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| Section | Objectives |
|---|---|
| Key Management and PKI | - Certificates, certificate authorities, and PKI structure - Key exchange and lifecycle management |
| Hash Functions and Message Authentication | - MAC and HMAC mechanisms - Cryptographic hash functions (e.g., SHA family concepts) |
| Cryptographic Protocols and Applications | - TLS/SSL conceptual overview - Secure communication design principles |
| Foundations of Cryptography | - Core concepts of confidentiality, integrity, authentication, non-repudiation - Historical and modern cryptography principles |
| Asymmetric Encryption | - Public key cryptography principles - RSA and ECC fundamentals |
| Symmetric Encryption | - Block and stream ciphers - AES and legacy algorithms (e.g., DES conceptually) |
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NEW QUESTION # 17
(Which number generator has different results given the same input data?)
Answer: B
Explanation:
A true random number generator (TRNG) produces outputs derived from nondeterministic physical processes (e.g., thermal noise, oscillator jitter, radioactive decay, or other hardware entropy sources). Because the underlying phenomenon is not algorithmically determined by an input seed in the same way as a PRNG, repeated "inputs" (or identical conditions from a software perspective) do not yield the same sequence; the outputs vary unpredictably. By contrast, a pseudorandom number generator (PRNG) is deterministic: given the same seed and internal state, it produces the same output sequence, which is useful for repeatability but means security depends on seed secrecy and proper seeding. "Prime" is not a generator type, and "sequence" is too generic and does not imply nondeterminism. In cryptographic systems, TRNGs (or hardware entropy sources) are often used to seed cryptographically secure PRNGs (CSPRNGs), combining high-quality entropy with efficient generation. Therefore, the generator that can produce different results for the "same input data" is a true random number generator.
NEW QUESTION # 18
(How does a cryptographic policy contribute to incident response?)
Answer: C
Explanation:
A cryptographic policy defines how encryption, keys, certificates, and integrity mechanisms are used and managed across an organization. During incident response, that policy becomes a playbook for making safe, consistent decisions under pressure. It can specify how to rotate or revoke compromised keys, how to validate and reissue certificates, how to preserve evidence integrity with hashing, and how to securely communicate sensitive incident details (e.g., using approved encrypted channels). It can also define backup encryption requirements and key escrow or recovery procedures, enabling secure data recovery without exposing protected data. Policies typically outline roles and responsibilities (who can access keys, who can approve rekeying), logging requirements, and escalation steps-reducing confusion and preventing ad hoc crypto changes that might worsen exposure. The goal is not to limit encryption; it is to ensure cryptography is used correctly to contain and remediate incidents. Therefore, providing guidelines for secure recovery and communication is the correct contribution of cryptographic policy to incident response.
NEW QUESTION # 19
(Why should a forensic investigator create a hash of a victim's hard drive and of the bitstream copy of the hard drive?)
Answer: A
Explanation:
In digital forensics, investigators must preserve evidence integrity and demonstrate an unbroken chain of custody. Creating a cryptographic hash (such as SHA-256) of the original drive and then hashing the forensic bitstream image provides a strong mathematical assurance that the copy is an exact, bit-for-bit replica. Because secure hash functions are designed so that any tiny change in data produces a dramatically different digest, matching hashes indicate the image contains identical data to the source at the time of acquisition. This is critical in legal and investigative contexts: analysis is performed on the copy, not the original, to avoid altering evidence. If the hashes match, the investigator can testify that the evidence examined is identical to what was collected, supporting admissibility and credibility.
Hashing does not prove who created files, nor does it directly show whether someone "opened the drive"; it specifically validates the integrity and equivalence of the captured image. Therefore, hashing both artifacts is done to verify that the original and the bitstream copy are identical.
NEW QUESTION # 20
(Why did the National Institute of Standards and Technology (NIST) choose Ascon for lightweight cryptography?)
Answer: B
Explanation:
NIST's lightweight cryptography effort targets environments like IoT and embedded systems where CPU, memory, energy, and bandwidth are constrained, yet strong security is still required. Ascon is an authenticated encryption with associated data (AEAD) family designed to be efficient in both hardware and software with small footprint, making it well-suited for constrained devices. NIST selected Ascon because it offers a strong security design with good performance and implementability under tight resource budgets, while providing modern protections (confidentiality + integrity) through AEAD. That aligns with option C: secure and efficient encryption for resource-constrained devices. The selection was not primarily about authenticating users (that is typically handled by protocols and identity systems, not an AEAD primitive). It was also not mainly about legacy compatibility; lightweight cryptography aims at new and constrained deployments rather than preserving outdated stacks. And while Ascon can certainly be used to protect data at rest, that is only one application; the core reason for the choice is its suitability for constrained environments and robust, efficient authenticated encryption.
NEW QUESTION # 21
(What describes a true random number generator?)
Answer: C
Explanation:
A true random number generator (TRNG) draws randomness from physical phenomena that are inherently unpredictable and not algorithmically reproducible. Because of this, it is nondeterministic: you cannot feed it the same "input" and expect the same output stream. TRNGs are often slower than PRNGs because they depend on collecting entropy from hardware sources and may require conditioning to remove bias. This aligns with option B: slow and nondeterministic, producing different results even under similar or repeated conditions. Option A describes a deterministic PRNG, where identical seeds yield identical sequences. Option C is unrelated; factorization is a hard math problem used in cryptography (e.g., RSA security assumptions), not a randomness generator definition. Option D describes a counter, which is deterministic and not random.
In secure systems, TRNG output may seed a cryptographically secure PRNG to provide both unpredictability and high throughput; but the defining characteristic of a TRNG is nondeterminism from physical entropy.
Therefore, option B is correct.
NEW QUESTION # 22
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