. Patnaik. 2020. Survey on IoT security: Challenges and solution using machine learning, artificial intelligence and blockchain technology. Internet Things 11 (2020), 100227. DOI:

[16]

T. Alladi, V. Chamola, B. Sikdar, and K. K. R. Choo. 2020. Consumer IoT: Security vulnerability case studies and solutions. IEEE Consum. Electron. Mag. 9, 2 (2020), 17–25. DOI:

[17]

H. Mrabet, S. Belguith, A. Alhomoud, and A. Jemai. 2020. A survey of IoT security based on a layered architecture of sensing and data analysis. Sensors 20, 13 (2020), 3625. DOI:

[18]

C. C. Sobin. 2020. A survey on architecture, protocols and challenges in IoT. Wirel. Pers. Commun. 112, 3 (2020), 1383–1429. DOI:

Digital Library

[19]

R. Patnaik, N. Padhy, and K. Srujan Raju. 2021. A systematic survey on IoT security issues, vulnerability and open challenges. Adv. Intell. Syst. Comput. 1171 (2021), 723–730. DOI:

[20]

F. A. Alaba, M. Othman, I. A. T. Hashem, and F. Alotaibi. 2017. Internet of things security: A survey. J. Netw. Comput. Appl. 88 (2017), 10–28. DOI:

Digital Library

[21]

X. Liang and Y. Kim. 2021. A survey on security attacks and solutions in the IoT network. In IEEE 11th Annual Computing and Communications Workshop and Conference. 853–859. DOI:

[22]

V. Hassija, V. Chamola, V. Saxena, D. Jain, P. Goyal, and B. Sikdar. 2019. A survey on IoT security: Application areas, security threats, and solution architectures. IEEE Access 7 (2019), 82721–82743. DOI:

[23]

N. Neshenko, E. Bou-Harb, J. Crichigno, G. Kaddoum, and N. Ghani. 2019. Demystifying IoT security: An exhaustive survey on IoT vulnerabilities and a first empirical look on internet-scale IoT exploitations. IEEE Commun. Surv. Tutor. 21, 3 (2019), 2702–2733. DOI:

[24]

A. A. Abbood, Q. M. Shallal, and M. A. Fadhel. 2020. Internet of things (IoT): A technology review, security issues, threats, and open challenges. Indones. J. Electr. Eng. Comput. Sci. 20, 3 (2020), 1685–1692. DOI:

[25]

W. Iqbal, H. Abbas, M. Daneshmand, B. Rauf, and Y. Abbas. 2020. An in-depth analysis of IoT security requirements, challenges and their countermeasures via software defined security. IEEE Internet Things J. 1–1. DOI:

[26]

S. N. Swamy and S. R. Kota. 2020. An empirical study on system level aspects of internet of things (IoT). IEEE Access 8 (2020), 188082–188134. DOI:

[27]

L. Boyanov, V. Kisimov, and Y. Christov. 2020. Evaluating IoT reference architecture. In 2020 International Conference Automatics and Informatics (ICAI). DOI:

[28]

A. E. Bouaouad, A. Cherradi, S. Assoul, and N. Souissi. 2020. The key layers of IoT architecture. In 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech). DOI:

[29]

A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash. 2015. Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17, 4 (2015), 2347–2376. DOI:

Digital Library

[30]

M. Lombardi, F. Pascale, and D. Santaniello. 2021. Internet of things: A general overview between architectures, protocols and applications. Inf. 2021 12, 2 (2021), 87. DOI:

[31]

S. Al-Sarawi, M. Anbar, K. Alieyan, and M. Alzubaidi. 2017. Internet of things (IoT) communication protocols: Review. In 2017 8th International Conference on Information Technology (ICIT). 685–690. DOI:

[32]

R. Gunasagaran, L. M. Kamarudin, and A. Zakaria. 2018. Embedded device free passive (EDfP) system: Effect of WiFi protocols. In 2018 IEEE Student Conference on Research and Development (SCOReD). DOI:

[33]

K. H. Chang. 2014. Bluetooth: A viable solution for IoT?. IEEE Wirel. Commun 21, 6 (2014), 6–7. DOI:

[34]

A. Triantafyllou, P. Sarigiannidis, and T. D. Lagkas. 2018. Network protocols, schemes, and mechanisms for internet of things (IoT): Features, open challenges, and trends. Wirel. Commun. Mob. Comput (2018). DOI:

Digital Library

[35]

X. Jia, Q. Feng, T. Fan, and Q. Lei. 2012. RFID technology and its applications in Internet of Things (IoT). In 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). 1282–1285. DOI:

[36]

Y. Li, Y. Yang, X. Yu, T. Yang, L. Dong, and W. Wang. 2020. IoT-APIScanner: Detecting API unauthorized access vulnerabilities of IoT platform. In 2020 29th International Conference on Computer Communications and Networks (ICCCN). DOI:

[37]

“Hacker tries to poison water supply of Florida city - BBC News.”. Retrieved from: https://www.bbc.com/news/world-us-canada-55989843

[38]

B. Li, R. Ye, G. Gu, R. Liang, W. Liu, and K. Cai. 2020. A detection mechanism on malicious nodes in IoT. Comput. Commun 151 (2020), 51–59. DOI:

Digital Library

[39]

M. A. Khatun, N. Chowdhury, and M. N. Uddin. 2019. Malicious nodes detection based on artificial neural network in IoT environments. In 2019 22nd International Conference on Computer and Information Technology (ICCIT). DOI:

[40]

N. Ruminot-Ahumada, C. Valencia-Cordero, and R. Abarzua-Ortiz. 2021. Side channel attack countermeasure for low power devices with AES encryption. In 2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA). DOI:

[41]

M. Khan and Y. Chen. 2021. A randomized switched-mode voltage regulation system for IoT edge devices to defend against power analysis based side channel attacks; A randomized switched-mode voltage regulation system for IoT edge devices to defend against power analysis based side channel attacks. In 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) DOI:

[42]

N. Živković and A. T. Sarić. 2018. Detection of false data injection attacks using unscented Kalman filter. J. Mod. Power Syst. Clean Energy 6, 5 (2018), 847–859. DOI:

[43]

Meng Zhang, Chao Shen, Ning He, SiCong Han, Qi Li, Qian Wang, and XiaoHong Guan. 2019. False data injection attacks against smart gird state estimation: Construction, detection and defense. Sci. China Technol. Sci 62, 12 (2019), 2077–2087. DOI:

[44]

K. Khanna, B. K. Panigrahi, and A. Joshi. 2020. Priority-based protection against the malicious data injection attacks on state estimation. IEEE Syst. J. 14, 2 (2020), 1945–1952. DOI:

[45]

A. Banerjee and S. P. Maity. 2020. Cognitive radio networks with energy harvesting and eavesdropping-emulation resilience. In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS). 873–875. DOI:

[46]

B. Ahuja, D. Mishra, and R. Bose. 2020. Optimal green hybrid attacks in secure IoT. IEEE Wirel. Commun. Lett 9, 4 (2020), 457–460. DOI:

[47]

P. Shorubiga and T. Kartheeswaran. 2020. Model for mitigating passive eavesdropping attack in IoT. University of Jaffna.

[48]

S. R. Rajendran, N. Devi, and M. Jayakumar. 2022. A node reduction technique for trojan detection and diagnosis in IoT hardware devices. Internet Things 43–64. DOI:

[49]

H. Mohammed, T. A. Odetola, S. R. Hasan, S. Stissi, I. Garlin, and F. Awwad. 2019. (HIADIoT): Hardware intrinsic attack detection in internet of things; Leveraging power profiling. In 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). 852–855. DOI:

[50]

H. Mohammed, S. R. Hasan, and F. Awwad. 2020. Fusion-on-field security and privacy preservation for IoT edge devices: Concurrent defense against multiple types of hardware trojan attacks. IEEE Access 8 (2020), 36847–36862. DOI:

[51]

R. Smith, D. Palin, P. P. Ioulianou, V. G. Vassilakis, and S. F. Shahandashti. 2020. Battery draining attacks against edge computing nodes in IoT networks. Taylor & Francisin Cyber-Physical Systems, 96–116. DOI:

[52]

Amjad Alsirhani, Muhammad Ali Khan, Abdullah Alomari, Sauda Maryam, Aiman Younas, Muddesar Iqbal, Muhammad Hameed Siqqidi, and Amjad Ali. 2021. Securing low-power blockchain-enabled IoT devices against energy depletion attack. ACM Trans. Internet Technol. 23, 3 (2021). DOI:

Digital Library

[53]

P. P. Ioulianou, V. G. Vassilakis, and M. D. Logothetis. 2019. Battery drain denial-of-service attacks and defenses in the internet of things. J. Telecommun. Inf. Technol. 2 (2019), 37–45. DOI:

[54]

B. Janes, H. Crawford, and T. J. Oconnor. 2020. Never ending story: Authentication and access control design flaws in shared IoT devices. In 2020 IEEE Security and Privacy Workshops (SPW). 104–109. DOI:

[55]

C. Hahn, J. Kim, H. Kwon, and J. Hur. 2020. Efficient IoT management with resilience to unauthorized access to cloud storage. IEEE Trans. Cloud Comput. 10, 2 (2020), 1–1. DOI:

[56]

M. Guerar, L. Verderame, A. Merlo, F. Palmieri, M. Migliardi, and L. Vallerini. 2020. CirclePIN. ACM Trans. Cyber-phys. Syst. 4, 3 (2020). DOI:

Digital Library

[57]

Z. A. Baig, S. Sanguanpong, S. N. Firdous, V. N. Vo, T. G. Nguyen, and C. So-In. 2020. Averaged dependence estimators for DoS attack detection in IoT networks. Fut. Gen. Comput. Syst. 102 (2020), 198–209. DOI:

Digital Library

[58]

S. Sinha and S. B. 2021. Impact of DoS attack in IoT system and identifying the attacker location for interference attacks. In 2021 6th International Conference on Communication and Electronics Systems (ICCES). 657–662. DOI:

[59]

M. Ghahramani, R. Javidan, M. Shojafar, R. Taheri, M. Alazab, and R. Tafazolli. 2021. RSS: An energy-efficient approach for securing IoT service protocols against the DoS attack. IEEE Internet Things J. 8, 5 (2021), 3619–3635. DOI:

[60]

M. M. Shurman, R. M. Khrais, and A. A. Yateem. 2019. IoT denial-of-service attack detection and prevention using hybrid IDS. In 2019 International Arab Conference on Information Technology (ACIT). 252–254. DOI:

[61]

A. Munshi, N. A. Alqarni, and N. Abdullah Almalki. 2020. DDOS attack on IOT devices. In 2020 3rd International Conference on Computer Applications & Information Security (ICCAIS). DOI:

[62]

K. Huang, L. X. Yang, X. Yang, Y. Xiang, and Y. Y. Tang. 2020. A low-cost distributed denial-of-service attack architecture. IEEE Access 8 (2020), 42111–42119. DOI:

[63]

N. Ravi and S. M. Shalinie. 2020. Learning-driven detection and mitigation of DDoS attack in IoT via SDN-cloud architecture. IEEE Internet Things J. 7, 4 (2020), 3559–3570. DOI:

[64]

F. Hussain, S. G. Abbas, M. Husnain, U. U. Fayyaz, F. Shahzad, and G. A. Shah. 2020. IoT DoS and DDoS attack detection using ResNet. In 2020 IEEE 23rd International Multitopic Conference (INMIC). DOI:

[65]

J. Bhayo, S. Hameed, and S. A. Shah. 2020. An efficient counter-based DDoS attack detection framework leveraging software defined IoT (SD-IoT). IEEE Access 8 (2020). DOI:

[66]

A. Agiollo, M. Conti, P. Kaliyar, T. N. Lin, and L. Pajola. 2021. DETONAR: Detection of routing attacks in RPL-based IoT. IEEE Trans. Netw. Serv. Manag 18, 2 (2021), 1178–1190. DOI:

[67]

R. Sahay, G. Geethakumari, and B. Mitra. 2020. A novel blockchain based framework to secure IoT-LLNs against routing attacks. Comput 102, 11 (2020), 2445–2470. DOI:

Digital Library

[68]

Anca Jurcut, Tiberiu Niculcea, Pasika Ranaweera, and Nhien-An Le-Khac. 2020. Security considerations for internet of things: A survey. Springer Nature. DOI:

Digital Library

[69]

H. Wong, T. T. Luo, and T. Luo. 2020. Man-in-the-middle attacks on MQTT-based IoT using BERT based adversarial message generation mobile edge computing view project mobile crowdsensing and crowdsourcing view project man-in-the-middle attacks on MQTT-based IoT using BERT based adversarial mess. In 3rd International Workshop on Artificial Intelligence of Things (AIoT’20).

[70]

J. Thomas, S. Cherian, S. Chandran, and V. Pavithran. 2020. Man in the middle attack mitigation in LoRaWAN. In 2020 International Conference on Inventive Computation Technologies (ICICT). 353–358. DOI:

[71]

D. A. McGrew and J. Viega. 2004. The security and performance of the Galois/counter mode (GCM) of operation. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics) 3348, 343–355. DOI:

Digital Library

[72]

J. J. Kang, K. Fahd, S. Venkatraman, R. Trujillo-Rasua, and P. Haskell-Dowland. 2019. Hybrid routing for man-in-the-middle (MITM) attack detection in IoT networks. In 2019 29th International Telecommunication Networks and Applications Conference (ITNAC). DOI:

[73]

H. Mohammadnia and S. Ben Slimane. 2020. IoT-NETZ: Practical spoofing attack mitigation approach in SDWN network. In 2020 7th International Conference on SoZware Defined Systems (SDS). 5–13. DOI:

[74]

H. Aldabbas and R. Amin. 2021. A novel mechanism to handle address spoofing attacks in SDN based IoT. Clust. Comput. 24, 4 (2021), 1–16. DOI:

Digital Library

[75]

F. Galtier, R. Cayre, G. Auriol, M. Kaaniche, and V. Nicomette. 2020. A PSD-based fingerprinting approach to detect IoT device spoofing. In 2020 IEEE 25th Pacific Rim International Symposium on Dependable Computing (PRDC). 40–49. DOI:

[76]

S. A. Chaudhry, K. Yahya, F. Al-Turjman, and M. H. Yang. 2020. A secure and reliable device access control scheme for IoT based sensor cloud systems. IEEE Access 8 (2020), 139244–139254. DOI:

[77]

A. K. Das, M. Wazid, A. R. Yannam, J. J. P. C. Rodrigues, and Y. Park. 2019. Provably secure ECC-based device access control and key agreement protocol for IoT environment. IEEE Access 7 (2019), 55382–55397. DOI:

[78]

S. Sun, R. Du, S. Chen, and W. Li. 2021. Blockchain-based IoT access control system: Towards security, lightweight, and cross-domain. IEEE Access 9 (2021), 36868–36878. DOI:

[79]

Y. E. Oktian and S. G. Lee. 2021. BorderChain: Blockchain-based access control framework for the internet of things endpoint. IEEE Access 9 (2021), 3592–3615. DOI:

[80]

T. P. Latchoumi, M. S. Reddy, and K. Balamurugan. 2020. Applied machine learning predictive analytics to SQL injection attack detection and prevention. Eur. J. Mol. Clin. Med. 7, 2 (2020), 3543--3553.

[81]

G. M. and P. H. B. 2021. Semantic query-featured ensemble learning model for SQL-injection attack detection in IoT-ecosystems. IEEE Trans. Reliab. 71, 2 (2021). DOI:

[82]

Q. Li, F. Wang, J. Wang, and W. Li. 2019. LSTM-based SQL injection detection method for intelligent transportation system. IEEE Trans. Veh. Technol. 68, 5 (2019), 4182–4191. DOI:

[83]

D. Chen, Q. Yan, C. Wu, and J. Zhao. 2021. SQL injection attack detection and prevention techniques using deep learning. J. Phys. Conf. Ser. 1757, 1 (2021), 012055. DOI:

[84]

J. Tournier, F. Lesueur, F. Le Mouël, L. Guyon, and H. Ben-Hassine. 2020. A survey of IoT protocols and their security issues through the lens of a generic IoT stack. Internet of Things. 16 (2020), 100264. DOI:.

[85]

T. Aditya Sai Srinivas and S. S. Manivannan. 2020. Prevention of hello flood attack in IoT using combination of deep learning with improved rider optimization algorithm. Comput. Commun. 163 (2020), 162–175. DOI:.

[86]

X. Ding, F. Xiao, M. Zhou, and Z. Wang. 2020. Active link obfuscation to thwart link-flooding attacks for internet of things. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). 217–224. DOI:

[87]

A. Gajbhiye, D. Sen, A. Bhatt, and G. Soni. 2020. DPLPLN: Detection and prevention from flooding attack in IoT. In 2020 International Conference on Smart Electronics and Communication (ICOSEC). 704–709. DOI:

[88]

B. T. Devi, S. Shitharth, and M. A. Jabbar. 2020. An appraisal over intrusion detection systems in cloud computing security attacks. In 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). 722–727. DOI:

[89]

A. McDole, M. Abdelsalam, M. Gupta, and S. Mittal. 2020. Analyzing CNN based behavioural malware detection techniques on cloud IaaS. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 12403 LNCS 64–79. DOI:

[90]

T. Panker and N. Nissim. 2021. Leveraging malicious behavior traces from volatile memory using machine learning methods for trusted unknown malware detection in Linux cloud environments. Knowl.-based Syst. 226 (2021), 107095. DOI:

[91]

S. Modak, K. Majumder, and D. De. 2021. Vulnerability of cloud: Analysis of XML signature wrapping attack and countermeasures. Adv. Intell. Syst. Comput 1255 (2021), 755–765. DOI:

[92]

M. D. Hossain, H. Ochiai, F. Doudou, and Y. Kadobayashi. 2020. SSH and FTP brute-force attacks detection in computer networks: LSTM and machine learning approaches. In 2020 5th International Conference on Computer and Communication Systems (ICCCS). 491–497. DOI:

[93]

J. Park, J. Kim, B. B. Gupta, and N. Park. Network log-based SSH brute-force attack detection model. Computers, Materials & Continua. DOI:

[94]

M. M. Raikar and S. M. Meena. 2021. SSH brute force attack mitigation in internet of things (IoT) network: An edge device security measure. In 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC). 72–77. DOI:

[95]

M. Šarac, N. Pavlović, N. Bacanin, F. Al-Turjman, and S. Adamović. 2021. Increasing privacy and security by integrating a blockchain secure interface into an IoT device security gateway architecture. Energy Rep. 7 (2021), 8075–8082. DOI:

[96]

Nikola Pavlović, Marko S̆arac, Sas̆a Adamović, Muzafer Sarac̆ević, Khaleel Ahmad, Nemanja Mac̆ek, and Deepak Kumar Sharma. 2021. An approach to adding simple interface as security gateway architecture for IoT device. Multimed. Tools Appl. 81, 26 (2021), 1–16. DOI:

[97]

S. A. Suresh and R. J. Priyadarsini. 2022. Design of maintaining data security on IoT data transferred through IoT gateway system to cloud storage. Int. J. Comput. Netw. Appl. 9, 1 (2022), 135--149. DOI:

[98]

R. Khan, K. McLaughlin, B. Kang, D. Laverty, and S. Sezer. 2021. A novel edge security gateway for end-to-end protection in industrial internet of things. In 2021 IEEE Power & Energy Society General Meeting (PESGM). DOI:

[99]

C. Peng, J. Chen, P. Vijayakumar, N. Kumar, and D. He. 2021. Efficient distributed decryption scheme for IoT gateway-based applications. ACM Trans. Internet Technol. 21, 1 (2021). DOI:

Digital Library

[100]

A. Pillai, M. Sindhu, and K. V. Lakshmy. 2019. Securing firmware in internet of things using blockchain. In 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS). 329–334. DOI:

[101]

A. Yohan and N. W. Lo. 2020. FOTB: A secure blockchain-based firmware update framework for IoT environment. Int. J. Inf. Secur 19, 3 (2020), 257–278. DOI:

Digital Library

[102]

A. Anastasiou, P. Christodoulou, K. Christodoulou, V. Vassiliou, and Z. Zinonos. 2020. IoT device firmware update over LoRa: The blockchain solution. In 2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS). 404–411. DOI:

[103]

M. Khari, A. K. Garg, A. H. Gandomi, R. Gupta, R. Patan, and B. Balusamy. 2020. Securing data in internet of things (IoT) using cryptography and steganography techniques. IEEE Trans. Syst. Man, Cybern. Syst. 50, 1 (2020), 73–80. DOI:

[104]

S. Sivagowry and M. Durairaj. 2014. PSO – An intellectual technique for feature reduction in heart malady anticipation data. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 4, 9 (2014), 735–742. DOI:

[105]

S. Chandra, S. Paira, S. S. Alam, and G. Sanyal. 2014. A comparative survey of symmetric and asymmetric key cryptography. In 2014 International Conference on Electronics, Communication and Computational Engineering (ICECCE). 83–93. DOI:

[106]

S. Sangeeta and E. A. Kaur. 2017. A review on symmetric key cryptography algorithms. Int. J. Adv. Res. Comput. Sci. 8, 4 (2017). DOI:

[107]

M. B. Yassein, S. Aljawarneh, E. Qawasmeh, W. Mardini, and Y. Khamayseh. 2018. Comprehensive study of symmetric key and asymmetric key encryption algorithms. In 2017 International Conference on Engineering and Technology (ICET). 1–7. DOI:

[108]

S. Rani and H. Kaur. 2017. Technical review on symmetric and asymmetric cryptography algorithms. Int. J. Adv. Res. Comput. Sci. 8, 4 (2017). DOI:

[109]

I. E. Salem, A. M. Salman, and M. M. Mijwil. 2019. A survey: Cryptographic hash functions for digital stamping. J. Southw. Jiaotong Univ. 54, 6 (2019). DOI:

[110]

D. Wang, Y. Jiang, H. Song, F. He, M. Gu, and J. Sun. 2017. Verification of implementations of cryptographic hash functions. IEEE Access 5 (2017), 7816–7825. DOI:

[111]

A. Kumar, V. Jain, and A. Yadav. 2020. A new approach for security in cloud data storage for IOT applications using hybrid cryptography technique. In 2020 International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC). 514–517. DOI:.

[112]

G. Sittampalam and N. Ratnarajah. 2020. Enhanced symmetric cryptography for IoT using novel random secret key approach. In 2020 2nd International Conference on Advancements in Computing (ICAC). 398–403. DOI:

[113]

J. Qiu, Z. Tian, C. Du, Q. Zuo, S. Su, and B. Fang. 2020. A survey on access control in the age of internet of things. IEEE Internet Things J. 7, 6 (2020), 4682–4696. DOI:

[114]

Muhammad Umar AZab, Yasir Munir, Ariyo Oluwasanmi, Zhiguang Qin, Muhammad Haris Aziz, Zakria, Ngo Tung Son, and Van Dinh Tran. 2020. A hybrid access control model with dynamic COI for secure localization of satellite and IoT-based vehicles. IEEE Access 8 (2020), 24196–24208. DOI:

[115]

D. Yu, L. Zhang, Y. Chen, Y. Ma, and J. Chen. 2020. Large-scale IoT devices firmware identification based on weak password. IEEE Access 8 (2020), 7981–7992. DOI:

[116]

F. M. Alfard, A. Ali Keshlaf, and O. M. Bouzid. 2021. IoTGazePass: A new password scheme for IoT applications. IEEE, 299–304. DOI:.

[117]

K. Zandberg, K. Schleiser, F. Acosta, H. Tschofenig, and E. Baccelli. 2019. Secure firmware updates for constrained IoT devices using open standards: A reality check. IEEE Access 7 (2019), 71907–71920. DOI:

[118]

N. Mtetwa, P. Tarwireyi, and M. Adigun. 2019. Secure the internet of things software updates with Ethereum blockchain. In 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC). DOI:

[119]

A. Aborujiah, A. E. F. M. Elsebaie, and S. A. Mokhtar. 2021. IoT MEMS: IoT based paradigm for medical equipment management systems of ICUs in light of COVID-19 outbreak. IEEE Access. 9 (2021). DOI:

[120]

Ibrahim Bello, Haruna Chiroma, Usman A. Abdullahi, Abdulsalam Ya'u Gital, Fatsuma Jauro, Abdullah Khan, Julius O. Okesola, and Shafi'i M. Abdulhamid. 2020. Detecting ransomware attacks using intelligent algorithms: Recent development and next direction from deep learning and big data perspectives. J. Amb. Intell. Hum. Comput. 12, 9 (2020), 8699–8717. DOI:

[121]

M. Humayun, N. Z. Jhanjhi, A. Alsayat, and V. Ponnusamy. 2021. Internet of things and ransomware: Evolution, mitigation and prevention. Egypt. Inform. J. 22, 1 (2021), 105–117. DOI:

[122]

Y. T. Lee et al. 2020. Cross platform IoT- malware family classification based on printable strings. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). 775–784. DOI:

[123]

J. Jeon, J. H. Park, and Y. S. Jeong. 2020. Dynamic analysis for IoT malware detection with convolution neural network model. IEEE Access 8 (2020), 96899–96911. DOI:

[124]

C. Jiang, J. Kuang, and S. Wang. 2019. Home IoT intrusion prevention strategy based on edge computing. In 2019 IEEE 2nd International Conference on Electronics and Communication Engineering (ICECE). 94–98. DOI:

[125]

G. Abdelmoumin, D. B. Rawat, and A. Rahman. 2021. On the performance of machine learning models for anomaly-based intelligent intrusion detection systems for the internet of things. IEEE Internet Things J. 9, 6 (2021), 1–1. DOI:

[126]

A. Yahyaoui, H. Lakhdhar, T. Abdellatif, and R. Attia. 2021. Machine learning based network intrusion detection for data streaming IoT applications. In 2021 21st ACIS International Winter Conference on SoZware Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter). 51–56. DOI:

[127]

C. Ioannou and V. Vassiliou. 2020. Experimentation with local intrusion detection in IoT networks using supervised learning. In 2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS). 423–428. DOI:

[128]

S. Joshi and E. Abdelfattah. 2020. Efficiency of different machine learning algorithms on the multivariate classification of IoT botnet attacks. In 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). 0517–0521. DOI:

[129]

Hanwen Liu, Xiaohan Helu, Chengjie Jin, Hui Lu, Zhihong Tian, Xiaojiang Du, and Khalid Abualsaud. 2020. A malware detection method for health sensor data based on machine learning. In 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT). 277–282. DOI:

[130]

A. Makkar, S. Garg, N. Kumar, M. S. Hossain, A. Ghoneim, and M. Alrashoud. 2021. An efficient spam detection technique for IoT devices using machine learning. IEEE Trans. Industr. Inform. 17, 2 (2021), 903–912. DOI:

[131]

R. Nadia, B. A. Tama, and J. S. Song. 2020. Seamless human impedance-based IoT authentication with machine learning techniques. In 2020 International Conference on Information and Communication Technology Convergence (ICTC). 339–343. DOI:

[132]

Y. W. Chen, J. P. Sheu, Y. C. Kuo, and N. Van Cuong. 2020. Design and implementation of IoT DDoS attacks detection system based on machine learning. In 2020 European Conference on Networks and Communications (EuCNC). 122–127. DOI:

[133]

M. M. N. Aboelwafa, K. G. Seddik, M. H. Eldefrawy, Y. Gadallah, and M. Gidlund. 2020. A machine-learning-based technique for false data injection attacks detection in industrial IoT. IEEE Internet Things J. 7, 9 (2020), 8462–8471. DOI:

[134]

T. M. Hoang, N. M. Nguyen, and T. Q. Duong. 2020. Detection of eavesdropping attack in UAV-aided wireless systems: Unsupervised learning with one-class SVM and k-means clustering. IEEE Wirel. Commun. Lett. 9, 2 (2020), 139–142. DOI:

[135]

V. Rey, P. M. Sánchez Sánchez, A. Huertas Celdrán, and G. Bovet. 2022. Federated learning for malware detection in IoT devices. Comput. Netw. 204 (2022), 108693. DOI:

Digital Library

[136]

S. T. Mehedi, A. Anwar, Z. Rahman, K. Ahmed, and R. Islam. 2023. Dependable intrusion detection system for IoT: A deep transfer learning based approach. IEEE Trans. Ind. Inform. 19, 1 (2023), 1006–1017. DOI:

[137]

H. Lin, S. Garg, J. Hu, X. Wang, M. J. Piran, and M. S. Hossain. 2022. Data fusion and transfer learning empowered granular trust evaluation for internet of things. Inf. Fusion 78 (2022), 149–157. DOI:

Digital Library

[138]

B. Xue, H. Zhao, and W. Yao. 2022. Deep transfer learning for IoT intrusion detection. In 2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT). 88–94. DOI:

[139]

Areej A. Malibari, Saud S. Alotaibi, Reem Alshahrani, Sami Dhahbi, Rana Alabdan, Fahd N. Al-wesabi, and Anwer Mustafa Hilal. 2022. A novel metaheuristics with deep learning enabled intrusion detection system for secured smart environment. Sustain. Energy Technol. Assessments 52 (2022), 102312. DOI:

[140]

S. S. Kareem, R. R. Mostafa, F. A. Hashim, and H. M. El-Bakry. 2022. An effective feature selection model using hybrid metaheuristic algorithms for IoT intrusion detection. Sensors 22, 4 (2022), 1396. DOI:

[141]

S. Saif, P. Das, S. Biswas, M. Khari, and V. Shanmuganathan. 2022. HIIDS: Hybrid intelligent intrusion detection system empowered with machine learning and metaheuristic algorithms for application in IoT based healthcare. Microprocess. Microsyst. 104622. DOI:

[142]

Y. Otoum, S. K. Yadlapalli, and A. Nayak. 2022. FTLIoT: A federated transfer learning framework for securing IoT. In GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 1146–1151. DOI:

[143]

Y. Otoum, D. Liu, and A. Nayak. 2022. DL-IDS: A deep learning–based intrusion detection framework for securing IoT. Trans. Emerg. Telecommun. Technol 33, 3 (2022), e3803. DOI:

Digital Library

[144]

W. H. Kuo and Y. C. Wang. 2019. An energy-saving edge computing and transmission scheme for IoT mobile devices. In 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE). 443–444. DOI:

[145]

R. Amin, M. Hussain, S. Mohsan Raza, M. Alhameed, F. Jeribi, and A. Tahir. 2020. Edge-computing with graph computation: A novel mechanism to handle network intrusion and address spoofing in SDN hybrid SDN view project efficient handling of network policy change in SDN view project edge-computing with graph computation: A novel mechanism to handle network intrusion and address spoofing in SDN. C. C. 65, 3 (2020), 1869–1890. DOI:

[146]

Laisen Nie, Yixuan Wu, Xiaojie Wang, Lei Guo, Guoyin Wang, Xinbo Gao, and Shengtao Li. 2021. Intrusion detection for secure social internet of things based on collaborative edge computing: A generative adversarial network-based approach. IEEE Trans. Comput. Soc. Syst. 9, 1 (2021). DOI:

[147]

Junxia Li, Jinjin Cai, Fazlullah Khan, Ateeq Ur Rehman, Venki Balasubramaniam, Jiangfeng Sun, and P. Venu. 2020. A secured framework for SDN-based edge computing in IoT-enabled healthcare system. IEEE Access 8 (2020), 135479–135490. DOI:

[148]

W. Ahmed, S. M. Hizam, I. Sentosa, J. Ali, and T. Ali. 2020. Structural equation modeling for acceptance of cloud computing. In 2019 International Conference on Advances in the Emerging Computing Technologies (AECT). DOI:

[149]

A. A. A. Alkhatib, T. Sawalha, and S. Alzu'Bi. 2020. Load balancing techniques in software-defined cloud computing: An overview. In 2020 Seventh International Conference on SoZware Defined Systems (SDS). 240–244. DOI:

[150]

A. Markandey, P. Dhamdhere, and Y. Gajmal. 2019. Data access security in cloud computing: A review. In 2018 International Conference on Computing, Power and Communication Technologies (GUCON). 633–636. DOI:

[151]

P. Yang, N. Xiong, and J. Ren. 2020. Data security and privacy protection for cloud storage: A survey. IEEE Access 8 (2020), 131723–131740. DOI:

[152]

S. Xiong, Q. Ni, L. Wang, and Q. Wang. 2020. SEM-ACSIT: Secure and efficient multiauthority access control for IoT cloud storage. IEEE Internet Things J. 7, 4 (2020), 2914–2927. DOI:

[153]

K. Riad, T. Huang, and L. Ke. 2020. A dynamic and hierarchical access control for IoT in multi-authority cloud storage. J. Netw. Comput. Appl. 160, 102633. DOI:

[154]

M. Rashid, S. A. Parah, A. R. Wani, and S. K. Gupta. 2020. Securing e-health IoT data on cloud systems using novel extended role based access control model. Internet Things Concepts Appl. 473–489. DOI:

[155]

L. Ding, Z. Wang, X. Wang, and D. Wu. 2020. Security information transmission algorithms for IoT based on cloud computing. Comput. Commun 155 (2020), 32–39. DOI:

[156]

M. Anuradha, T. Jayasankar, N. B. Prakash, Mohamed Yacin Sikkandar, G. R. Hemalakshmi, C. Bharatiraja, and A. Sagai Francis Britto. 2021. IoT enabled cancer prediction system to enhance the authentication and security using cloud computing. Microprocess. Microsyst. 80 (2021), 103301. DOI:

Digital Library

[157]

M. Wang and Q. Zhang. 2020. Optimized data storage algorithm of IoT based on cloud computing in distributed system. Comput. Commun. 157 (2020), 124–131. DOI:

[158]

R. SaiSindhuTheja and G. K. Shyam. 2021. An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment. Appl. Soft Comput. 100 (2021), 106997. DOI:

[159]

R. Saxena and S. Dey. 2019. DDoS attack prevention using collaborative approach for cloud computing. Clust. Comput. 23, 2 (2019), 1329–1344. DOI:

Digital Library

[160]

H. H. Pajooh, M. Rashid, F. Alam, and S. Demidenko. 2021. Hyperledger fabric blockchain for securing the edge internet of things. Sensors 21, 2 (2021), 359. DOI:

[161]

L. Hang and D.-H. Kim. 2019. Design and implementation of an integrated IoT blockchain platform for sensing data integrity. Sensors 19, 10 (2019), 2228. DOI:

[162]

A. M. Al-Madani and A. T. Gaikwad. 2020. IoT data security via blockchain technology and service-centric networking. In 2020 International Conference on Inventive Computation Technologies (ICICT). 17–21. DOI:

[163]

M. Bhandary, M. Parmar, and D. Ambawade. 2020. A blockchain solution based on directed acyclic graph for IoT data security using IoTA tangle. IEEE, 827–832. DOI:

[164]

H. Xu, Q. He, X. Li, B. Jiang, and K. Qin. 2020. BDSS-FA: A blockchain-based data security sharing platform with fine-grained access control. IEEE Access 8 (2020), 87552–87561. DOI:

[165]

P. C. Wei, D. Wang, Y. Zhao, S. K. S. Tyagi, and N. Kumar. 2020. Blockchain data-based cloud data integrity protection mechanism. Fut. Gen. Comput. Syst. 102 (2020), 902–911. DOI:

Digital Library

[166]

Q. Zhao, S. Chen, Z. Liu, T. Baker, and Y. Zhang. 2020. Blockchain-based privacy-preserving remote data integrity checking scheme for IoT information systems. Inf. Process. Manag. 57, 6 (2020), 102355. DOI:

[167]

H. Liu, D. Han, and D. Li. 2020. Fabric-IoT: A blockchain-based access control system in IoT. IEEE Access 8 (2020), 18207–18218. DOI:

[168]

Zhihua Cui, Fei Xue, Shiqiang Zhang, Xingjuan Cai, Yang Cao, Wensheng Zhang, and Jinjun Chen. 2020. A hybrid blockchain-based identity authentication scheme for multi-WSN. IEEE Trans. Serv. Comput. 13, 2 (2020), 241–251. DOI:

[169]

F. A. A. Lins and M. Vieira. 2021. Security requirements and solutions for IoT gateways: A comprehensive study. IEEE Internet Things J. 8, 11 (2021), 8667–8679. DOI:

[170]

B. L. Tait. 2021. Aspects of biometric security in internet of things devices. Adv. Sci. Technol. Secur. Appl. 169–186. DOI:

[171]

Xinyu Jiang, Xiangyu Liu, Jiahao Fan, Xinming Ye, Chenyun Dai, Edward A. Clancy, Dario Farina, and Wei Chen. 2021. Enhancing IoT security via cancelable HD-sEMG-based biometric authentication password, encoded by gesture. IEEE Internet Things J. 8, 22 (2021). DOI:

Cited By

Wei JTian GChen XSusilo W(2025)Lightweight 0-RTT Session Resumption Protocol for Constrained DevicesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.349779620(221-233)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TIFS.2024.3497796
Ferraris DFernandez-Gago CAssouyat YLabiod HHaiguang WLopez J(2025)Trust dynamicity for IoT: How do i trust your social IoT cluster?Internet of Things10.1016/j.iot.2025.101529(101529)Online publication date: Feb-2025
https://doi.org/10.1016/j.iot.2025.101529
Mustafa RSarkar NMohaghegh MPervez S(2024)A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive SurveySensors10.3390/s2422720924:22(7209)Online publication date: 11-Nov-2024
https://doi.org/10.3390/s24227209
Show More Cited By

Index Terms

A Systematic Review of IoT Security: Research Potential, Challenges, and Future Directions
1. Networks
2. Security and privacy
  1. Formal methods and theory of security
  2. Intrusion/anomaly detection and malware mitigation
    1. Malware and its mitigation

Recommendations

A top-down survey on securing IoT with machine learning: goals, recent advances and challenges

The Internet of Things (IoT) has seen it all from being just another innovation to a leading technology; it is now a binding force that interconnects various aspects of our lives. The IoT's tremendous growth is driven by emerging applications and evolving ...
IoT Eco-system, Layered Architectures, Security and Advancing Technologies: A Comprehensive Survey
Abstract
Today almost every person’s life revolves around internet and Internet of Things (IoT). IoT is a paradigm which interconnects devices, people, or networks with the ability to process and respond to any physical or virtual communication without a ...
Industrial Internet of Things enabled technologies, challenges, and future directions
Highlights
- IIoT-enabled technologies, challenges, and future directions are explored.
- A blockchain-based cement industry security framework can overcome 51% of security issues.
- The performance of major companies depends on well-designed IIoT ...
Abstract
The Industrial Internet of Things (IIoT) is recognized as the fourth industrial revolution as it enhances productivity, dependability, and competitive performance by concentrating on profitability. IIoT-enabled technologies have been reviewed and ...
Graphical abstract

Display Omitted

Comments

Information & Contributors

Information

Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 56, Issue 5

May 2024

1019 pages

EISSN:1557-7341

DOI:10.1145/3613598

Editor:
Albert Zomaya
University of Sydney, Australia

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 November 2023

Online AM: 09 October 2023

Accepted: 21 August 2023

Revised: 28 April 2023

Received: 15 June 2022

Published in CSUR Volume 56, Issue 5

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Survey

Funding Sources

Natural Sciences and Engineering Research Council (NSERC) of Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

8
Total Citations
View Citations
2,668
Total Downloads

Downloads (Last 12 months)1,791
Downloads (Last 6 weeks)146

Reflects downloads up to 08 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Wei JTian GChen XSusilo W(2025)Lightweight 0-RTT Session Resumption Protocol for Constrained DevicesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.349779620(221-233)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TIFS.2024.3497796
Ferraris DFernandez-Gago CAssouyat YLabiod HHaiguang WLopez J(2025)Trust dynamicity for IoT: How do i trust your social IoT cluster?Internet of Things10.1016/j.iot.2025.101529(101529)Online publication date: Feb-2025
https://doi.org/10.1016/j.iot.2025.101529
Mustafa RSarkar NMohaghegh MPervez S(2024)A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive SurveySensors10.3390/s2422720924:22(7209)Online publication date: 11-Nov-2024
https://doi.org/10.3390/s24227209
Gómez-Hernández JGarcía-Teodoro P(2024)Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile MonitoringSensors10.3390/s2409267924:9(2679)Online publication date: 23-Apr-2024
https://doi.org/10.3390/s24092679
Minani JSabir FMoha NGuéhéneuc Y(2024)A Systematic Review of IoT Systems Testing: Objectives, Approaches, Tools, and ChallengesIEEE Transactions on Software Engineering10.1109/TSE.2024.336361150:4(785-815)Online publication date: Apr-2024
https://doi.org/10.1109/TSE.2024.3363611
Guo HChen LRen XZhao MLi CXue JZhu LZhang C(2024)Privacy-Preserving and Revocable Redactable Blockchains With Expressive Policies in IoTIEEE Internet of Things Journal10.1109/JIOT.2024.343572911:21(35390-35404)Online publication date: 1-Nov-2024
https://doi.org/10.1109/JIOT.2024.3435729
Alghamdi ABarsoum A(2024)A Comprehensive IDs to Detect Botnet Attacks Using Machine Learning Techniques2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI)10.1109/ICMI60790.2024.10585846(1-6)Online publication date: 13-Apr-2024
https://doi.org/10.1109/ICMI60790.2024.10585846
Bhole MKastner WSauter T(2024)Towards Unveiling Vulnerabilities and Securing IoT Devices: An Ontology-Based Approach2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)10.1109/ETFA61755.2024.10710882(1-8)Online publication date: 10-Sep-2024
https://doi.org/10.1109/ETFA61755.2024.10710882
Galli ALa Gatta VMoscato VPostiglione MSperlì G(2024)Explainability in AI-based behavioral malware detection systemsComputers and Security10.1016/j.cose.2024.103842141:COnline publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.cose.2024.103842

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Full Text

View this article in Full Text.

Figures

Tables

Media

View full text|Download PDF

View Issue’s Table of Contents