Data for 2011
Government Cyber Security Capacity, 2011
2011, 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, 2011 covers 176 countries. Israel is highest, at 3.497; Timor-Leste is lowest, at -3.069. The middle country reads -0.323. Against 2010, 22 values changed (20 up, 2 down), 1 country joined.
Government Cyber Security Capacity · Data for 2011
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, 2011, 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 | USANorthern America | 2.612 |
| 5 | CHNEastern Asia | 2.570 |
| 6 | ESTNorthern Europe | 2.548 |
| 7 | RUSEastern Europe | 2.240 |
| 8 | FRAWestern Europe | 1.960 |
| 9 | KOREastern Asia | 1.945 |
| 10 | SGPSouth-eastern Asia | 1.851 |
| 11 | GBRNorthern Europe | 1.746 |
| 12 | TWNEastern Asia | 1.739 |
| 13 | AREWestern Asia | 1.726 |
| 14 | CANNorthern America | 1.678 |
| 15 | HUNEastern Europe | 1.477 |
| 16 | TUNNorthern Africa | 1.474 |
| 17 | CHLSouth America | 1.466 |
| =18 | JPNEastern Asia | 1.422 |
| =18 | PRTSouthern Europe | 1.422 |
| 20 | SWENorthern Europe | 1.418 |
| 21 | FINNorthern Europe | 1.417 |
| 22 | KWTWestern Asia | 1.343 |
| 23 | DNKNorthern Europe | 1.326 |
| 24 | ESPSouthern Europe | 1.243 |
| 25 | AUSAustralia and New Zealand | 1.201 |
| 26 | JORWestern Asia | 1.190 |
| 27 | NZLAustralia and New Zealand | 1.114 |
| 28 | SAUWestern Asia | 1.100 |
| 29 | QATWestern Asia | 1.091 |
| 30 | ROUEastern Europe | 1.063 |
| 31 | INDSouthern Asia | 1.043 |
| 32 | GEOWestern Asia | 1.042 |
| 33 | MARNorthern Africa | 0.990 |
| 34 | LVANorthern Europe | 0.974 |
| 35 | URYSouth America | 0.959 |
| 36 | AUTWestern Europe | 0.931 |
| 37 | POLEastern Europe | 0.886 |
| 38 | ARMWestern Asia | 0.885 |
| 39 | AZEWestern Asia | 0.871 |
| 40 | NLDWestern Europe | 0.851 |
| 41 | BLREastern Europe | 0.842 |
| 42 | LUXWestern Europe | 0.833 |
| 43 | EGYNorthern Africa | 0.823 |
| 44 | IRNSouthern Asia | 0.778 |
| 45 | ARGSouth America | 0.744 |
| 46 | BRASouth America | 0.712 |
| 47 | CHEWestern Europe | 0.709 |
| 48 | CUBCaribbean | 0.706 |
| 49 | HKGEastern Asia | 0.682 |
| 50 | BHRWestern Asia | 0.662 |
| 51 | MUSEastern Africa | 0.638 |
| 52 | KAZCentral Asia | 0.631 |
| 53 | RWAEastern Africa | 0.566 |
| 54 | DEUWestern Europe | 0.560 |
| 55 | MNGEastern Asia | 0.559 |
| 56 | TURWestern Asia | 0.551 |
| 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 | MDAEastern Europe | 0.438 |
| 63 | ITASouthern Europe | 0.411 |
| 64 | LKASouthern Asia | 0.385 |
| 65 | BELWestern Europe | 0.372 |
| 66 | LTUNorthern Europe | 0.367 |
| 67 | MLTSouthern Europe | 0.350 |
| 68 | SYRWestern Asia | 0.296 |
| 69 | CYPWestern Asia | 0.278 |
| 70 | BGDSouthern Asia | 0.220 |
| 71 | ECUSouth America | 0.190 |
| 72 | ZAFSouthern Africa | 0.189 |
| 73 | SENWestern Africa | 0.135 |
| 74 | PANCentral America | 0.127 |
| 75 | ZWEEastern Africa | 0.099 |
| 76 | MNESouthern Europe | 0.080 |
| 77 | IRLNorthern Europe | 0.075 |
| 78 | PAKSouthern Asia | -0.012 |
| 79 | HRVSouthern Europe | -0.084 |
| 80 | MEXCentral America | -0.098 |
| 81 | JAMCaribbean | -0.102 |
| =82 | OMNWestern Asia | -0.136 |
| =82 | UGAEastern Africa | -0.136 |
| 84 | CZEEastern Europe | -0.185 |
| 85 | BWASouthern Africa | -0.234 |
| 86 | BRBCaribbean | -0.270 |
| 87 | LBNWestern Asia | -0.308 |
| 88 | TGOWestern Africa | -0.313 |
| 89 | SWZSouthern Africa | -0.332 |
| 90 | GNQMiddle Africa | -0.340 |
| 91 | VENSouth America | -0.349 |
| 92 | CRICentral America | -0.393 |
| 93 | AGOMiddle Africa | -0.439 |
| 94 | THASouth-eastern Asia | -0.487 |
| 95 | SDNNorthern Africa | -0.499 |
| 96 | KENEastern Africa | -0.503 |
| 97 | BGREastern Europe | -0.509 |
| 98 | SYCEastern Africa | -0.514 |
| 99 | CIVWestern Africa | -0.565 |
| 100 | IDNSouth-eastern Asia | -0.602 |
| 101 | PHLSouth-eastern Asia | -0.608 |
| 102 | UZBCentral Asia | -0.616 |
| 103 | DOMCaribbean | -0.625 |
| 104 | SVKEastern Europe | -0.628 |
| 105 | YEMWestern Asia | -0.637 |
| 106 | GABMiddle Africa | -0.653 |
| 107 | ETHEastern Africa | -0.663 |
| 108 | FJIMelanesia | -0.688 |
| 109 | COGMiddle Africa | -0.747 |
| 110 | BIHSouthern Europe | -0.755 |
| 111 | LSOSouthern Africa | -0.759 |
| 112 | UKREastern Europe | -0.773 |
| 113 | CPVWestern Africa | -0.786 |
| 114 | COLSouth America | -0.789 |
| 115 | SVNSouthern Europe | -0.846 |
| =116 | MDVSouthern Asia | -0.862 |
| =116 | ZMBEastern Africa | -0.862 |
| 118 | TKMCentral Asia | -0.870 |
| 119 | ERIEastern Africa | -0.874 |
| 120 | NAMSouthern Africa | -0.878 |
| 121 | GHAWestern Africa | -0.894 |
| 122 | BENWestern Africa | -0.905 |
| 123 | SURSouth America | -0.916 |
| 124 | GMBWestern Africa | -0.947 |
| 125 | BTNSouthern Asia | -0.974 |
| 126 | TZAEastern Africa | -0.993 |
| 127 | PERSouth America | -1.017 |
| 128 | NERWestern Africa | -1.028 |
| 129 | MMRSouth-eastern Asia | -1.030 |
| =130 | ISLNorthern Europe | -1.034 |
| =130 | IRQWestern Asia | -1.034 |
| 132 | SRBSouthern Europe | -1.165 |
| 133 | SomalilandXSLEastern Africa | -1.170 |
| 134 | NGAWestern Africa | -1.171 |
| 135 | TJKCentral Asia | -1.261 |
| 136 | TTOCaribbean | -1.313 |
| 137 | MKDSouthern Europe | -1.319 |
| 138 | STPMiddle Africa | -1.339 |
| 139 | CODMiddle Africa | -1.374 |
| 140 | PRYSouth America | -1.376 |
| 141 | COMEastern Africa | -1.385 |
| 142 | VUTMelanesia | -1.426 |
| 143 | TCDMiddle Africa | -1.457 |
| 144 | ALBSouthern Europe | -1.507 |
| 145 | NICCentral America | -1.530 |
| 146 | NPLSouthern Asia | -1.536 |
| 147 | CMRMiddle Africa | -1.549 |
| 148 | KGZCentral Asia | -1.564 |
| 149 | DJIEastern Africa | -1.569 |
| 150 | GTMCentral America | -1.591 |
| 151 | HNDCentral America | -1.597 |
| 152 | GUYSouth America | -1.625 |
| 153 | BOLSouth America | -1.627 |
| 154 | SLVCentral America | -1.709 |
| 155 | MOZEastern Africa | -1.768 |
| 156 | LBYNorthern Africa | -1.790 |
| 157 | MWIEastern Africa | -1.803 |
| 158 | SSDEastern Africa | -1.836 |
| 159 | BDIEastern Africa | -1.858 |
| 160 | MDGEastern Africa | -1.865 |
| 161 | PNGMelanesia | -1.908 |
| 162 | BFAWestern Africa | -2.013 |
| 163 | KHMSouth-eastern Asia | -2.081 |
| 164 | HTICaribbean | -2.109 |
| 165 | MLIWestern Africa | -2.197 |
| 166 | CAFMiddle Africa | -2.215 |
| 167 | XKXSouthern Europe | -2.280 |
| 168 | AFGSouthern Asia | -2.350 |
| 169 | GINWestern Africa | -2.358 |
| 170 | LAOSouth-eastern Asia | -2.364 |
| 171 | LBRWestern Africa | -2.402 |
| 172 | GNBWestern Africa | -2.516 |
| 173 | SOMEastern Africa | -2.571 |
| 174 | SLEWestern Africa | -2.988 |
| 175 | SLBMelanesia | -3.050 |
| 176 | TLSSouth-eastern Asia | -3.069 |
02In 2011
At either end
The 5 countries at each end of the headline.
Highest
- 1
Israel3.497
- 2
North Korea2.771
- 3
Malaysia2.741
- 4
United States2.612
- 5
China2.570
Lowest
- 176
Timor-Leste-3.069
- 175
Solomon Islands-3.050
- 174
Sierra Leone-2.988
- 173
Somalia-2.571
- 172
Guinea-Bissau-2.516
A higher value is the better result. The middle country reads -0.323. “Shared” marks a value another country also holds.
032010 → 2011
Since 2010
- +1 / −0countries joined / left
- 22values changed, of 175 in both
- 20 · 2rose · fell
- 153unchanged
Rose most
Tunisia0.940 → 1.474+0.534
Côte d’Ivoire-1.098 → -0.565+0.533
Georgia0.667 → 1.042+0.375
Guatemala-1.928 → -1.591+0.337
Germany0.229 → 0.560+0.331
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 2011.
172 distinct values among 176
Values are stored exactly as published, to 3 decimals. 2 countries share 1.422. 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-2011-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 (2011). Government Cyber Security Capacity, 2011 [data set], describing 2011. As held by Nations Inquiry, https://nationsinquiry.com/datasets/cyber-security-capacity/2011
0626 held
Other years
‹ The year before
Government Cyber Security Capacity, 2010175 countries
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Government Cyber Security Capacity, 2012176 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