CWISA-103 Practice Questions

Security is a fundamental requirement that must be integrated into every phase of a project's lifecycle, beginning at its inception. This principle is often referred to as "security by design." The planning phase is the earliest and most critical stage to define security requirements, policies, and architecture. Addressing security from the start ensures that the entire wireless implementation is built on a secure foundation, which is far more effective and less costly than attempting to add security measures during or after implementation. Waiting until later phases introduces significant risk and often requires expensive rework.

A. During hand-off to support: This is far too late. The system is already designed and built; discovering security needs at this point would be a catastrophic failure in project management.

C. In the implementation phase: While security controls are configured during implementation, the requirements and overall design must be established during the preceding planning phase.

D. In the acceptance testing phase: This phase is for validating that the implementation meets the pre-defined requirements. Introducing new security considerations here indicates a major planning oversight.

1. National Institute of Standards and Technology (NIST) Special Publication 800-64 Rev. 2, Security Considerations in the System Development Life Cycle.

Reference: Section 2.1, "Integrating Information Security into the SDLC," states, "The traditional system development life cycle (SDLC) consists of five phases: initiation, acquisition/development, implementation, operations/maintenance, and disposition. Security must be integrated into each of these phases." The "initiation" phase, where the need for a system is expressed and its purpose is documented, is analogous to the "planning phase" in the question.

2. Carnegie Mellon University, Software Engineering Institute (SEI), Security Quality Requirements Engineering (SQUARE).

Reference: The SQUARE methodology, a widely recognized academic and industry model, explicitly places security requirement elicitation and definition at the beginning of the development lifecycle, prior to architectural design and implementation. This reinforces the principle of addressing security in the earliest planning stages. (See technical reports like CMU/SEI-2005-TR-009).

3. MIT OpenCourseWare, 16.355J Software Engineering Concepts.

Reference: Course materials on the software development lifecycle emphasize that non-functional requirements, such as security, performance, and reliability, must be defined during the initial requirements and specification phase (the planning phase). Failing to do so is a common cause of project failure.

Radio-Frequency Identification (RFID) is the most prevalent technology for tracking and individually identifying livestock. Small, passive or active RFID tags are attached to animals, typically as ear tags. Each tag stores a unique identification number. When an animal passes near an RFID reader (e.g., at a feeding station, water trough, or gate), the reader wirelessly captures the unique ID. This allows for automated, individual tracking of location, health, feeding patterns, and other critical data, which is essential for managing large herds efficiently.

A. Photodiode sensors are used to detect light intensity and are not suitable for uniquely identifying individual animals.

C. 802.11 wireless radios (Wi-Fi) are too complex, costly, and power-intensive for simple, per-animal identification on a large scale.

D. Thermistor sensors measure temperature and are used for health monitoring (e.g., detecting fever), but they do not provide a unique identity.

1. CWNP, "CWISA-103 Certified Wireless IoT Solutions Administrator Official Study Guide," (2020). Chapter 1, "What is IoT?", discusses various IoT verticals and use cases, including smart agriculture (agritech), where RFID is a foundational technology for asset and livestock tracking.

2. Kamilaris, A., & Prenafeta-Boldú, F. X. (2018). "Deep learning in agriculture: A survey." Computers and Electronics in Agriculture, 147, 70-90. Section 3.1, "Livestock Monitoring," explicitly details the use of RFID tags for the identification and tracking of individual animals to monitor their behavior and health. DOI: https://doi.org/10.1016/j.compag.2018.02.016

3. Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). "Internet of Things in agriculture, recent advances and future challenges." Biosystems Engineering, 164, 31-48. The paper reviews IoT technologies in agriculture, identifying RFID in Section 2.2 as a key technology for "animal identification and traceability," which is fundamental to modern livestock management. DOI: https://doi.org/10.1016/j.biosystemseng.2017.09.007

LoRa (Long Range) is a proprietary physical layer (PHY) modulation technique developed by Semtech. It is based on Chirp Spread Spectrum (CSS) modulation. In CSS, data is encoded using "chirps," which are signals that continuously vary in frequency, either increasing (up-chirp) or decreasing (down-chirp) over a specific bandwidth. This spread spectrum method allows the signal to be received even when it is below the noise floor, providing excellent robustness against interference and enabling long-range, low-power communication, which is ideal for IoT applications.

A. OFDMA (Orthogonal Frequency-Division Multiple Access) is a multi-user access scheme used in high-throughput technologies like Wi-Fi 6 (802.11ax) and 5G, not in LoRa.

C. ASK (Amplitude-Shift Keying) is a simpler modulation where data is represented by variations in the carrier signal's amplitude, which lacks the range and interference resilience of LoRa's CSS.

D. OFDM (Orthogonal Frequency-Division Multiplexing) is a modulation technique used for high-data-rate communications like Wi-Fi (802.11a/g/n/ac) and LTE, which is fundamentally different from LoRa's low-rate, long-range approach.

1. Semtech Corporation. (2020). AN1200.22 - LoRa® Modulation Basics. Section 2, "LoRa Modulation," Paragraph 1. "The LoRa modulation is a proprietary technology, based on the Chirp Spread Spectrum (CSS) modulation, which has been used in military and space communication for decades."

2. Haxhibeqiri, J., De Poorter, E., Moerman, I., & Hoebeke, J. (2018). A Survey of LoRaWAN for IoT: From Technology to Application. Sensors, 18(11), 3995. Section 2.1, "LoRa Physical Layer," Paragraph 1. "LoRa is a proprietary modulation format owned by Semtech, based on Chirp Spread Spectrum (CSS) modulation." DOI: https://doi.org/10.3390/s18113995

3. Bor, M., Roedig, U., Voigt, T., & Alonso, J. M. (2016). Do LoRa Low-Power Wide-Area Networks Scale? In Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM '16). Association for Computing Machinery, New York, NY, USA, 59–67. Section 2, "LoRa and LoRaWAN," Paragraph 1. "LoRa is a proprietary spread-spectrum modulation scheme that is a derivative of Chirp Spread Spectrum (CSS) modulation." DOI: https://doi.org/10.1145/2988287.2989163

The Institute of Electrical and Electronics Engineers (IEEE) is a global professional organization whose primary function in the technology sector is to foster innovation and develop consensus-based global standards. Through its IEEE Standards Association (IEEE SA), it manages the development of technical specifications that form the foundation for new technologies. For wireless, its most notable contribution is the IEEE 802.11 family of standards, which defines the physical (PHY) and medium access control (MAC) layers for Wi-Fi. This standards development process is crucial for promoting technological advancement and ensuring a baseline for interoperability.

B. Designs wireless chipsets: This is the function of semiconductor manufacturers like Qualcomm, Broadcom, and Intel, not a standards development organization like the IEEE.

C. Certified equipment to be compatible: This is the primary role of the Wi-Fi Alliance, which creates certification programs (e.g., Wi-Fi CERTIFIED™) to ensure interoperability based on the IEEE 802.11 standards.

D. Brings wireless products to market: This is the responsibility of Original Equipment Manufacturers (OEMs) and vendors such as Apple, Cisco, and Samsung who build and sell end-user devices.

---

1. IEEE Standards Association. (n.d.). About IEEE SA. Retrieved from the official IEEE website. The site states, "The IEEE Standards Association (IEEE SA) is a leading consensus-building organization that nurtures, develops and advances global technologies, through the IEEE." This directly supports the function of standards development and technology promotion. (Source: https://standards.ieee.org/about/)

2. Kurose, J. F., & Ross, K. W. (2021). Computer Networking: A Top-Down Approach (8th ed.). Pearson. In Chapter 7, Section 7.3, the text distinguishes the roles of standards bodies, stating, "The IEEE 802.11 standards define the physical and link layers for wireless LANs... The Wi-Fi Alliance is a nonprofit organization that tests and certifies 802.11 products for interoperability." This university-level textbook clarifies the separate functions of the IEEE (standards development) and the Wi-Fi Alliance (certification).

3. Crow, B. P., Widjaja, I., Kim, J. G., & Sakai, P. T. (1997). IEEE 802.11 Wireless Local Area Networks. IEEE Communications Magazine, 35(9), 116-126. This peer-reviewed article details the history and process of the IEEE 802.11 working group's efforts to "develop a standard for wireless local area networks (LANs)," confirming the IEEE's role in standards development. (DOI: https://doi.org/10.1109/35.620533)

The IEEE 802.15.4 standard, upon which ZigBee is based, specifies the 2.4 GHz Industrial, Scientific, and Medical (ISM) band for worldwide operation. This band is also heavily utilized by IEEE 802.11 (Wi-Fi) networks, leading to significant potential for co-channel and adjacent-channel interference. The most effective method to mitigate this interference is to ensure the two technologies operate in completely separate, non-overlapping frequency bands. By moving all 802.11 communications to the 5 GHz band, the ZigBee network can operate in the 2.4 GHz band without contention from Wi-Fi signals, thus providing the most comprehensive interference minimization.

A. ZigBee is not defined by the IEEE 802.15.4 standard to operate in the 6 GHz band.

C. ZigBee is not defined by the IEEE 802.15.4 standard to operate in the 5 GHz band.

D. This action would force both networks to compete for the same 2.4 GHz spectrum, maximizing interference rather than minimizing it.

1. IEEE Std 802.15.4™-2020, IEEE Standard for Low-Rate Wireless Networks. Clause 10, "2450 MHz PHY," specifies the physical layer parameters for operation in the 2400–2483.5 MHz band, which is the worldwide band for ZigBee.

2. IEEE Std 802.11™-2020, IEEE Standard for Information Technology...Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Annex E, "Channel numbering across regulatory domains," details the channelization for 802.11 operation in both the 2.4 GHz and 5 GHz bands.

3. Sikora, A., & Groza, V. F. (2005). Coexistence of IEEE 802.15.4 with other systems in the 2.4 GHz-ISM-Band. IEEE Instrumentation and Measurement Technology Conference Proceedings. Section IV, "Coexistence Improvement," discusses frequency separation as a primary mitigation strategy, stating, "The most obvious but also most effective method is to use different frequency bands for the different systems (e.g. IEEE 802.11a in the 5 GHz band)." DOI: 10.1109/IMTC.2005.1604455

The simplified three-layer IoT model consists of the Perception, Network, and Application layers. The Perception layer, also known as the device or sensing layer, forms the physical base of the IoT system. Its fundamental purpose is to interact directly with the physical world. It uses sensors, RFID tags, and other devices to "perceive" the environment by collecting data such as temperature, location, or motion. This raw data is then passed to the Network layer for transmission. Therefore, its universal primary function is to gather and initiate the transmission of data for subsequent analysis, reporting, or action.

B. Analyzing data for actions and reporting using AI and ML is the primary function of the Application layer, which processes the data to deliver services.

C. This describes a specific security operation, not a primary layer function. Furthermore, sending data over an unencrypted network is contrary to security best practices.

D. Providing the network for data transmission is the core responsibility of the Network layer, which sits between the Perception and Application layers.

1. Ray, P. P. (2018). A survey on Internet of Things architectures. Journal of King Saud University-Computer and Information Sciences, 30(3), 291-319. In Section 3.1, "Three-Layer Architecture," the paper states, "The first layer is the Perception layer, which is the physical layer... It senses and gathers information about the environment." (p. 293). https://doi.org/10.1016/j.jksuci.2016.10.003

2. Sethuraman, S. C., & T., Y. J. (2017). A study of architectures in internet of things (IoT). In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) (pp. 697-702). IEEE. The paper describes the three-layer model, stating, "Perception Layer: This is the physical layer, which has sensors for sensing and gathering information about the environment." (p. 698). https://doi.org/10.1109/I-SMAC.2017.8058399

3. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660. The article discusses a generic architecture where the lowest layer is responsible for "data acquisition from the environment," which corresponds to the Perception layer's function. (Section 3.1, p. 1648). https://doi.org/10.1016/j.future.2013.01.010

The fundamental difference between Amplitude-Shift Keying (ASK) and Frequency-Shift Keying (FSK) lies in which property of the carrier wave is modified to encode data. In ASK, the amplitude of a constant-frequency carrier wave is varied to represent binary data (e.g., high amplitude for '1', low/zero amplitude for '0'). In contrast, FSK maintains a constant amplitude carrier wave but shifts its frequency between two or more discrete values to represent the data (e.g., frequency f1 for '1', frequency f2 for '0'). This distinction is the defining characteristic of each modulation scheme.

B. FSK is more sensitive to noise than ASK

This is incorrect. ASK is generally more susceptible to noise and interference because these phenomena often manifest as amplitude variations, which can be misinterpreted as data by an ASK receiver.

C. ASK does not work at high frequencies

This is false. Both ASK and FSK are used across a wide spectrum, including high-frequency (HF), very-high-frequency (VHF), and ultra-high-frequency (UHF) bands, depending on the application.

D. ASK can carry more data than FSK

This statement is not universally true. The data rate depends on factors like available bandwidth, signal-to-noise ratio, and the specific variant of the modulation. Neither scheme is inherently superior in all scenarios.

1. Madhow, U. (2014). Introduction to Communication Systems. Cambridge University Press.

Page 168, Section 5.1: "In amplitude shift keying (ASK), the transmitted signal corresponding to bit b is sb(t) = Ab cos(2πfc t), where A0 and A1 are two different amplitudes."

Page 173, Section 5.2: "In frequency shift keying (FSK), the transmitted signal corresponding to bit b is sb(t) = A cos(2πfb t), where f0 and f1 are two different frequencies near the carrier frequency fc."

2. Gallager, R. G. (2008). Course 6.450, Principles of Digital Communications I, Lecture Notes. MIT OpenCourseWare.

Lecture 10, Page 10-1: "In ASK, the information is carried in the amplitude of a sinusoid... In FSK, the information is carried in the frequency of a sinusoid."

3. Proakis, J. G., & Salehi, M. (2008). Digital Communications (5th ed.). McGraw-Hill.

Page 166, Section 4.2.2: Discusses the higher susceptibility of ASK to noise compared to FSK, stating, "amplitude-shift keying is a linear modulation method and, consequently, it is suboptimal in terms of power-efficiency." FSK is a non-linear modulation which provides better performance in the presence of noise.

A significant negative attribute of many consumer-targeted smart devices is their reliance on the 2.4 GHz Industrial, Scientific, and Medical (ISM) band. This frequency band is heavily congested as it is shared by various technologies, including 802.11 Wi-Fi (b/g/n/ax), Bluetooth, Zigbee, and other proprietary wireless protocols common in low-cost IoT devices. In a business environment, this concentration of devices leads to increased co-channel and adjacent-channel interference, which can degrade the performance and reliability of both the smart office devices and the primary business Wi-Fi network that employees and customers depend on.

A. While they may lack enterprise-grade management or security, many consumer devices have features that are adequate for a small business's basic operational needs.

C. This is incorrect. Consumer devices use a wide variety of modulation schemes, including DSSS and OFDM for Wi-Fi and O-QPSK for Zigbee, not just FHSS.

D. This is a generalization about product reliability and not a fundamental technical attribute. Device lifespan varies greatly and is not a guaranteed characteristic.

1. CWNP. (2021). CWISA-103 Certified Wireless IoT Solutions Administrator Official Study Guide. Chapter 2: Radio Frequency (RF) Technologies, pp. 38-40, discusses the 2.4 GHz ISM band and the numerous technologies (Wi-Fi, Bluetooth, Zigbee) that operate within it, highlighting its crowded nature. Chapter 6: The Internet of Things (IoT), pp. 167-185, details protocols like Zigbee and Bluetooth LE, which predominantly use the 2.4 GHz band.

2. Staniec, K., & Kowal, M. (2021). Experimental Study of Coexistence between IEEE 802.11ax and IEEE 802.15.4. Sensors, 21(19), 6439. This study experimentally analyzes the performance degradation due to interference between modern Wi-Fi (802.11ax) and a common IoT protocol (IEEE 802.15.4, the basis for Zigbee), both operating in the 2.4 GHz band. DOI: https://doi.org/10.3390/s21196439

3. MIT OpenCourseWare. (2011). 6.02 Introduction to EECS II: Digital Communication Systems, Fall 2011. Lecture 18: Wireless Communication. This lecture series discusses the properties of wireless channels, including the unlicensed ISM bands. It explains that the 2.4 GHz band is popular for low-cost consumer devices but is also "very crowded," leading to significant interference issues that must be managed. (Available at ocw.mit.edu).

A Wi-Fi enabled weight scale is classified as a non-wearable health IoT device. This category includes devices that are used for health monitoring but are not worn on the body. The scale is an external, often stationary, device that a user interacts with for a specific measurement at a point in time. It collects data (e.g., weight, body fat percentage) and transmits it wirelessly, but it is not designed for continuous, on-body use like a wearable or for internal use like an implantable device.

A. implantable: Incorrect. Implantable devices are surgically placed inside the human body for long-term monitoring or therapeutic purposes, such as a smart pacemaker or an implantable cardioverter-defibrillator (ICD).

B. wearable: Incorrect. Wearable devices are designed to be worn on the body for continuous or frequent data collection. Examples include smartwatches, fitness trackers, and smart clothing.

D. injectable: Incorrect. Injectable IoT devices are typically microscopic sensors or nanobots that are introduced into the body via injection for highly specific internal monitoring, which is a distinct and more advanced category.

1. CWNP. (2021). CWISA-103 Certified Wireless IoT Solutions Administrator Official Study Guide. Chapter 5: IoT Verticals and Industries, Section: "Healthcare," pp. 168-171. The guide categorizes healthcare IoT devices based on their application and form factor, distinguishing between wearables (e.g., fitness bands), implantables (e.g., pacemakers), and stationary/environmental monitoring devices, where a smart scale would be classified.

2. Al-Turjman, F., & De, S. (2020). Mobility in the Internet of Things. IET. In Chapter 3, "IoT in Healthcare," the text discusses the taxonomy of medical IoT devices, differentiating between on-body sensors (wearables), in-body sensors (implantables), and off-body devices (environmental or home-based), which include smart scales and blood pressure monitors.

3. Yin, Y., Zeng, Y., Chen, X., & Fan, Y. (2016). The internet of things in healthcare: An overview. Journal of Industrial Information Integration, 1, 3-13. https://doi.org/10.1016/j.jii.2016.03.004. This paper's Figure 1 provides a conceptual framework for healthcare IoT, categorizing devices. A smart scale falls under "Health & Wellness" monitoring devices that are used in a "Personal Area Network" but are not classified as wearable or implantable.

Free Space Path Loss (FSPL) is the fundamental concept describing the reduction in signal strength (attenuation) of an electromagnetic wave as it propagates through a line-of-sight path in free space. This loss is not due to absorption by a medium but is a natural consequence of the signal's energy spreading out over a larger area as it moves away from the transmitter. According to the inverse-square law, the power density of the RF signal decreases proportionally to the square of the distance from the source. FSPL is a critical, predictable component in calculating the link budget for any wireless system.

A. RF latency: This refers to the time delay for a signal to travel from the transmitter to the receiver, not the loss of signal strength.

C. Beamwidth: This is a specification of an antenna, defining the angular width of its main radiation lobe, which relates to directivity, not signal loss over distance.

D. Diffraction: This is a specific RF behavior where waves bend around an obstacle, which is different from the general signal weakening that occurs in unobstructed space.

1. Goldsmith, A. (2005). Wireless Communications. Cambridge University Press. In Chapter 2, Section 2.5, "Path Loss Models," the text introduces the free-space path loss model, stating, "This model predicts that received power decays as the square of the T-R separation distance." (p. 39).

2. Rappaport, T. S. (2002). Wireless Communications: Principles and Practice (2nd ed.). Prentice Hall. Chapter 4, "Mobile Radio Propagation: Large-Scale Path Loss," introduces the Free Space Propagation Model, explaining that it is used to "predict received signal strength when the transmitter and receiver have a clear, unobstructed line-of-sight path between them." The Friis free space equation is presented to quantify this loss as a function of distance and frequency. (pp. 102-104).

3. MIT OpenCourseWare. (2011). 6.02 Introduction to EECS II: Digital Communication Systems, Fall 2011. Massachusetts Institute of Technology. Lecture 15 notes, "Wireless Communication," describe path loss: "As the signal propagates from the transmitter, its energy spreads out. This is a 'good' effect... but it also means that the power of the signal falls with distance." The notes explicitly link this to the inverse square law. (p. 2). Available at: https://ocw.mit.edu/courses/6-02-introduction-to-eecs-ii-digital-communication-systems-fall-2011/resources/lecture-15-wireless-communication/