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Anatomical Grounding and Leakage-Aware Multimodal Contrastive Learning for Alzheimer's Disease Classification from Structural MRI
Study of label leakage and anatomical grounding in multimodal MRI models for Alzheimer's staging shows cognitive-score fusion accuracy of 87.3% is leakage-driven.
The authors train a ResNet18 slice-based encoder with a one-layer Transformer on 1,075 ADNI-1 T1 MRI scans, using FastSurfer segmentations and YOLOv8 localization (mAP_50 above 0.96) as anatomical reference. Grad-CAM shows the image-only classifier often attends to skull and background rather than disease-relevant structures. A CLIP-style image-tabular contrastive framework organized along a label-leakage spectrum yields 87.3% three-way accuracy with cognitive scores versus 73.0% with regional volumes, and cropping to the medial temporal lobe raises image-only accuracy from 58.7% to 65.1%. Results come from single runs on a small balanced test set with reported confidence intervals.
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Cross-modal learning for SAR target recognition using optical vision foundation models
Frozen DINOv3 optical prototypes supervise SAR target recognition without EO/SAR pairs, improving classification on the heavily imbalanced UNICORNv2 dataset.
The framework aligns SAR embeddings to class-level prototypes built from a frozen DINOv3 electro-optical encoder, requiring no strict EO/SAR image pairs. At inference the SAR model operates independently without access to optical imagery. On UNICORNv2, a civilian vehicle dataset with heavy speckle and severe class imbalance, EO prototype alignment improves accuracy over frozen DINOv3, SAR-only finetuning, and unpaired distribution alignment baselines.
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Top 10 Best Cloud Access Security Broker (CASB) Solutions in 2026
2026 CASB guide ranks Netskope first for depth and Microsoft Defender for Cloud Apps for Microsoft estates, as standalone CASB fades into SSE.
Buyer's guide covers ten CASB products across four enforcement modes: API, forward proxy, reverse proxy and log-based discovery. Netskope leads on SaaS activity context depth, while Microsoft Defender for Cloud Apps wins on Microsoft 365 E5 estate economics. The guide argues standalone CASB purchases have largely disappeared into SSE platforms and increasingly overlap with SSPM.
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MemSentry: A Framework for Detecting Persistent Memory Poisoning in Agentic AI
MemSentry intercepts persistent-memory writes in agentic AI to catch memory poisoning, reaching 91.7% accuracy with SBERT+LR classification.
Memory poisoning lets adversaries plant crafted content in an agent's long-term memory to suppress security alerts, enable privilege escalation, or override policies without modifying model weights or system prompts. The paper presents MemSentry, a configuration-driven framework that evaluates proposed persistent-memory writes on source trust, semantic risk, attack radius over a dependency DAG, access risk, and a signed security-state delta to issue deterministic Accept, Review, or Quarantine decisions. Across 1,000 GPT-4-generated scenarios on a 20-asset dependency DAG, SBERT+LR achieved 91.7% accuracy and 0.908 macro-F1, all four classifiers detected 100% of external quarantine-class threats, and verified-insider writes are escalated for human review rather than auto-quarantined.
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Autoencoder Is All You Need: Profiling and Detecting Malicious DNS Traffic
Palo Alto Unit 42 details an autoencoder-based method that profiles DNS traffic to detect C2 and malicious domains, blocking ~374,000 malicious DNS requests daily.
Unit 42 built an RNN-based autoencoder that compresses DNS traffic time series into fixed-dimensional 'DNS profiles' for each domain and device. Downstream classification, clustering, and anomaly detection modules flag suspicious domains, capturing 170 emerging suspicious domains in May 2024. Signatures block roughly 374,000 malicious DNS requests daily and run in the Advanced DNS Security service, with detections shared to Advanced URL Filtering. Case studies link DNS traffic patterns to C2 beaconing, dynamic DNS abuse, and DNS tunneling for data exfiltration.
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