DAHUA SD52C430U-HNI 4MP 30x PTZ Network Camera
SKU: 14083636297

DAHUA SD52C430U-HNI 4MP 30x PTZ Network Camera

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Description

DAHUA SD52C430U-HNI 4MP 30x PTZ Network CameraSD52C430U HNI 4MP 30x PTZ Network Camera > 1 3 4Megapixel CMOS > Powerful 30x optical zoom > H. 265 Encoding > Max. 25 30fps@4M 3M, 25 30 50 60fps@1080P > Auto tracking and IVS > Support PoE+ > IK10 Product Data Camera Image Sensor 1 3 CMOS Effective Pixels 2592(H) x 1520(V), 4 Megapixels RAM ROM 1024M 128M Scanning System Progressive Electronic Shutter Speed 1 1s~1 30,000s Minimum Illumination Color: 0. 05Lux@F1. 6; B W: 0. 005Lux@F1. 6 S N Ratio

SD52C430U-HNI 

4MP 30x PTZ Network Camera

> 1/3” 4Megapixel CMOS
> Powerful 30x optical zoom
> H.265 Encoding
> Max. 25/30fps@4M/3M, 25/30/50/60fps@1080P
> Auto-tracking and IVS
> Support PoE+
> IK10


Product Data

Camera

Image Sensor

1/3” CMOS

Effective Pixels

2592(H) x 1520(V), 4 Megapixels

RAM/ROM

1024M/128M

Scanning System

Progressive

Electronic Shutter Speed

1/1s~1/30,000s

Minimum Illumination

Color: [email protected]; B/W: [email protected]

S/N Ratio

More than 55dB

IR Distance

N/A

IR On/Off Control

N/A

IR LEDs

N/A

Lens

Focal Length

4.5mm~135mm

Max. Aperture

F1.6 ~ F4.4

Angle of View

H: 60° ~ 2.2°

Optical Zoom

30x

Focus Control

Auto/Manual

Close Focus Distance

100mm~ 1000mm

DORI Distance

Note: The DORI distance is a “general proximity” of distance which makes it easy to pinpoint the right camera for your needs. The DORI distance is calculated based on sensor specification and lab test result according to EN 62676-4 which defines the criteria for Detect, Observe, Recognize and Identify respectively.

Detect

Observe

Recognize

Identify

2700m(8858ft)

1080m(3543ft)

540m(1772ft)

270m(886ft)

PTZ

Pan/Tilt Range

Pan: 0° ~ 360° endless; Tilt: 0° ~ 90°,auto flip 180°

Manual Control Speed

Pan: 0.1° ~350° /s; Tilt: 0.1° ~250° /s

Preset Speed

Pan: 500° /s; Tilt: 500° /s

Presets

300

PTZ Mode

5 Pattern, 8 Tour, Auto Pan ,Auto Scan

Speed Setup

Human-oriented focal Length/ speed adaptation

Power up Action

Auto restore to previous PTZ and lens status after

power failure

Idle Motion

Activate Preset/ Scan/ Tour/ Pattern if there is no

command in the specified period

Protocol

DH-SD

Intelligence

Event Trigger

Motion detection, Video tampering , Scene changing, Network disconnection, IP address conflict, Illegal Access, Storage anomaly

Auto Tracking

Support

IVS

Tripwire, Intrusion, Abandoned/Missing

Advanced Intelligent Functions

Face Detection, Heat Map

Video

Compression

H.265+/H.265/H.264+/H.264

Streaming Capability

3 Streams

Resolution

4M(2592×1520)/3M(2304×1296)/1080P(1920×1080)/720P(1280×720)/D1(704×576/704×480)/CIF(352×288/352×240)

Frame Rate

Main stream: 4M/3M(1~25/30fps), 1080P/1.3M/ 720P(1~50/60fps)

Sub stream1: D1/CIF(1 ~ 25/30fps)

Sub stream2: 1080P/1.3M/720P/D1/CIF (1~25/30fps)

Bit Rate Control

CBR/VBR

Bit Rate

H.265/H.264: 448K ~ 8192Kbps

Day/Night

Auto(ICR) / Color / B/W

Backlight Compensation

BLC / HLC / WDR (120dB)

White Balance

Auto, ATW, Indoor, Outdoor, Manual

Gain Control

Auto / Manual

Noise Reduction

Ultra DNR (2D/3D)

Motion Detection

Support

Region of Interest

Support

Electronic Image Stabilization (EIS)

Support

Defog

Support

Digital Zoom

16x

Flip

180°

Privacy Masking

Up to 24 areas

Audio

Compression

G.711a/G.711Mu/AAC/G.722 / G.726/G.729/MPEG2-L2

Network

Ethernet

RJ-45 (10Base-T/100Base-TX)

Protocol

IPv4/IPv6, HTTP, HTTPS, SSL, TCP/IP, UDP, UPnP,

ICMP, IGMP, SNMP, RTSP, RTP, SMTP, NTP, DHCP,

DNS,PPPOE,DDNS,FTP, IP Filter,QoS,Bonjour,802.1x

Interoperability

ONVIF Profile S&G, API

Streaming Method

Unicast / Multicast

Max. User Access

20 users

Edge Storage

NAS (Network Attached Storage),Local PC for instant recording, Micro SD card 256GB

Web Viewer

IE, Chrome, Firefox, Safari

Management Software

Smart PSS, DSS, DMSS

Smart Phone

IOS, Android

Certifications

Certifications

CE: EN55032/EN55024/EN50130-4

FCC: Part15 subpartB,ANSI C63.4- 2014

UL: UL60950-1+CAN/CSA C22.2,No.60950-1

Interface

Video Interface

N/A

RS485

N/A

Audio I/O

1/1

Alarm I/O

2/1

Electrical

Power Supply

AC24V/1.5A(±10%), PoE+(802.3at)

Power Consumption

13W

Environmental

Operating Conditions

-30°C ~ 60°C (-22°F ~ +140°F) / Less than 95% RH

Ingress Protection

N/A

Vandal Resistance

IK10

Construction

Casing

Metal

Dimensions

Φ198(mm) x 177(mm)

Net Weight

2.2kg(4.85lb)

Gross Weight

3.7kg(8.16lb)

Shipping Notes
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Exchange/Return Notes
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  • Final sale items are not eligible for returns or exchanges.
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SKU: 14083636297

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4.1 ★★★★★
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Product Reviews
E
eyal Fishman
Phoenix, US
★★★★★ 5
outstanding and highly informative book
Format: Paperback
MAoS - Malware Analysis on Steroids: Fighting Malware to the Death - Real-World Threats and Reverse Engineering Tactics by Uriel Kosayev is an outstanding and highly informative book. This is the second book I’ve read from him, after Antivirus Bypass Techniques, and once again I found the content to be extremely practical, well-structured, and insightful. Uriel has a way of explaining complex malware analysis and reverse engineering concepts in a way that is both approachable and deeply technical. The real-world tactics and examples make it not just a book you read once, but a reference you’ll return to often. Without a doubt, another excellent resource—I’m giving it 5 stars.
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Reviewed in the United States on September 10, 2025
A
Verified Purchase
Arthur Donkers
Alexandria, US
★★★★★ 4
good
Format: Paperback
Good practical content, quality of images could be improved
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Reviewed in the United States on October 13, 2025
Z
Zachi
Whiting, US
★★★★★ 5
Essential for Malware Hunters
Format: Hardcover
MAoS - Malware Analysis on Steroids is a clear, practical, and engaging guide to real-world malware threats. It blends hands-on reverse engineering tactics with modern case studies, making it both highly technical and easy to follow. Whether you’re new to malware analysis or a seasoned security pro, this book sharpens your skills and mindset for the fight against today’s threats.
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Reviewed in the United States on September 20, 2025
C
Verified Purchase
Cliente Amazon
Massapequa, US
★★★★★ 5
All OK.
Format: Paperback
All OK.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 23, 2024
E
Eugene
Waukegan, US
★★★★★ 5
Great book on Android malware reverse engineering and detection!
Format: Paperback
This book offers a holistic approach for learning how to deal with malware targeting Android platform. I find this book to be equally interesting to read for both people with little experience in the domain of malware analysis as quick-start guide as well as for experienced reverse engineers who would want to translate their knowledge from malware analysis in other platforms to Android. This book is definitely worth the time reading it. The first half of the book is a great source of information on reverse engineering Android malware. Chapters on categories of Android Malware and examples of the malware in the wild set up the necessary context for the readers and help to better understand why Android malware focuses on certain infection/monetization techniques. It also bring context in the evolution of mitigation and hardening in Android platform. Chapters on static and dynamic analysis are very practical and engaging to read which I probably enjoyed the most in the book. They teach readers how to do reverse engineering of Android malware -- covers tooling, methodologies, hints to look for in the code or binary artifacts when doing reverse engineering. The second half of the book is dedicated to using machine learning techniques for detecting malware. It starts with a concise yet self-contained necessary theoretical background. In my point of view the authors hit a very good balance for making material accurate and comprehensive yet easy to read and follow along for people without extensive background in the field (which is not a trivial thing for math texts). As it is probably impossible to fit all the necessary theoretical material in a single (or even couple of chapters) they text offers references to sources which cover certain topics in-depth -- for those readers who would like to dive deeper in machine learning. Finally, the book wraps with application of the discussed machine learning techniques to certain malware families.
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Reviewed in the United States on October 14, 2024

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