Data for 2013
Government Cyber Security Capacity, 2013
2013, 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, 2013 covers 176 countries. Israel is highest, at 3.497; Timor-Leste is lowest, at -3.069. The middle country reads -0.206. Against 2012, 29 values changed (26 up, 3 down), the same countries are covered.
Government Cyber Security Capacity · Data for 2013
HighestIsrael
3.497LowestTimor-Leste
-3.069Shaded 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, 2013, 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 | PRKEastern Asia | 2.771 |
| 3 | MYSSouth-eastern Asia | 2.741 |
| 4 | RUSEastern Europe | 2.678 |
| 5 | CHNEastern Asia | 2.570 |
| 6 | ESTNorthern Europe | 2.548 |
| 7 | AREWestern Asia | 2.334 |
| 8 | FRAWestern Europe | 1.960 |
| 9 | KOREastern Asia | 1.945 |
| 10 | USANorthern America | 1.896 |
| 11 | CANNorthern America | 1.888 |
| 12 | SGPSouth-eastern Asia | 1.851 |
| 13 | LVANorthern Europe | 1.818 |
| 14 | GBRNorthern Europe | 1.746 |
| 15 | TWNEastern Asia | 1.739 |
| 16 | ESPSouthern Europe | 1.660 |
| 17 | KWTWestern Asia | 1.652 |
| 18 | TUNNorthern Africa | 1.633 |
| 19 | JPNEastern Asia | 1.518 |
| 20 | HUNEastern Europe | 1.477 |
| 21 | CHLSouth America | 1.466 |
| 22 | PRTSouthern Europe | 1.422 |
| 23 | SWENorthern Europe | 1.418 |
| 24 | FINNorthern Europe | 1.417 |
| 25 | AUTWestern Europe | 1.409 |
| 26 | DNKNorthern Europe | 1.326 |
| 27 | AUSAustralia and New Zealand | 1.249 |
| 28 | NZLAustralia and New Zealand | 1.195 |
| 29 | JORWestern Asia | 1.190 |
| 30 | SAUWestern Asia | 1.100 |
| 31 | QATWestern Asia | 1.091 |
| 32 | INDSouthern Asia | 1.076 |
| 33 | ROUEastern Europe | 1.063 |
| 34 | POLEastern Europe | 1.033 |
| 35 | MARNorthern Africa | 0.990 |
| 36 | URYSouth America | 0.959 |
| 37 | BRASouth America | 0.903 |
| 38 | ARMWestern Asia | 0.885 |
| 39 | AZEWestern Asia | 0.871 |
| 40 | MUSEastern Africa | 0.869 |
| 41 | NLDWestern Europe | 0.851 |
| 42 | BLREastern Europe | 0.842 |
| 43 | LUXWestern Europe | 0.833 |
| 44 | SYRWestern Asia | 0.825 |
| 45 | EGYNorthern Africa | 0.823 |
| 46 | IRNSouthern Asia | 0.778 |
| 47 | ARGSouth America | 0.744 |
| 48 | CHEWestern Europe | 0.709 |
| 49 | CUBCaribbean | 0.706 |
| 50 | HKGEastern Asia | 0.682 |
| 51 | BHRWestern Asia | 0.662 |
| 52 | TURWestern Asia | 0.639 |
| 53 | KAZCentral Asia | 0.631 |
| 54 | RWAEastern Africa | 0.566 |
| 55 | DEUWestern Europe | 0.560 |
| 56 | MNGEastern Asia | 0.559 |
| 57 | DZANorthern Africa | 0.521 |
| 58 | MRTWestern Africa | 0.498 |
| 59 | VNMSouth-eastern Asia | 0.476 |
| 60 | NORNorthern Europe | 0.473 |
| 61 | GRCSouthern Europe | 0.469 |
| 62 | CYPWestern Asia | 0.464 |
| 63 | MDAEastern Europe | 0.438 |
| 64 | ITASouthern Europe | 0.411 |
| 65 | LKASouthern Asia | 0.385 |
| 66 | BELWestern Europe | 0.372 |
| 67 | LTUNorthern Europe | 0.367 |
| 68 | MLTSouthern Europe | 0.350 |
| 69 | GEOWestern Asia | 0.347 |
| 70 | PAKSouthern Asia | 0.263 |
| 71 | BGDSouthern Asia | 0.220 |
| 72 | ECUSouth America | 0.190 |
| 73 | ZAFSouthern Africa | 0.189 |
| 74 | IRLNorthern Europe | 0.184 |
| 75 | HRVSouthern Europe | 0.147 |
| 76 | SENWestern Africa | 0.135 |
| =77 | DOMCaribbean | 0.127 |
| =77 | PANCentral America | 0.127 |
| 79 | VENSouth America | 0.113 |
| 80 | ZWEEastern Africa | 0.099 |
| 81 | MEXCentral America | 0.081 |
| 82 | MNESouthern Europe | 0.080 |
| 83 | UGAEastern Africa | -0.090 |
| 84 | JAMCaribbean | -0.102 |
| 85 | OMNWestern Asia | -0.136 |
| 86 | CZEEastern Europe | -0.185 |
| 87 | KENEastern Africa | -0.193 |
| 88 | SWZSouthern Africa | -0.196 |
| 89 | ZMBEastern Africa | -0.215 |
| 90 | BWASouthern Africa | -0.234 |
| 91 | BRBCaribbean | -0.270 |
| 92 | LBNWestern Asia | -0.308 |
| 93 | IDNSouth-eastern Asia | -0.312 |
| 94 | TGOWestern Africa | -0.313 |
| 95 | GNQMiddle Africa | -0.340 |
| 96 | CRICentral America | -0.393 |
| 97 | AGOMiddle Africa | -0.439 |
| 98 | THASouth-eastern Asia | -0.487 |
| 99 | SDNNorthern Africa | -0.499 |
| 100 | SYCEastern Africa | -0.514 |
| 101 | CIVWestern Africa | -0.565 |
| 102 | UKREastern Europe | -0.606 |
| 103 | PHLSouth-eastern Asia | -0.608 |
| 104 | UZBCentral Asia | -0.616 |
| 105 | SVKEastern Europe | -0.628 |
| 106 | YEMWestern Asia | -0.637 |
| 107 | GABMiddle Africa | -0.653 |
| 108 | ETHEastern Africa | -0.663 |
| 109 | FJIMelanesia | -0.688 |
| 110 | BIHSouthern Europe | -0.702 |
| 111 | COGMiddle Africa | -0.747 |
| 112 | LSOSouthern Africa | -0.759 |
| 113 | CPVWestern Africa | -0.786 |
| 114 | COLSouth America | -0.789 |
| 115 | SVNSouthern Europe | -0.846 |
| 116 | MDVSouthern Asia | -0.862 |
| 117 | TKMCentral Asia | -0.870 |
| 118 | ERIEastern Africa | -0.874 |
| 119 | NAMSouthern Africa | -0.878 |
| 120 | BGREastern Europe | -0.884 |
| 121 | GHAWestern Africa | -0.894 |
| 122 | BENWestern Africa | -0.905 |
| 123 | SURSouth America | -0.916 |
| 124 | PERSouth America | -0.924 |
| 125 | SRBSouthern Europe | -0.925 |
| 126 | MMRSouth-eastern Asia | -0.928 |
| 127 | GMBWestern Africa | -0.947 |
| 128 | BTNSouthern Asia | -0.974 |
| 129 | TZAEastern Africa | -0.993 |
| 130 | NERWestern Africa | -1.028 |
| =131 | ISLNorthern Europe | -1.034 |
| =131 | IRQWestern Asia | -1.034 |
| 133 | BOLSouth America | -1.085 |
| 134 | MOZEastern Africa | -1.097 |
| 135 | SomalilandXSLEastern Africa | -1.170 |
| 136 | NGAWestern Africa | -1.171 |
| 137 | TJKCentral Asia | -1.261 |
| 138 | KGZCentral Asia | -1.300 |
| 139 | GTMCentral America | -1.306 |
| 140 | TTOCaribbean | -1.313 |
| 141 | MKDSouthern Europe | -1.319 |
| 142 | STPMiddle Africa | -1.339 |
| 143 | DJIEastern Africa | -1.370 |
| 144 | CODMiddle Africa | -1.374 |
| 145 | PRYSouth America | -1.376 |
| 146 | COMEastern Africa | -1.385 |
| 147 | VUTMelanesia | -1.426 |
| 148 | SSDEastern Africa | -1.436 |
| 149 | TCDMiddle Africa | -1.457 |
| 150 | ALBSouthern Europe | -1.507 |
| 151 | NICCentral America | -1.530 |
| 152 | NPLSouthern Asia | -1.536 |
| 153 | CMRMiddle Africa | -1.549 |
| 154 | HNDCentral America | -1.597 |
| 155 | GUYSouth America | -1.625 |
| 156 | SLVCentral America | -1.709 |
| 157 | PNGMelanesia | -1.711 |
| 158 | SOMEastern Africa | -1.733 |
| 159 | MWIEastern Africa | -1.803 |
| 160 | BDIEastern Africa | -1.858 |
| 161 | MDGEastern Africa | -1.865 |
| 162 | MLIWestern Africa | -1.942 |
| 163 | BFAWestern Africa | -2.013 |
| 164 | LBYNorthern Africa | -2.065 |
| 165 | KHMSouth-eastern Asia | -2.081 |
| 166 | HTICaribbean | -2.109 |
| 167 | CAFMiddle Africa | -2.215 |
| 168 | XKXSouthern Europe | -2.280 |
| 169 | AFGSouthern Asia | -2.350 |
| 170 | SLEWestern Africa | -2.363 |
| 171 | LAOSouth-eastern Asia | -2.364 |
| 172 | GINWestern Africa | -2.372 |
| 173 | LBRWestern Africa | -2.402 |
| 174 | GNBWestern Africa | -2.516 |
| 175 | SLBMelanesia | -3.050 |
| 176 | TLSSouth-eastern Asia | -3.069 |
02In 2013
At either end
The 5 countries at each end of the headline.
Highest
- 1
Israel3.497
- 2
North Korea2.771
- 3
Malaysia2.741
- 4
Russia2.678
- 5
China2.570
Lowest
- 176
Timor-Leste-3.069
- 175
Solomon Islands-3.050
- 174
Guinea-Bissau-2.516
- 173
Liberia-2.402
- 172
Guinea-2.372
A higher value is the better result. The middle country reads -0.206. “Shared” marks a value another country also holds.
032012 → 2013
Since 2012
- +0 / −0countries joined / left
- 29values changed, of 176 in both
- 26 · 3rose · fell
- 147unchanged
Rose most
Dominican Republic-0.625 → 0.127+0.752
Mozambique-1.768 → -1.097+0.671
United Arab Emirates1.726 → 2.334+0.608
Bolivia-1.627 → -1.085+0.542
Austria0.931 → 1.409+0.478
Fell most
Bulgaria-0.509 → -0.884−0.375
United States2.153 → 1.896−0.257
Guinea-2.328 → -2.372−0.044
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 2013.
174 distinct values among 176
Values are stored exactly as published, to 3 decimals. 2 countries share 0.127. 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-2013-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 (2013). Government Cyber Security Capacity, 2013 [data set], describing 2013. As held by Nations Inquiry, https://nationsinquiry.com/datasets/cyber-security-capacity/2013
0626 held
Other years
‹ The year before
Government Cyber Security Capacity, 2012176 countries
The year after ›
Government Cyber Security Capacity, 2014176 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