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Su, Jiawei, Yoshioka, Katsunari, Shikata, Junji, Matsumoto, Tsutomu.  2016.  An Efficient Method for Detecting Obfuscated Suspicious JavaScript Based on Text Pattern Analysis. Proceedings of the 2016 ACM International on Workshop on Traffic Measurements for Cybersecurity. :3–11.

The malicious JavaScript is a common springboard for attackers to launch several types of network attacks, such as Drive-by-Download and malicious PDF delivery attack. In order to elude detection of signature matching, malicious JavaScript is often packed (so-called "obfuscation") with diversified algorithms therefore the occurrence of obfuscation is always a good pointer for potential maliciousness. In this investigation, we propose a light weight approach for quickly filtering obfuscated JavaScript by a novel method of tokenizing JavaScript text at letter level and information-theoretic measures, based on the previous work in the domain of detecting obfuscated malicious code as well as the pattern analysis of natural languages. The new approach is apparently time efficient compared to existing systems since it processes much less objects while it is also proved to be able to reach the acceptable detection accuracies.

Su, Jinshu, Chen, Shuhui, Han, Biao, Xu, Chengcheng, Wang, Xin.  2016.  A 60Gbps DPI Prototype Based on Memory-Centric FPGA. Proceedings of the 2016 ACM SIGCOMM Conference. :627–628.

Deep packet inspection (DPI) is widely used in content-aware network applications to detect string features. It is of vital importance to improve the DPI performance due to the ever-increasing link speed. In this demo, we propose a novel DPI architecture with a hierarchy memory structure and parallel matching engines based on memory-centric FPGA. The implemented DPI prototype is able to provide up to 60Gbps full-text string matching throughput and fast rules update speed.

Su, Jinsong, Zeng, Jiali, Xiong, Deyi, Liu, Yang, Wang, Mingxuan, Xie, Jun.  2018.  A Hierarchy-to-Sequence Attentional Neural Machine Translation Model. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 26:623—632.

Although sequence-to-sequence attentional neural machine translation (NMT) has achieved great progress recently, it is confronted with two challenges: learning optimal model parameters for long parallel sentences and well exploiting different scopes of contexts. In this paper, partially inspired by the idea of segmenting a long sentence into short clauses, each of which can be easily translated by NMT, we propose a hierarchy-to-sequence attentional NMT model to handle these two challenges. Our encoder takes the segmented clause sequence as input and explores a hierarchical neural network structure to model words, clauses, and sentences at different levels, particularly with two layers of recurrent neural networks modeling semantic compositionality at the word and clause level. Correspondingly, the decoder sequentially translates segmented clauses and simultaneously applies two types of attention models to capture contexts of interclause and intraclause for translation prediction. In this way, we can not only improve parameter learning, but also well explore different scopes of contexts for translation. Experimental results on Chinese-English and English-German translation demonstrate the superiorities of the proposed model over the conventional NMT model.

Su, K.-M., Liu, I.-H., Li, J.-S..  2020.  The Risk of Industrial Control System Programmable Logic Controller Default Configurations. 2020 International Computer Symposium (ICS). :443—447.
In recent years, many devices in industrial control systems (ICS) equip Ethernet modules for more efficient communication and more fiexible deployment. Many communication protocols of those devices are based on internet protocol, which brings the above benefits but also makes it easier to access by anyone including attackers. In the case of using the factory default configurations, we wiiˆ demonstrate how to easily modify the programmable logic controllers (PLCs) program through the Integrated Development Environment provided by the manufacturer under the security protection of PLC not set properly and discuss the severity of it.
Su, Lili, Vaidya, Nitin H..  2016.  Fault-Tolerant Multi-Agent Optimization: Optimal Iterative Distributed Algorithms. Proceedings of the 2016 ACM Symposium on Principles of Distributed Computing. :425–434.

This paper addresses the problem of distributed multi-agent optimization in which each agent i has a local cost function hi(x), and the goal is to optimize a global cost function that aggregates the local cost functions. Such optimization problems are of interest in many contexts, including distributed machine learning, distributed resource allocation, and distributed robotics. We consider the distributed optimization problem in the presence of faulty agents. We focus primarily on Byzantine failures, but also briey discuss some results for crash failures. For the Byzantine fault-tolerant optimization problem, the ideal goal is to optimize the average of local cost functions of the non-faulty agents. However, this goal also cannot be achieved. Therefore, we consider a relaxed version of the fault-tolerant optimization problem. The goal for the relaxed problem is to generate an output that is an optimum of a global cost function formed as a convex combination of local cost functions of the non-faulty agents. More precisely, there must exist weights αi for i∈N such that αi ≥ 0 and ∑i≥ Nαi=1, and the output is an optimum of the cost function ∑i≥ N αihi(x). Ideally, we would like αi=1/textbarNtextbar for all i≥ N, however, this cannot be guaranteed due to the presence of faulty agents. In fact, the maximum number of nonzero weights (αi's) that can be guaranteed is textbarNtextbar-f, where f is the maximum number of Byzantine faulty agents. We present an iterative distributed algorithm that achieves optimal fault-tolerance. Specifically, it ensures that at least textbarNtextbar-f agents have weights that are bounded away from 0 (in particular, lower bounded by 1/2textbarNtextbar-f\vphantom\\). The proposed distributed algorithm has a simple iterative structure, with each agent maintaining only a small amount of local state. We show that the iterative algorithm ensures two properties as time goes to ∞: consensus (i.e., output of non-faulty agents becomes identical in the time limit), and optimality (in the sense that the output is the optimum of a suitably defined global cost function).

Su, Liya, Yao, Yepeng, Lu, Zhigang, Liu, Baoxu.  2019.  Understanding the Influence of Graph Kernels on Deep Learning Architecture: A Case Study of Flow-Based Network Attack Detection. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :312–318.
Flow-based network attack detection technology is able to identify many threats in network traffic. Existing techniques have several drawbacks: i) rule-based approaches are vulnerable because it needs all the signatures defined for the possible attacks, ii) anomaly-based approaches are not efficient because it is easy to find ways to launch attacks that bypass detection, and iii) both rule-based and anomaly-based approaches heavily rely on domain knowledge of networked system and cyber security. The major challenge to existing methods is to understand novel attack scenarios and design a model to detect novel and more serious attacks. In this paper, we investigate network attacks and unveil the key activities and the relationships between these activities. For that reason, we propose methods to understand the network security practices using theoretic concepts such as graph kernels. In addition, we integrate graph kernels over deep learning architecture to exploit the relationship expressiveness among network flows and combine ability of deep neural networks (DNNs) with deep architectures to learn hidden representations, based on the communication representation graph of each network flow in a specific time interval, then the flow-based network attack detection can be done effectively by measuring the similarity between the graphs to two flows. The proposed study provides the effectiveness to obtain insights about network attacks and detect network attacks. Using two real-world datasets which contain several new types of network attacks, we achieve significant improvements in accuracies over existing network attack detection tasks.
Su, Qiankun, Jaffres-Runser, Katia, Jakllari, Gentian, Poulliat, Charly.  2016.  An Efficient Content Delivery Infrastructure Leveraging the Public Transportation Network. Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. :338–347.

With the world population becoming increasingly urban and the multiplication of mega cities, urban leaders have responded with plans calling for so called smart cities relying on instantaneous access to information using mobile devices for an intelligent management of resources. Coupled with the advent of the smartphone as the main platform for accessing the Internet, this has created the conditions for the looming wireless bandwidth crunch. This paper presents a content delivery infrastructure relying on off-the-shelf technology and the public transportation network (PTN) aimed at relieving the wireless bandwidth crunch in urban centers. Our solution proposes installing WiFi access points on selected public bus stations and buses and using the latter as data mules, creating a delay tolerant network capable of carrying content users can access while using the public transportation. Building such an infrastructure poses several challenges, including congestion points in major hubs and the cost of additional hardware necessary for secure communications. To address these challenges we propose a 3-Tier architecture that guarantees end-to-end delivery and minimizes hardware cost. Trace-based simulations from three major European cities of Paris, Helsinki and Toulouse demonstrate the viability of our design choices. In particular, the 3-Tier architecture is shown to guarantee end-to-end connectivity and reduce the deployment cost by several times while delivering at least as many packets as a baseline architecture.

Su, W., Antoniou, A., Eagle, C..  2017.  Cyber Security of Industrial Communication Protocols. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). :1–4.

In this paper, an industrial testbed is proposed utilizing commercial-off-the-shelf equipment, and it is used to study the weakness of industrial Ethernet, i.e., PROFINET. The investigation is based on observation of the principles of operation of PROFINET and the functionality of industrial control systems.

Su, Wei-Tsung, Chen, Wei-Cheng, Chen, Chao-Chun.  2019.  An Extensible and Transparent Thing-to-Thing Security Enhancement for MQTT Protocol in IoT Environment. 2019 Global IoT Summit (GIoTS). :1—4.

Message Queue Telemetry Transport (MQTT) is widely accepted as a data exchange protocol in Internet of Things (IoT) environment. For security, MQTT supports Transport Layer Security (MQTT-TLS). However, MQTT-TLS provides thing-to-broker channel encryption only because data can still be exposed after MQTT broker. In addition, ACL becomes impractical due to the increasing number of rules for authorizing massive IoT devices. For solving these problems, we propose MQTT Thing-to-Thing Security (MQTT-TTS) which provides thing-to-thing security which prevents data leak. MQTT-TTS also provides the extensibility to include demanded security mechanisms for various security requirements. Moreover, the transparency of MQTT-TTS lets IoT application developers implementing secure data exchange with less programming efforts. Our MQTT-TTS implementation is available on for evaluation.

Su, Yishan, Zhang, Ting, Jin, Zhigang, Guo, Lei.  2020.  An Anti-Attack Trust Mechanism Based on Collaborative Spectrum Sensing for Underwater Acoustic Sensor Networks. Global Oceans 2020: Singapore – U.S. Gulf Coast. :1—5.
The main method for long-distance underwater communication is underwater acoustic communication(UAC). The bandwidth of UAC channel is narrow and the frequency band resources are scarce. Therefore, it is important to improve the frequency band utilization of UAC system. Cognitive underwater acoustic (CUA) technology is an important method. CUA network can share spectrum resources with the primary network. Spectrum sensing (SS) technology is the premise of realizing CUA. Therefore, improving the accuracy of spectral sensing is the main purpose of this paper. However, the realization of underwater SS technology still faces many difficulties. First, underwater energy supplies are scarce, making it difficult to apply complex algorithms. Second, and more seriously, CUA network can sometimes be attacked and exploited by hostile forces, which will not only lead to data leakage, but also greatly affect the accuracy of SS. In order to improve the utilization of underwater spectrum and avoid attack, an underwater spectrum sensing model based on the two-threshold energy detection method and K of M fusion decision method is established. Then, the trust mechanism based on beta function and XOR operation are proposed to combat individual attack and multi-user joint attack (MUJA) respectively. Finally, simulation result shows the effectiveness of these methods.
Su, Yu, Wu, Jing, Long, Chengnian, Li, Shaoyuan.  2018.  Event-triggered Control for Networked Control Systems Under Replay Attacks. 2018 Chinese Automation Congress (CAC). :2636—2641.
With wide application of networked control systems(N CSs), NCSs security have encountered severe challenges. In this paper, we propose a robust event-triggered controller design method under replay attacks, and the control signal on the plant is updated only when the event-triggering condition is satisfied. We develop a general random replay attack model rather than predetermined specific patterns for the occurrences of replay attacks, which allows to obtain random states to replay. We show that the proposed event-triggered control (ETC) scheme, if well designed, can tolerate some consecutive replay attacks, without affecting the corresponding closed-loop system stability and performance. A numerical examples is finally given to illustrate the effectiveness of our method.
Su, Yu, Zhou, Jian, Guo, Zhinuan.  2020.  A Trust-Based Security Scheme for 5G UAV Communication Systems. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :371—374.
As the increasing demands of social services, unmanned aerial vehicles (UAVs)-assisted networks promote the promising prospect for implementing high-rate information transmission and applications. The sensing data can be collected by UAVs, a large number of applications based on UAVs have been realized in the 5G networks. However, the malicious UAVs may provide false information and destroy the services. The 5G UAV communication systems face the security threats. Therefore, this paper develops a novel trust-based security scheme for 5G UAV communication systems. Firstly, the architecture of the 5G UAV communication system is presented to improve the communication performance. Secondly, the trust evaluation scheme for UAVs is developed to evaluate the reliability of UAVs. By introducing the trust threshold, the malicious UAVs will be filtered out from the systems to protect the security of systems. Finally, the simulation results have been demonstrated the effectiveness of the proposed scheme.
Su, Z., Song, C., Dai, L., Ge, F., Yang, R., Biennier, F..  2017.  A security criteria regulation middleware using security policy for Web Services on multi-Cloud tenancies. 2017 3rd International Conference on Computational Intelligence Communication Technology (CICT). :1–5.

In the multi-cloud tenancy environments, Web Service offers an standard approach for discovering and using capabilities in an environment that transcends ownership domains. This brings into concern the ownership and security related to Web Service governance. Our approach for this issue involves an ESB-integrated middleware for security criteria regulation on Clouds. It uses an attribute-based security policy model for the exhibition of assets consumers' security profiles and deducing service accessing decision. Assets represent computing power/functionality and information/data provided by entities. Experiments show the middleware to bring minor governance burdens on the hardware aspect, as well as better performance with colosum scaling property, dealing well with cumbersome policy files, which is probably the situation of complex composite service scenarios.

Suarez, Drew, Mayer, Daniel.  2016.  Faux Disk Encryption: Realities of Secure Storage on Mobile Devices. Proceedings of the International Conference on Mobile Software Engineering and Systems. :283–284.

This paper reviews the challenges faced when securing data on mobile devices. After a discussion of the state-of-the-art of secure storage for iOS and Android, the paper introduces an attack which demonstrates how Full Disk Encryption (FDE) on Android can be ineffective in practice.

Suarez, Drew, Mayer, Daniel.  2016.  Faux Disk Encryption: Realities of Secure Storage on Mobile Devices. Proceedings of the International Conference on Mobile Software Engineering and Systems. :283–284.

This paper reviews the challenges faced when securing data on mobile devices. After a discussion of the state-of-the-art of secure storage for iOS and Android, the paper introduces an attack which demonstrates how Full Disk Encryption (FDE) on Android can be ineffective in practice.

Subahi, Alanoud, Theodorakopoulos, George.  2018.  Ensuring Compliance of IoT Devices with Their Privacy Policy Agreement. 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud). :100–107.
In the past few years, Internet of Things (IoT) devices have emerged and spread everywhere. Many researchers have been motivated to study the security issues of IoT devices due to the sensitive information they carry about their owners. Privacy is not simply about encryption and access authorization, but also about what kind of information is transmitted, how it used and to whom it will be shared with. Thus, IoT manufacturers should be compelled to issue Privacy Policy Agreements for their respective devices as well as ensure that the actual behavior of the IoT device complies with the issued privacy policy. In this paper, we implement a test bed for ensuring compliance of Internet of Things data disclosure to the corresponding privacy policy. The fundamental approach used in the test bed is to capture the data traffic between the IoT device and the cloud, between the IoT device and its application on the smart-phone, and between the IoT application and the cloud and analyze those packets for various features. We test 11 IoT manufacturers and the results reveal that half of those IoT manufacturers do not have an adequate privacy policy specifically for their IoT devices. In addition, we prove that the action of two IoT devices does not comply with what they stated in their privacy policy agreement.
Subangan, S., Senthooran, V..  2019.  Secure Authentication Mechanism for Resistance to Password Attacks. 2019 19th International Conference on Advances in ICT for Emerging Regions (ICTer). 250:1—7.
Authentication is a process that provides access control of any type of computing applications by inspecting the user's identification with the database of authorized users. Passwords play the vital role in authentication mechanism to ensure the privacy of the information and avert from the illicit access. Password based authentication mechanism suffers from many password attacks such as shoulder surfing, brute forcing and dictionary attacks that crack the password of authentication schema by the adversary. Key Stroke technique, Click Pattern technique, Graphichical Password technique and Authentication panel are the several authentication techniques used to resist the password attacks in the literature. This research study critically reviews the types of password attacks and proposes a matrix based secure authentication mechanism which includes three phases namely, User generation phase, Matrix generation phase and Authentication phase to resist the existing password attacks. The performance measure of the proposed method investigates the results in terms existing password attacks and shows the good resistance to password attacks in any type of computing applications.
Subasi, A., Al-Marwani, K., Alghamdi, R., Kwairanga, A., Qaisar, S. M., Al-Nory, M., Rambo, K. A..  2018.  Intrusion Detection in Smart Grid Using Data Mining Techniques. 2018 21st Saudi Computer Society National Computer Conference (NCC). :1-6.

The rapid growth of population and industrialization has given rise to the way for the use of technologies like the Internet of Things (IoT). Innovations in Information and Communication Technologies (ICT) carries with it many challenges to our privacy's expectations and security. In Smart environments there are uses of security devices and smart appliances, sensors and energy meters. New requirements in security and privacy are driven by the massive growth of devices numbers that are connected to IoT which increases concerns in security and privacy. The most ubiquitous threats to the security of the smart grids (SG) ascended from infrastructural physical damages, destroying data, malwares, DoS, and intrusions. Intrusion detection comprehends illegitimate access to information and attacks which creates physical disruption in the availability of servers. This work proposes an intrusion detection system using data mining techniques for intrusion detection in smart grid environment. The results showed that the proposed random forest method with a total classification accuracy of 98.94 %, F-measure of 0.989, area under the ROC curve (AUC) of 0.999, and kappa value of 0.9865 outperforms over other classification methods. In addition, the feasibility of our method has been successfully demonstrated by comparing other classification techniques such as ANN, k-NN, SVM and Rotation Forest.

Subedi, K. P., Budhathoki, D. R., Chen, B., Dasgupta, D..  2017.  RDS3: Ransomware Defense Strategy by Using Stealthily Spare Space. 2017 IEEE Symposium Series on Computational Intelligence (SSCI). :1–8.

Ransomware attacks are becoming prevalent nowadays with the flourishing of crypto-currencies. As the most harmful variant of ransomware crypto-ransomware encrypts the victim's valuable data, and asks for ransom money. Paying the ransom money, however, may not guarantee recovery of the data being encrypted. Most of the existing work for ransomware defense purely focuses on ransomware detection. A few of them consider data recovery from ransomware attacks, but they are not able to defend against ransomware which can obtain a high system privilege. In this work, we design RDS3, a novel Ransomware Defense Strategy, in which we Stealthily back up data in the Spare space of a computing device, such that the data encrypted by ransomware can be restored. Our key idea is that the spare space which stores the backup data is fully isolated from the ransomware. In this way, the ransomware is not able to ``touch'' the backup data regardless of what privilege it can obtain. Security analysis and experimental evaluation show that RDS3 can mitigate ransomware attacks with an acceptable overhead.

Subramani, K. S., Antonopoulos, A., Abotabl, A. A., Nosratinia, A., Makris, Y..  2017.  INFECT: INconspicuous FEC-based Trojan: A hardware attack on an 802.11a/g wireless network. 2017 IEEE International Symposium on Hardware Oriented Security and Trust (HOST). :90–94.

We discuss the threat that hardware Trojans (HTs) impose on wireless networks, along with possible remedies for mitigating the risk. We first present an HT attack on an 802.11a/g transmitter (TX), which exploits Forward Error Correction (FEC) encoding. While FEC seeks to protect the transmitted signal against channel noise, it often offers more protection than needed by the actual channel. This margin is precisely where our HT finds room to stage an attack. We, then, introduce a Trojan-agnostic method which can be applied at the receiver (RX) to detect such attacks. This method monitors the noise distribution, to identify systematic inconsistencies which may be caused by an HT. Lastly, we describe a Wireless open-Access Research Platform (WARP) based experimental setup to investigate the feasibility and effectiveness of the proposed attack and defense. More specifically, we evaluate (i) the ability of a rogue RX to extract the leaked information, while an unsuspecting, legitimate RX accurately recovers the original message and remains oblivious to the attack, and (ii) the ability of channel noise profiling to detect the presence of the HT.

Subramani, Shweta, Vouk, Mladen, Williams, Laurie.  2014.  An Analysis of Fedora Security Profile. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :35:1–35:2.

This paper examines security faults/vulnerabilities reported for Fedora. Results indicate that, at least in some situations, fault roughly constant may be used to guide estimation of residual vulnerabilities in an already released product, as well as possibly guide testing of the next version of the product.

Subramanya, Supreeth, Mustafa, Zain, Irwin, David, Shenoy, Prashant.  2016.  Beyond Energy-Efficiency: Evaluating Green Datacenter Applications for Energy-Agility. Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering. :185–196.

Computing researchers have long focused on improving energy-efficiency under the implicit assumption that all energy is created equal. Yet, this assumption is actually incorrect: energy's cost and carbon footprint vary substantially over time. As a result, consuming energy inefficiently when it is cheap and clean may sometimes be preferable to consuming it efficiently when it is expensive and dirty. Green datacenters adapt their energy usage to optimize for such variations, as reflected in changing electricity prices or renewable energy output. Thus, we introduce energy-agility as a new metric to evaluate green datacenter applications. To illustrate fundamental tradeoffs in energy-agile design, we develop GreenSort, a distributed sorting system optimized for energy-agility. GreenSort is representative of the long-running, massively-parallel, data-intensive tasks that are common in datacenters and amenable to delays from power variations. Our results demonstrate the importance of energy-agile design when considering the benefits of using variable power. For example, we show that GreenSort requires 31% more time and energy to complete when power varies based on real-time electricity prices versus when it is constant. Thus, in this case, real-time prices should be at least 31% lower than fixed prices to warrant using them.

Subramanyan, P., Tsiskaridze, N., Wenchao Li, Gascon, A., Wei Yang Tan, Tiwari, A., Shankar, N., Seshia, S.A., Malik, S..  2014.  Reverse Engineering Digital Circuits Using Structural and Functional Analyses. Emerging Topics in Computing, IEEE Transactions on. 2:63-80.

Integrated circuits (ICs) are now designed and fabricated in a globalized multivendor environment making them vulnerable to malicious design changes, the insertion of hardware Trojans/malware, and intellectual property (IP) theft. Algorithmic reverse engineering of digital circuits can mitigate these concerns by enabling analysts to detect malicious hardware, verify the integrity of ICs, and detect IP violations. In this paper, we present a set of algorithms for the reverse engineering of digital circuits starting from an unstructured netlist and resulting in a high-level netlist with components such as register files, counters, adders, and subtractors. Our techniques require no manual intervention and experiments show that they determine the functionality of >45% and up to 93% of the gates in each of the test circuits that we examine. We also demonstrate that our algorithms are scalable to real designs by experimenting with a very large, highly-optimized system-on-chip (SOC) design with over 375000 combinational elements. Our inference algorithms cover 68% of the gates in this SOC. We also demonstrate that our algorithms are effective in aiding a human analyst to detect hardware Trojans in an unstructured netlist.

Subramanyan, Pramod, Sinha, Rohit, Lebedev, Ilia, Devadas, Srinivas, Seshia, Sanjit A..  2017.  A Formal Foundation for Secure Remote Execution of Enclaves. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2435–2450.

Recent proposals for trusted hardware platforms, such as Intel SGX and the MIT Sanctum processor, offer compelling security features but lack formal guarantees. We introduce a verification methodology based on a trusted abstract platform (TAP), a formalization of idealized enclave platforms along with a parameterized adversary. We also formalize the notion of secure remote execution and present machine-checked proofs showing that the TAP satisfies the three key security properties that entail secure remote execution: integrity, confidentiality and secure measurement. We then present machine-checked proofs showing that SGX and Sanctum are refinements of the TAP under certain parameterizations of the adversary, demonstrating that these systems implement secure enclaves for the stated adversary models.

Suciu, George, Hussain, Ijaz, Petrescu, Gabriel.  2020.  Role of Ubiquitous Computing and Mobile WSN Technologies and Implementation. 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE). :1–6.
Computing capabilities such as real time data, unlimited connection, data from sensors, environmental analysis, automated decisions (machine learning) are demanded by many areas like industry for example decision making, machine learning, by research and military, for example GPS, sensor data collection. The possibility to make these features compatible with each domain that demands them is known as ubiquitous computing. Ubiquitous computing includes network topologies such as wireless sensor networks (WSN) which can help further improving the existing communication, for example the Internet. Also, ubiquitous computing is included in the Internet of Things (IoT) applications. In this article, it is discussed the mobility of WSN and its advantages and innovations, which make possible implementations for smart home and office. Knowing the growing number of mobile users, we place the mobile phone as the key factor of the future ubiquitous wireless networks. With secure computing, communicating, and storage capacities of mobile devices, they can be taken advantage of in terms of architecture in the sense of scalability, energy efficiency, packet delay, etc. Our work targets to present a structure from a ubiquitous computing point of view for researchers who have an interest in ubiquitous computing and want to research on the analysis, to implement a novel method structure for the ubiquitous computing system in military sectors. Also, this paper presents security and privacy issues in ubiquitous sensor networks (USN).