Data for 2019
Government Cyber Security Capacity, 2019
2019, as V-Dem Institute’s 2026 release gives it · stored as published, never rewritten
V-Dem's measure of government cyber-security capacity asks whether a state has the skilled staff and resources to protect itself against cyber attacks, from none at all to attacks by highly skilled actors. It is an expert-coded estimate on an open-ended scale centred near zero, and a higher figure means more capacity.
Government Cyber Security Capacity, 2019 covers 176 countries. Israel is highest, at 3.497; Liberia is lowest, at -2.660. The middle country reads 0.097. Against 2018, 75 values changed (43 up, 32 down), the same countries are covered.
Government Cyber Security Capacity · Data for 2019
HighestIsrael
3.497LowestLiberia
-2.660Shaded by value in five groups of equal size, darkest at the better end.
01Position · derived
The table
Every country and every column of Government Cyber Security Capacity, 2019, as published. V-Dem Institute ranks nobody on this measure; the position is derived here by ordering the published values. “=” marks a shared position.
Showing 25 of 176 countries · select a heading to sort
| derived | ||
|---|---|---|
| 1 | ISRWestern Asia | 3.497 |
| 2 | ESTNorthern Europe | 3.076 |
| 3 | RUSEastern Europe | 2.819 |
| 4 | PRKEastern Asia | 2.771 |
| 5 | MYSSouth-eastern Asia | 2.741 |
| 6 | SGPSouth-eastern Asia | 2.689 |
| 7 | CHNEastern Asia | 2.570 |
| 8 | AREWestern Asia | 2.537 |
| 9 | CANNorthern America | 2.351 |
| 10 | KOREastern Asia | 2.231 |
| 11 | LVANorthern Europe | 2.020 |
| 12 | FRAWestern Europe | 1.960 |
| 13 | SAUWestern Asia | 1.928 |
| 14 | QATWestern Asia | 1.907 |
| 15 | LTUNorthern Europe | 1.832 |
| 16 | ESPSouthern Europe | 1.829 |
| 17 | KWTWestern Asia | 1.828 |
| 18 | DNKNorthern Europe | 1.778 |
| 19 | GBRNorthern Europe | 1.746 |
| 20 | USANorthern America | 1.653 |
| 21 | TUNNorthern Africa | 1.633 |
| 22 | ISLNorthern Europe | 1.572 |
| 23 | TWNEastern Asia | 1.553 |
| 24 | JPNEastern Asia | 1.550 |
| 25 | HUNEastern Europe | 1.477 |
| 26 | SWENorthern Europe | 1.418 |
| =27 | CHLSouth America | 1.417 |
| =27 | FINNorthern Europe | 1.417 |
| 29 | CHEWestern Europe | 1.375 |
| 30 | EGYNorthern Africa | 1.297 |
| 31 | ROUEastern Europe | 1.287 |
| 32 | PRTSouthern Europe | 1.277 |
| 33 | JORWestern Asia | 1.190 |
| 34 | MUSEastern Africa | 1.114 |
| 35 | AUTWestern Europe | 1.104 |
| 36 | KAZCentral Asia | 1.014 |
| 37 | MARNorthern Africa | 0.990 |
| 38 | SYRWestern Asia | 0.982 |
| 39 | ARMWestern Asia | 0.978 |
| 40 | INDSouthern Asia | 0.973 |
| 41 | URYSouth America | 0.959 |
| 42 | IRNSouthern Asia | 0.939 |
| 43 | BLREastern Europe | 0.938 |
| 44 | ARGSouth America | 0.933 |
| 45 | PAKSouthern Asia | 0.924 |
| 46 | BRASouth America | 0.903 |
| 47 | LUXWestern Europe | 0.833 |
| 48 | RWAEastern Africa | 0.831 |
| 49 | NZLAustralia and New Zealand | 0.811 |
| 50 | NLDWestern Europe | 0.797 |
| 51 | POLEastern Europe | 0.768 |
| 52 | AZEWestern Asia | 0.744 |
| 53 | CZEEastern Europe | 0.722 |
| 54 | CYPWestern Asia | 0.710 |
| 55 | CUBCaribbean | 0.706 |
| 56 | MNGEastern Asia | 0.698 |
| 57 | DEUWestern Europe | 0.676 |
| 58 | TURWestern Asia | 0.639 |
| 59 | AUSAustralia and New Zealand | 0.572 |
| 60 | BELWestern Europe | 0.558 |
| 61 | MDAEastern Europe | 0.555 |
| 62 | GEOWestern Asia | 0.538 |
| 63 | HKGEastern Asia | 0.536 |
| 64 | UKREastern Europe | 0.534 |
| 65 | IRLNorthern Europe | 0.533 |
| 66 | DZANorthern Africa | 0.521 |
| 67 | VNMSouth-eastern Asia | 0.476 |
| 68 | MEXCentral America | 0.472 |
| 69 | GRCSouthern Europe | 0.469 |
| 70 | NORNorthern Europe | 0.458 |
| 71 | ITASouthern Europe | 0.439 |
| 72 | VENSouth America | 0.432 |
| 73 | LKASouthern Asia | 0.392 |
| 74 | HRVSouthern Europe | 0.388 |
| =75 | MLTSouthern Europe | 0.350 |
| =75 | SVKEastern Europe | 0.350 |
| 77 | SENWestern Africa | 0.325 |
| 78 | MRTWestern Africa | 0.253 |
| 79 | BHRWestern Asia | 0.235 |
| 80 | BGDSouthern Asia | 0.206 |
| 81 | ECUSouth America | 0.190 |
| 82 | ZAFSouthern Africa | 0.189 |
| =83 | DOMCaribbean | 0.127 |
| =83 | PANCentral America | 0.127 |
| 85 | ZMBEastern Africa | 0.114 |
| 86 | IDNSouth-eastern Asia | 0.104 |
| 87 | ZWEEastern Africa | 0.099 |
| 88 | GABMiddle Africa | 0.097 |
| 89 | UGAEastern Africa | 0.096 |
| 90 | MNESouthern Europe | 0.080 |
| 91 | TGOWestern Africa | 0.059 |
| 92 | THASouth-eastern Asia | -0.021 |
| 93 | TZAEastern Africa | -0.039 |
| 94 | LBNWestern Asia | -0.072 |
| 95 | SRBSouthern Europe | -0.082 |
| 96 | PHLSouth-eastern Asia | -0.089 |
| 97 | BRBCaribbean | -0.098 |
| 98 | BWASouthern Africa | -0.101 |
| 99 | JAMCaribbean | -0.104 |
| 100 | OMNWestern Asia | -0.136 |
| 101 | KENEastern Africa | -0.193 |
| 102 | SWZSouthern Africa | -0.196 |
| 103 | HNDCentral America | -0.239 |
| 104 | FJIMelanesia | -0.322 |
| 105 | GNQMiddle Africa | -0.340 |
| 106 | MDVSouthern Asia | -0.386 |
| 107 | CRICentral America | -0.393 |
| 108 | BGREastern Europe | -0.401 |
| 109 | CIVWestern Africa | -0.413 |
| 110 | AGOMiddle Africa | -0.439 |
| 111 | SDNNorthern Africa | -0.499 |
| 112 | UZBCentral Asia | -0.553 |
| 113 | GHAWestern Africa | -0.583 |
| 114 | BTNSouthern Asia | -0.603 |
| 115 | SURSouth America | -0.676 |
| 116 | ETHEastern Africa | -0.677 |
| 117 | BIHSouthern Europe | -0.702 |
| 118 | MKDSouthern Europe | -0.719 |
| 119 | LSOSouthern Africa | -0.721 |
| 120 | IRQWestern Asia | -0.726 |
| =121 | CPVWestern Africa | -0.786 |
| =121 | YEMWestern Asia | -0.786 |
| 123 | SYCEastern Africa | -0.790 |
| 124 | NPLSouthern Asia | -0.805 |
| 125 | GMBWestern Africa | -0.809 |
| 126 | BOLSouth America | -0.817 |
| 127 | MMRSouth-eastern Asia | -0.821 |
| 128 | TCDMiddle Africa | -0.823 |
| 129 | SVNSouthern Europe | -0.846 |
| 130 | KGZCentral Asia | -0.850 |
| 131 | ERIEastern Africa | -0.874 |
| 132 | NAMSouthern Africa | -0.878 |
| 133 | BENWestern Africa | -0.905 |
| 134 | PERSouth America | -0.924 |
| 135 | COLSouth America | -0.926 |
| 136 | TKMCentral Asia | -0.936 |
| 137 | TJKCentral Asia | -0.989 |
| 138 | CMRMiddle Africa | -1.031 |
| 139 | NGAWestern Africa | -1.171 |
| 140 | MDGEastern Africa | -1.198 |
| 141 | PRYSouth America | -1.226 |
| 142 | GTMCentral America | -1.306 |
| 143 | TTOCaribbean | -1.313 |
| 144 | NICCentral America | -1.315 |
| 145 | STPMiddle Africa | -1.339 |
| 146 | MOZEastern Africa | -1.351 |
| 147 | MWIEastern Africa | -1.362 |
| 148 | DJIEastern Africa | -1.370 |
| 149 | CODMiddle Africa | -1.374 |
| 150 | COMEastern Africa | -1.385 |
| 151 | SLEWestern Africa | -1.389 |
| 152 | VUTMelanesia | -1.426 |
| 153 | NERWestern Africa | -1.428 |
| 154 | SSDEastern Africa | -1.436 |
| 155 | ALBSouthern Europe | -1.507 |
| 156 | PNGMelanesia | -1.529 |
| 157 | LAOSouth-eastern Asia | -1.574 |
| 158 | GUYSouth America | -1.625 |
| 159 | SOMEastern Africa | -1.629 |
| 160 | COGMiddle Africa | -1.632 |
| 161 | SLVCentral America | -1.646 |
| 162 | BFAWestern Africa | -1.647 |
| 163 | CAFMiddle Africa | -1.774 |
| 164 | BDIEastern Africa | -1.783 |
| 165 | AFGSouthern Asia | -1.814 |
| 166 | SomalilandXSLEastern Africa | -1.928 |
| 167 | MLIWestern Africa | -1.942 |
| 168 | TLSSouth-eastern Asia | -2.007 |
| 169 | XKXSouthern Europe | -2.008 |
| 170 | LBYNorthern Africa | -2.065 |
| 171 | KHMSouth-eastern Asia | -2.081 |
| 172 | HTICaribbean | -2.109 |
| 173 | GNBWestern Africa | -2.122 |
| 174 | SLBMelanesia | -2.548 |
| 175 | GINWestern Africa | -2.576 |
| 176 | LBRWestern Africa | -2.660 |
02In 2019
At either end
The 5 countries at each end of the headline.
Highest
- 1
Israel3.497
- 2
Estonia3.076
- 3
Russia2.819
- 4
North Korea2.771
- 5
Malaysia2.741
Lowest
- 176
Liberia-2.660
- 175
Guinea-2.576
- 174
Solomon Islands-2.548
- 173
Guinea-Bissau-2.122
- 172
Haiti-2.109
A higher value is the better result. The middle country reads 0.097. “Shared” marks a value another country also holds.
032018 → 2019
Since 2018
- +0 / −0countries joined / left
- 75values changed, of 176 in both
- 43 · 32rose · fell
- 101unchanged
Rose most
Iceland-1.034 → 1.572+2.606
Honduras-1.489 → -0.239+1.250
Gabon-0.653 → 0.097+0.750
Chad-1.457 → -0.823+0.634
Sierra Leone-1.991 → -1.389+0.602
Fell most
Australia1.487 → 0.572−0.915
Republic of the Congo-0.747 → -1.632−0.885
- Somaliland-1.170 → -1.928−0.758
Seychelles-0.166 → -0.790−0.624
Bahrain0.795 → 0.235−0.560
04Caveats
Read before you use
One year of the 2026 release
Every year in this series comes from V-Dem Institute’s 2026 release, recalculated on one method, so a change from one year to the next is not a revision. It can differ from what was first published for 2019.
172 distinct values among 176
Values are stored exactly as published, to 3 decimals. 2 countries share 1.417. Countries sharing a value share a position too.
Nothing missing
Every one of the 176 countries has every column.
05The files
Download and cite
- .csv
For a spreadsheet or code
176 rows · 4.9 KB · UTF-8, opens in Excel
Opens with 11 lines of source notes; the table starts on row 13.
Download cyber-security-capacity-2019-nations-inquiry.csv - ↗
The publisher’s original
V-Dem Institute’s own file, on its own site.
V-Dem-CY-FullOthers-v16_csv.zip
What this site changed: Reshaped to one row per country, with its ISO code; no value recalculated, rescaled or rounded. In full
Licence: CC BY-SA 4.0 · what it allows, in plain words
Cite this edition
V-Dem Institute, University of Gothenburg (2019). Government Cyber Security Capacity, 2019 [data set], describing 2019. As held by Nations Inquiry, https://nationsinquiry.com/datasets/cyber-security-capacity/2019
0626 held
Other years
‹ The year before
Government Cyber Security Capacity, 2018176 countries
The year after ›
Government Cyber Security Capacity, 2020176 countries
All of them
Government Cyber Security Capacity: every year26 held, with the data dictionary, coverage and licence.
How it has moved, charted by country