arXiv subjects

Muhammad Shaheer Bin Junaid

Publications and source records attributed to Muhammad Shaheer Bin Junaid.

4 recordsLinked to original sources

arXiv2026

Zirah: A Post-Quantum True Random Number Generator Hardware Signer With an Avalanche Noise

Zirah is a hardware signer built around an STM32F407 microcontroller, and its purpose is to find out, on inexpensive hardware, where a post-quantum signing key is exposed and what actually protects it. The device draws every random bit from a reverse-biased 2N3904 junction in avalanche breakdown, amplified by an LM358 and screened by SP 800-90B health tests, computes ML-DSA-65 (FIPS 204, hedged) on the STM32 with two-share arithmetic masking of the secret-key multiplications, and adds ECDSA P-256 from an ATECC608 secure element over the same digest, once a person has matched an eight-digit digest prefix on its OLED with the PC and pressed a button. A desktop application and a command-line tool drive the board and verify its output, and because only a 32-byte manifest digest reaches the device, it signs files of any type and size, returning signed copies for PDF, Office Open XML, ZIP, PNG and JPEG files and detached records for every other format. NIST's SP 800-90B tool rejected the IID assumption for 1,000,000 raw samples and assessed 6.898 bits of min-entropy per byte on the non-IID track, against the 1 bit the firmware credits, while spectral lines near 116 Hz that hold about 5 % of the variance remain unexplained. At 168 MHz the masked signature took a median of 157 ms over 20 runs and a complete signing operation under 0.8 s, and the signer matched the pq-crystals reference in 1,976 checks natively and on an emulated Cortex-M4. The ATECC608 can neither store the 4,032-byte ML-DSA-65 key nor compute with it, so that key sits in ordinary flash behind readout protection, and on an earlier board, before that protection was enabled, a debugger copied it out and the copy produced a valid ML-DSA-65 signature without the device, although the leakage results come from an instruction-level emulator and nothing here is certified.

cs.CR↗

arXiv2026

Quantum Machine Learning Protection of Military Quantum Key Distribution Against Cryptographically Camouflaged Attacks

Quantum key distribution proves its protocol secure and says nothing about the hardware beneath it, so military and government operators fielding it for command-and-control keys monitor the channel for implementation attacks, and that monitoring has a blind spot. An adversary with a kleptographic foothold in the generator of a public per-block value \(x=g^v \pmod p\) can hide attacked blocks in honest noise, gating them on a predicate of its discrete logarithm, making detection a discrete logarithm problem that defeats every efficient classical monitor yet yields to a quantum kernel recovering \(v\) through Shor's algorithm. I formalise these cryptographically camouflaged attacks, reduce their hardness to an established learning separation, prove a single-frequency fidelity kernel cannot represent an interval predicate, and test them on Ghillie, a decoy-state BB84 simulator with a positive key rate to 142 km. From 10- to 14-bit groups over two seeds, a classical monitor reads 0.458 to 0.516 on camouflaged attacks while the quantum kernel reads 1.000, and both catch overt attacks above 0.99. Finite-precision recovery under depolarising noise and a hardened predicate lower the quantum result to 0.916 through 0.983 with the classical monitor at chance, and a feasibility probe on IBM Heron processors tracks the exact kernel within 0.034. A defender can therefore discard precisely the compromised key material, although the advantage is asymptotic, awaits fault tolerance, and holds only when the feature map matches the adversary's predicate, since a low-frequency map reads 0.545 on a residue pattern and 0.982 once aligned.

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arXiv2026

Static Detection of Post-Quantum Cryptographic Algorithms in Stripped Binaries for Digital Forensic Examination and Migration Assurance

Identifying which post-quantum algorithm a compiled binary implements is a core problem in binary analysis, and it becomes acute once the binary has been stripped, statically linked, and optimised, since the symbols, library dependencies, and runtime behaviour that conventional discovery tools rely on are then gone. This paper presents Kestrel, a static analysis method that identifies an algorithm from the number-theoretic transform constant tables its arithmetic depends on, and applies it to the standardised lattice schemes ML-KEM and ML-DSA, for which no prior method could confirm, from a shipped binary alone, that a quantum-vulnerable algorithm had been replaced by its approved successor. The fingerprints Kestrel derives from public scheme parameters are localised by a normalisation-and-multiset-matching procedure; the false-positive probability is established analytically. Across four independent implementation lineages and all build transformations, including compiler-level obfuscation, Kestrel achieved recall of 128 of 128 with zero false positives. Applied to 6,224 binaries on a production Linux system, it disclosed twelve uncatalogued programs containing ML-KEM, among them the OpenSSH key-exchange program and the container-management stack, where post-quantum code had entered production through the language runtime without the awareness of the projects distributing them. Kestrel distinguishes genuine implementations from advertised claims not backed by the underlying code, attributes each detection to its originating codebase, and, in a forensic disk-image trial, recovered a detection from unallocated space after the deleted binary could no longer be reconstructed. It thus provides a practical basis for cryptographic migration assurance, compliance verification, software supply-chain inspection, and post-quantum forensic examination.

cs.CR↗

arXiv2026

A Hybrid Post-Quantum Encryption Architecture with Self-Hosted Key Management for SME Cloud Data Protection

Harvesting ciphertext from cloud storage needs no quantum computer; decrypting it later does. That gap is the harvest-now-decrypt-later exposure: anything protected by RSA or ECDH today that must stay secret for decades is already compromised. Small and medium-sized enterprises are least able to respond: they neither run the infrastructure on which their data sits on nor employ a cryptographer. Bespoke migration suits firms with security budgets; a managed key service relocates trust rather than removing it. The obstacle is architectural, not cryptographic. We present Quantum Cloud Guard (QCG), a software-only three-layer architecture. No prior SME-oriented system combines its three elements: client-side hybrid post-quantum encryption, self-hosted key custody with client-verifiable ML-DSA-87 signatures on served keys, and an integrated application-layer abuse-prevention gateway. Files never leave the client: each is sealed under AES-256-GCM, its key wrapped to an ML-KEM-1024 public key from the enterprise's key service. The enterprise alone administers it; it signs every key with ML-DSA-87, so a client that pinned it detects substitution. Separating key custody from data custody is the point: a provider holding both can read the data. On a 24 MHz STM32F407, ML-KEM-1024 key generation takes 40.8 ms and decapsulation 44.0 ms; on the server every post-quantum operation stays sub-millisecond, signing adding 0.24 ms per request. The service runs on a 4.49 EUR/month virtual server. Under sustained flooding, the in-process gateway Sentinel Gate rejected 98.8% of attack traffic while a legitimate client's median latency moved from 621 to 625 ms. Being single-source, this shows filtering effectiveness, not DDoS resilience.

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